JP2002358472A - Vehicle resale price analysis system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an article resale price analysis system which can objectively predict the resale price of a commodity to be resold without depending upon human experience. SOLUTION: This vehicle resale price analysis system which predicts information regarding the sell price, the remaining amount, or remaining value rate of a vehicle to be resold by using data (maker name, vehicle type, vehicle use, vehicle shape, vehicle type grade, new-vehicle price, travel distance at resale time, assessed evaluation at resale time, etc.), regarding vehicles having been resold, has a 1st step for extracting data regarding vehicles which were resold within a specific period, a 2nd step for extracting, using the data extracted in the 1st step, factors affecting vehicle resale prices through correlative analysis, and a 3rd step for obtaining a multiple-recurrence expression from the correlation between the extracted factors and data regarding the price of the already sold vehicle, and uses the multiple-recurrence expression obtained at the 3rd step to predict information regarding a predicted sale price, a predicted remaining amount, or a predicted remaining value rate of the vehicle to be resold.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle resale price analysis system for predicting information on a sale amount, a residual value, or a residual value rate of a vehicle before resale using data on a resold vehicle, and data on a resold vehicle. , A residual value profit / loss analysis system that predicts the residual value profit / loss of vehicles before resale, an asset valuation system that predicts the market value of vehicles at any time during the term of use by using data on vehicles that have already been resold, A residual value setting system that sets a residual value for a new contract vehicle using data about a vehicle, a residual value setting system that sets a residual value for a new contract item using data about a resold vehicle, and data that is used for a resold vehicle The present invention relates to a residual value setting system for setting a residual value for a new model.

[0002]

2. Description of the Related Art In general, the resale price of a vehicle after the expiration of a use contract is empirically determined from the year of registration of the vehicle in the first year, the mileage, and the like. , Sold to second-hand dealers, exhibited at bidding and auctions, or disposed of.

[0003]

However, the expected resale price based on human experience does not always have a clear basis, and the fluctuation of the expected price by the judge is not small.
In addition, since accurate resale forecasts cannot be made, wasteful transportation and losses at bids and auctions have occurred. On the other hand, for vehicles under lease contracts, rental contracts, or loan contracts with residual value, etc., the profit on sale at the time of resale is set as the residual value in advance, but the profit or loss from this residual value can only be determined at the time of sale. It is the current situation. On the other hand, the majority of the conventional companies, which are far from the actual state of ordinary profit, place importance on sales, and the majority said that the more subsidiaries and affiliated companies and the larger the sales, the better. However, at present, how much dividends can be paid to shareholders is an important factor, and the key point is that the company's management information is disclosed. The importance of information disclosure also applies to a company's “rating”. By the way, in the leasing business, it is important to provide new services, and the profits are fixed by controlling resale and creating a system to earn reliable profits at low cost. In other words, setting a competitive residual value is an extremely important factor. Further, if the residual value setting can be calculated rationally and the information can be disclosed, it is possible that the vehicle during the contract period can be financed as an asset-backed security. Thus, it is very important to construct a system for setting the residual value.

Accordingly, the present invention provides an article resale price analysis system capable of objectively predicting the amount of sale of an article before resale from data on the sale of articles such as vehicles already resold without relying on human experience. The purpose is to provide.
Another object of the present invention is to provide a vehicle resale price analysis system that can obtain information on an objective expected sale price and the like for a vehicle to be resold. It is another object of the present invention to provide a residual value profit / loss analysis system capable of obtaining objective residual value profit / loss information at the time of contract expiration for a vehicle during a use contract period. Another object of the present invention is to provide an asset evaluation system capable of obtaining objective market value information at any time regarding a vehicle during a use contract period. Another object of the present invention is to provide a residual value setting system capable of obtaining objective residual value prediction information on a new contract vehicle. It is another object of the present invention to provide a storage medium capable of acquiring a correlation equation or a table in which a correlation is obtained for obtaining an objective sale price or the like for a new contract vehicle. Another object of the present invention is to provide a storage medium capable of obtaining an objective sale price or the like for a new contract vehicle.
In addition, the present invention can obtain a correlation formula or a table in which a correlation is obtained for obtaining an objective sale amount or the like with respect to a new contract vehicle. It is an object of the present invention to provide a storage medium capable of outputting information about the storage medium. Another object of the present invention is to provide a display device capable of outputting information about a resold vehicle that has been a source of a predicted sale price or the like. Another object of the present invention is to provide a residual value setting system that can set a residual value for a new contract vehicle. Another object of the present invention is to provide a residual value setting system capable of setting a residual value for a new contract article. Another object of the present invention is to provide a residual value setting system capable of setting a residual value for a new model vehicle. Another object of the present invention is to provide a vehicle resale price analysis system capable of more accurately obtaining an expected sale price for an average vehicle having no special reason.

[0005]

According to the first aspect of the present invention, there is provided:
Vehicle resale price analysis system is based on manufacturer name, vehicle type name, vehicle
Application, vehicle shape, vehicle grade, certified model, model designation number
No., category number, mission, drive system, displacement,
Number, popular model, capacity and load capacity, engine model, engine
Number of cylinders, engine mechanism, tire size, turbocharger,
Shape, emission control, body size, automobile tax zone
Minutes, weight tax, insurance class, year of use contract, expiration of use contract
Year, use contract period, new car price, sale after expiration of use contract
Resale vehicles already sold, including amount, mileage at resale, and assessment at resale
Using the data on both, the sales price and residual value of the vehicle before resale
Amount or vehicle resale price for which information about residual value rate is predicted
Analysis system, resold vehicles that have been resold within a predetermined period
A first step of extracting data relating to both,
Using the data extracted in step 1, the vehicle resale price
Extract the factors that are affecting
Step 2 and the extracted factors and the sold amount
The third step of obtaining a multiple regression equation from the correlation with the data
Multiple regression equation obtained in the third step
The expected sale price, residual value, or residual
It is characterized in that it is used for predicting information relating to a price. Claim
The vehicle resale price analysis system according to item 2 of the present invention
Name, vehicle type, vehicle application, vehicle shape, vehicle grade, certification
Fixed model, model designation number, classification number, mission, drive
Operating system, displacement, number of doors, popular model, capacity and load capacity,
Engine model, number of engine cylinders, engine mechanism, tires
Size, turbocharger, roof shape, emission control, body support
Tax, car tax classification, weight tax, insurance class, use contract
Year, expiration year of use contract, use contract period, new car price, use
Sale price after contract expiration, mileage at resale, assessment at resale
Cars before resale using data on resold vehicles, such as evaluations
Forecast information about the sale amount, residual value, or residual value
Vehicle resale price analysis system
First method to extract data on sold resold vehicles
Using the steps and the data extracted in the first step,
The new car price and the sale price or the sale price divided by the new car price
Obtain first equation data showing correlation with power rate
The second step and the data extracted in the first step
Using the data, the mileage and the amount of sale or the amount of sale
The second equation data showing the correlation with the residual value rate
Acquiring a third step, and acquiring the first equation data and
And average mileage using the second equation data
Fourth step of obtaining first corrected equation data
And the first equation data and the second equation data
Data of the second correction equation taking into account the average new car price
A fifth step of acquiring data and the first correction process
Using the equation data and the second correction equation data,
Popularity index data and residual value determined according to data or vehicle type
The third equation data showing the correlation with the rate or the sale amount
Acquiring the third equation data.
The expected sale price, residual value, or
It is characterized in that it is used for predicting information about the expected residual value rate.
The vehicle resale price analysis system of the present invention according to claim 3 is
Manufacturer name, vehicle type name, vehicle application, vehicle shape, vehicle type gray
Model, approval model, model designation number, classification number, mission
, Drive system, displacement, number of doors, common name type, capacity and loading
Quantity, engine model, number of engine cylinders, engine mechanism,
Tire size, turbocharger, roof shape, exhaust gas regulations, body
Vehicle size, vehicle tax classification, weight tax, insurance class, use
Contract year, use contract expiration year, use contract period, new car price,
Sale price after expiration of usage contract, mileage at resale,
Before resale using data on resold vehicles, such as assessments
Information about the sale, residual value, or residual value rate of
A vehicle resale price analysis system to measure
From data on resold vehicles resold to
At least the number of months that have passed since the year of registration or use
Data on the actual usage period, such as the contract period, and the displacement
Data, new car price data,
Before resale using data on mileage during
The expected sale, expected residual value, or expected residual value rate of the vehicle.
Correlation equations or correlations to obtain information
And acquiring the table. Claim 4
The vehicle resale price analysis system of the present invention
Type name, vehicle use, vehicle shape, vehicle grade, certified model,
Model designation number, classification number, mission, drive system,
Displacement, number of doors, popular model, capacity and loading capacity, engine type
Formula, number of engine cylinders, engine mechanism, tire size,
Turbocharger, roof shape, emission control, body size, self
Vehicle tax classification, weight tax, insurance class, use contract year, use contract
About expiration year, use contract period, new car price, after use contract expiration
Of sales, mileage at resale, assessment at resale, etc.
Selling vehicles before resale using data on resold vehicles
Vehicle forecasting information about the amount, residual value, or residual value rate
A sales price analysis system that is resold within a predetermined period
From data on resold vehicles, at least in the first year
Number of months elapsed from registration or use contract year or use contract period, etc.
Data on the actual use period of the gas and data on the displacement
And data on the mileage during the actual use period.
And the expected sale price, residual value, or
A correlation equation or correlation to obtain information about the residual value rate
It is characterized in that a table in which a person is associated is acquired.
The vehicle resale price analysis system of the present invention according to claim 5 is
Manufacturer name, vehicle type name, vehicle application, vehicle shape, vehicle type gray
Model, approval model, model designation number, classification number, mission
, Drive system, displacement, number of doors, common name type, capacity and loading
Quantity, engine model, number of engine cylinders, engine mechanism,
Tire size, turbocharger, roof shape, exhaust gas regulations, body
Vehicle size, vehicle tax classification, weight tax, insurance class, use
Contract year, use contract expiration year, use contract period, new car price,
Sale price after expiration of usage contract, mileage at resale,
Before resale using data on resold vehicles, such as assessments
Information about the sale, residual value, or residual value rate of
A vehicle resale price analysis system to measure
From data on resold vehicles resold to
At least data on displacement and data on new car prices
Data and data on the mileage during the actual use period.
To be used for the expected sale, residual value, or
Correlation formula or correlation to obtain information on the expected residual value
Acquires a table that associates relationships
You. A vehicle resale price analysis system according to claim 6 of the present invention.
Is the manufacturer name, vehicle type name, vehicle application, vehicle shape, vehicle type
Code, approved model, model designation number, classification number, miss
Function, drive system, displacement, number of doors, common name model, capacity and product
Load capacity, engine model, number of engine cylinders, engine machine
Structure, tire size, turbocharger, roof shape, emission control,
Body size, car tax classification, weight tax, insurance class,
Use contract year, use contract expiration year, use contract period, new vehicle price
Rating, sales amount after expiration of use contract, mileage at resale, resale
Using data on resold vehicles, such as
Information about the sale price, residual value, or residual value rate of the vehicle before sale
A vehicle resale price analysis system that predicts
From data on resold vehicles resold during the period,
At least the number of months since the first year registration or use contract year or
Is the data on the actual use period such as the contract period and the new vehicle price
Forecast sale of vehicles before resale using case data
Information about the amount, expected residual value, or expected residual value rate
A table that correlates the correlation equation or correlation
It is characterized by obtaining. The invention according to claim 7 is a contractor.
In the vehicle resale price analysis system according to claim 6,
Using data on mileage during the actual use period
It is characterized by. The present invention described in claim 8 describes the invention described in claim 6.
In the vehicle resale price analysis system described above,
The feature is that the data concerning is used. Claim 9
The present invention according to any one of claims 3 to 8
In the vehicle resale price analysis system, whether it is a mini car or not
Therefore, the data on the resold vehicles classified and classified
Is used. The invention according to claim 10
Is a vehicle resale according to any one of claims 3 to 8
In the price analysis system, whether or not it is a luxury car
Data on the resold vehicles
Data is used. The invention according to claim 11
A vehicle is a vehicle according to any one of claims 3 to 8.
In the sales price analysis system, the resold vehicle is
, Commercial, freight, or vehicle applications such as buses, or
Type, hatchback type, or one box
Classified according to vehicle shape such as type, etc.
It is characterized by using data on sales vehicles. Claim
The present invention described in claim 12 is any of claims 3 to 11.
Acquired by the vehicle resale price analysis system described in
Using a correlation equation or a table that correlates the correlation
And the expected sale price, residual value, or
It is characterized by outputting information about the residual value rate. Claim
Item 13. The residual value profit / loss analysis system according to item 13 of the present invention
Vehicle resale price analysis according to any one of claims 3 to 11.
The correlation expression or correlation acquired by the system
Using the adapted table, information on vehicles during the contract period
Output residual value profit and loss information at any time
I do. The asset evaluation system of the present invention according to claim 14,
The vehicle resale price according to any one of claims 3 to 11.
Correlation formula or correlation obtained by the case analysis system.
Vehicles during the usage contract period using the table that associates the staff
The feature is to output the market value information at any time regarding
And A residual value setting system according to claim 15 of the present invention.
The vehicle according to any one of claims 3 to 11,
Correlation formula or phase obtained by the sales price analysis system
Using a table in which relationships are
Is output. Claim
The storage medium of the present invention described in Item 16 is Claim 3 to Claim 1.
The vehicle resale price analysis system described in
The expected sale price, residual value, or residual value of the vehicle before resale.
Correlation formula or correlation to obtain information on price
Used to acquire a table that associates
Is stored. A book according to claim 17
A storage medium according to any one of claims 3 to 11
The data used for the vehicle resale price analysis system described in
It is characterized by remembering. The invention according to claim 18
Storage media is resold using data on resold vehicles
Information about the sale price, residual value, or residual value rate of the previous vehicle
Record the data used for the forecast vehicle resale price analysis system.
Storage media that has been resold within a predetermined period.
Is at least the first year registration or use contract year for vehicles sold
Actual use period such as the number of months passed or the contract period for use
Data, displacement data, and new car prices
Data and data on the mileage during the actual use period
Is stored. Claim 19
The storage medium of the present invention uses data on resold vehicles.
The sale value, residual value, or residual value rate of the vehicle before resale
Data used in a vehicle resale price analysis system that predicts information
Is a storage medium that stores
At least the first year of registration or use
In the actual use period such as the number of months since the year or the contract period
Data, displacement data, and the actual use
Memorize data on mileage during the period
It is characterized by. The storage medium of the present invention according to claim 20 is:
Sale of vehicles before resale using data on resold vehicles
Vehicle forecasting information about the amount, residual value, or residual value rate
Storage medium storing data used for sales price analysis system
And regarding a resold vehicle resold within a predetermined period,
At least data on displacement and new car prices
Data and data on the mileage during the actual use period
Is stored. Claim 21
The storage medium of the present invention uses data on resold vehicles.
The sale value, residual value, or residual value rate of the vehicle before resale
Data used in a vehicle resale price analysis system that predicts information
Is a storage medium that stores
At least the first year of registration or use
In the actual use period such as the number of months since the year or the contract period
And new car price data.
It is characterized by that. The present invention according to claim 22 is the invention
Item 22. The storage medium according to Item 21, wherein during the actual use period,
Characterized by storing data on mileage
You. The present invention according to claim 23 provides the present invention according to claim 21.
In the storage medium, the data regarding the displacement is stored.
It is characterized by being. The invention according to claim 24 is a contractor.
The storage medium according to any one of claims 18 to 23,
Data that can be classified according to whether the vehicle is a minicar or not.
It is characterized by remembering. The invention according to claim 25.
The storage according to any one of claims 18 to 23.
In the media, store data on automobile tax classification
It is characterized by being. The invention according to claim 26 is a contractor.
The storage medium according to any one of claims 18 to 23,
For passenger, commercial, freight, or vehicles such as buses
Way, or sedan type, hatchback type, or
Data that can be classified according to vehicle shape such as one-box type
Data is stored. Claim 27
The display device of the present invention according to any one of claims 18 to 26.
Display the data stored in the storage medium described in any of them
It is characterized by the following. A vehicle resale according to claim 28.
The price analysis system according to any one of claims 18 to 26,
Resale using the data stored in the storage media described in
The expected sale price, expected residual value, or expected residual value rate of the previous vehicle
And outputting related information. Claim 29
The residual value profit and loss analysis system of the present invention described above
Data stored in the storage medium according to claim 26.
At any time with respect to the vehicle during the contract period
Output the residual value profit and loss information at Claim
30. The asset evaluation system according to claim 30, wherein
A storage medium according to any one of claims 26 to 26.
At any time about the vehicle during the use contract period using the data
It is characterized by outputting market value information at points. Claim 3
According to the remaining value setting system of the present invention described in claim 1,
Data stored in the storage medium according to claim 26.
Data to output residual value forecast information for new contract vehicles
It is characterized by doing. A vehicle according to claim 32 of the present invention.
The resale price analysis system has at least
The period of use or period of use since the first year registration, vehicle type or vehicle
Popularity index determined by species, new car price, sale at resale
Phase derived from the correlation between amount and mileage at resale
Using a relational expression or a table in which the correlation is associated
The sale value, residual value, or residual value rate of the vehicle before resale
A vehicle resale price analysis system that predicts information
Elapsed period or use period from year registration and vehicle type or vehicle type
Index, new car price, mileage,
Enter or select data regarding resale forecast
Provides information about the sale price, expected residual value, or expected residual value rate
It is characterized by force. An article according to the invention as claimed in claim 33.
Product resale price analysis system
Production or sales period or use period, sales price,
Is there a correlation between the sale price at the time of sale and the actual usage data at the time of resale?
Correlation formula derived from the above or the correlation
Use the table to sell or resell the goods before resale, or
An article resale price analysis system that predicts information about the residual value rate
The period of time elapsed from the time of manufacture or sale, or
Enter data on usage period, sales price, and actual use.
Estimated sales amount at resale, expected residual value
Outputs information on the amount or expected residual value rate
And A vehicle resale price analysis system according to claim 34.
Stem is the name of the manufacturer, model name, vehicle application, vehicle shape, vehicle
Grade grade, certified model, model designation number, classification number,
Mission, drive system, displacement, number of doors, common name, constant
Crew and load capacity, engine model, number of engine cylinders, engine
Mechanism, tire size, turbocharger, roof shape, emission regulations
System, body size, automobile tax classification, weight tax, insurance class
Service contract year, use contract expiration year, use contract period, new
Car price, sale price after expiration of use contract, mileage at resale,
Using data on resold vehicles, such as assessments at resale
The sale value, residual value, or residual value rate of the vehicle before resale
A vehicle resale price analysis system that predicts information
Data on the species name, model designation number, or approved model,
Lease or use period, first year registration year, expected driving
Enter data on distance, assessment, or new car price or
By selecting the expected sale amount, the expected residual value at resale, or
It is characterized by outputting information on the expected residual value rate.
The vehicle resale price analysis system according to claim 35 of the present invention.
Means at least a new car price for resold vehicles,
Derived from correlation between sales price or mileage at resale
A correlation expression or a table that associates the correlation
Used to determine the sale value, residual value, or residual value ratio of the vehicle before resale.
Vehicle resale price analysis system that predicts
To enter or select data on new car prices or mileage.
Option allows you to estimate the expected sale price, residual value, or
And outputting information relating to the expected residual value rate. Contract
Claim 36 The article resale price analysis system of the present invention according to claim 36,
Sale price at least for resold goods, sale at resale
Derived from the correlation between the amount or the actual use data at the time of resale
A correlation expression or a table that associates the correlation
Used to determine the sale value, residual value, or residual value rate of the goods before resale.
Product resale price analysis system that predicts
To enter or select data on sales prices or actual use
The expected sale price, expected residual value, or
It is characterized by outputting information about the residual value rate. Claim
Item 37 is a vehicle resale price analysis system according to the present invention.
Car name, vehicle type name, vehicle application, vehicle shape, vehicle type grade,
Approved model, model designation number, classification number, mission,
Drive system, displacement, number of doors, commonly known model, capacity and loading capacity,
Engine model, number of engine cylinders, engine mechanism, Thailand
Size, turbocharger, roof shape, emission control, body
Size, vehicle tax classification, weight tax, insurance class, contract of use
Year, expiration year of use contract, use contract period, new car price, use
Sale price after contract expiration, mileage at resale, assessment at resale
Cars before resale using data on resold vehicles, such as evaluations
Forecast information about the sale amount, residual value, or residual value
Vehicle resale price analysis system
Along with information on the rejected amount, expected residual value, or expected residual value rate
To output information on individual vehicles related to resold vehicles
It is characterized by. The present invention according to claim 38 provides the present invention according to claim 37.
In the vehicle resale price analysis system described in
Information on the individual vehicles for both, sales rate, manufacturer
Name, model name, vehicle shape, displacement, grade, elapsed months,
Year, new car price, mileage, mission, fuel, driving method
It includes a formula or a year of sale. Claim 39
The vehicle resale price analysis system of the present invention described above, the manufacturer name,
Model name, vehicle use, vehicle shape, vehicle grade, certified type
Formula, model designation number, classification number, mission, driving method
Type, displacement, number of doors, popular model, capacity and loading capacity, engine
Model, number of engine cylinders, engine mechanism, tire size
Size, turbocharger, roof shape, exhaust gas regulations, body size
Tax, car tax classification, weight tax, insurance class, year of use contract,
Expiration year of use contract, use contract period, new car price, use contract
Sale price after expiration, mileage at resale, assessment at resale
Using data on resold vehicles such as
Vehicles that predict information about the sale price, residual value, or residual value rate
Both resale price analysis systems, anticipated sale at the time of resale
Along with information on the amount, expected residual value, or expected residual value rate
Average mileage, average sales amount,
Average selling rate, average new car price, or resold vehicles
The standard mileage and standard for resold vehicles within the specified deviation
Output quasi-sale price, standard sale rate, or standard new car price
It is characterized by that. The vehicle of the present invention according to claim 40.
The sales price analysis system uses the model name, model designation number, or certification.
Data on fixed form and lease or use period
Time, first year registration year, estimated mileage, assessment, or new car price
By entering or selecting data on
Information about the expected sale price, expected residual value, or expected residual value rate
Along with the sales rate, manufacturer name, model name, vehicle shape,
Capacity, grade, elapsed months, year, new car price, mileage
Includes release, mission, fuel, drive, or year of sale.
Outputs information on individual vehicles related to resold vehicles
And A vehicle resale price analysis system according to claim 41
Stem will at least cover new vehicle prices for resold vehicles and
From the correlation between the sales amount at the time of resale, the sales amount of the vehicle before resale,
Vehicle resale price that predicts information about the residual value or residual value rate
Case analysis system, wherein the new vehicle price is
And the sale amount or the sale amount is divided by the new vehicle price.
Display a graph with the residual value rate on the other axis, and
The new car price and the sale price for the resold vehicle
Or, while displaying the actual data with the residual value rate,
Shows the correlation between the new car price and the sale price or the residual value rate
It is characterized by showing. 43. The vehicle according to claim 42.
Both resale price analysis systems provide less
Is there a correlation between the sales amount at resale and the mileage at resale?
From the sale price, residual value, or residual value rate of the vehicle before resale
A vehicle resale price analysis system that predicts information
The mileage is one axis and the sale amount or the sale amount
Is plotted on the other axis, with the residual value ratio obtained by dividing
And the running on the resold vehicle is shown on the graph.
Display actual data of line distance and the sale price or the residual value rate
And the mileage and the sale price or the residual value
The correlation with the rate is displayed. Claim 4
The vehicle resale price analysis system of the present invention described in No. 3
At least the resale amount and model or vehicle for the vehicle at the time of resale
Cars before resale from correlation of popularity index determined according to species
Forecast information about the sale amount, residual value, or residual value
A vehicle resale price analysis system,
With the popularity index as one axis, the sale amount or the sale amount
Is plotted on the other axis, with the residual value ratio obtained by dividing
Showing the car related to the resold vehicle on the graph
Seed or the popularity index and the actual value of the sale price or the residual value rate
Display the data and the vehicle type or the popularity index
And the correlation between the sale price or the residual value rate.
And features. The present invention described in claim 44 is based on claim 4.
The vehicle resale price analysis according to any one of claims 1 to 43.
In the system, the correlation is calculated from the first year registration.
It is characterized by displaying multiple items according to elapsed period or usage period.
You. The invention according to claim 45 is the invention according to claims 41 to 41.
43 for the vehicle resale price analysis system
And the correlation is based on actual data on the resold vehicles.
Specified by the equation obtained by regression analysis from the data
It is characterized by. An article resale price according to claim 46 of the present invention.
The analytics system should provide at least
The sale of goods before resale is
Goods that predict information about rejected value, residual value, or residual value rate
A resale price analysis system, wherein the sale price is
The sales price or the sales price divided by the sales price
A graph with the remaining value rate as the other axis, and
The sales price and the sales price for the resale item
In addition to displaying actual data with the rejected amount or the residual value rate,
Correlation between the sale price and the sale price or the residual value rate
Is displayed. The invention according to claim 47.
Commodity resale price analysis system
At least at the time of resale and the actual use data at the time of resale
Sales value, residual value, or residual value rate of goods before resale from the relationship
Product resale price analysis system that predicts information about
Therefore, the actual use data is used as one axis, and the sales amount or
Is the remaining value rate obtained by dividing the sale price by the selling price on the other axis.
Display the graph that was re-sold on the graph
The actual use data and the sale price or the residual value rate
Display the actual data of the
Indicate the sale amount or correlation with the residual value rate
Features. An article resale price of the invention according to claim 48.
Analysis system should be used for resale items at least at the time of resale.
Phase of popularity index determined according to sale price and model or model
Sales value, residual value, or residual value rate of goods before resale from the relationship
Product resale price analysis system that predicts information about
Thus, the model or the popularity index as one axis,
The sale price or the residual value rate obtained by dividing the sale price by the selling price
Is displayed on the graph, and the graph is displayed on the graph.
The model or the popularity index and the sale price of the product for sale
Or, while displaying the actual data with the residual value rate,
Between the model or the popularity index and the sale amount or the residual value rate
The correlation is displayed. Claim 49
The present invention according to any one of claims 46 to 48.
In the article resale price analysis system described above, the correlation
The period of time elapsed from the time of manufacture or sale or the period of use
It is characterized by displaying a plurality of separate items. Claim 50
The present invention provides any one of claims 46 to 48.
In the goods resale price analysis system of the
Is based on regression analysis based on actual data
It is characterized by the equation obtained. Claim
Item 51 is a system for analyzing residual value profit and loss according to the present invention.
Name, model name, vehicle use, vehicle shape, vehicle grade, certification
Model, model designation number, classification number, mission, drive
Method, displacement, number of doors, commonly known model, capacity and loading capacity, engine
Gin type, number of engine cylinders, engine mechanism, tire size
Size, turbocharger, roof shape, emission control, body size
Tax, car tax classification, weight tax, insurance class, year of use contract,
Expiration year of use contract, use contract period, new car price, use contract
Sale price after expiration, mileage at resale, assessment at resale
Using data on resold vehicles such as
A residual value profit / loss analysis system that predicts residual value profit / loss
New vehicle prices for vehicles during the contract period, average mileage per month
Is the assumed mileage or expected use period at the time of separation, use contract expiration
Calculate the expected sale amount at the time of resale from the
Output the residual value profit and loss from the planned sale amount set at the time of contract
It is characterized by the following. The residual value profit and loss of the present invention according to claim 52.
The analysis system includes the manufacturer name, model grade, product model,
Use contract year, use contract expiration year, use contract period, sales price
Rating, sale amount after expiration of usage contract, actual usage status at resale,
Using data on resold goods such as assessments at the time of sale
Residual value profit / loss analysis system for predicting residual value profit / loss of goods before resale
The selling price of goods during the period of use contract,
Monthly usage status, expected usage status at the end of usage contract or assumption
Calculate the expected sale price at the time of resale from the usage period, and
From the rejected amount and the planned sale amount set at the time of the usage contract
Is output. The invention according to claim 53.
Is a residual value profit and loss analysis system according to claim 51 or 52.
In the system, the expected sale amount is
Resale market price at expiration of contract based on market price
Multiplied by the set relative value
And The storage medium of the present invention according to claim 54 is characterized in that:
The residual value loss analysis system according to any one of claims 51 to 53.
Data used for the stem is stored.
You. An asset evaluation system according to the present invention as set forth in claim 55,
Car name, vehicle type name, vehicle application, vehicle shape, vehicle type grade,
Approved model, model designation number, classification number, mission,
Drive system, displacement, number of doors, commonly known model, capacity and loading capacity,
Engine model, number of engine cylinders, engine mechanism, Thailand
Size, turbocharger, roof shape, emission control, body
Size, vehicle tax classification, weight tax, insurance class, contract of use
Year, expiration year of use contract, use contract period, new car price, use
Sale price after contract expiration, mileage at resale, assessment at resale
Use contract period using data on resold vehicles such as evaluations
Assets that predict market value at any time for vehicles in between
An evaluation system for vehicles during the contract period
New car price, monthly average mileage, expected running at the end of the usage contract
Travel distance, assumed mileage at any time, or assumed use period
Calculate the expected sale amount at any time from the
At any time regarding the vehicle during the contract period
It is characterized by outputting the current value. The book of claim 56
The asset evaluation system of the invention is based on the manufacturer name, model grade,
Goods model, use contract year, use contract expiration year, use contract period
Time, sales price, sale price after expiration of use contract, actual use at resale
Data on resold goods, such as usage status and assessment at resale
At any time regarding goods during the contract period
Asset valuation system that predicts the market value of
Sales prices, monthly usage status, usage contracts for articles during the period
At any time from the assumed usage status or expected usage period at the time of expiration
Calculate the expected sales amount at
Output the current value of the goods at any time during the period
It is characterized by the following. The present invention described in claim 57 is based on the claims.
55. The asset evaluation system according to claim 55 or 56.
Of the expected sale value in current or past resale markets
Forecast and set the resale market price at any time based on the market
The calculated value is multiplied by the calculated relative value. Claim
The storage medium according to the present invention as set forth in claim 58, wherein the storage medium of claim 55
Data used for the asset valuation system described in any of
Data is stored. Claim 59.
The residual value setting system of the present invention includes a manufacturer name, a vehicle type name, and a vehicle.
Application, vehicle shape, vehicle grade, certified model, model designation number
No., category number, mission, drive system, displacement,
Number, popular model, capacity and load capacity, engine model, engine
Number of cylinders, engine mechanism, tire size, turbocharger,
Shape, emission control, body size, automobile tax zone
Minutes, weight tax, insurance class, year of use contract, expiration of use contract
Year, use contract period, new car price, sale after expiration of use contract
Resale vehicles already sold, including amount, mileage at resale, and assessment at resale
Using the data on both, the residual value for new contract vehicles
A residual value setting system to set
New vehicle prices for vehicles, average monthly mileage, full use contract
New contract vehicle from the assumed mileage at the end of
Calculate the expected sale amount for
It is characterized by outputting a residual value relating to a contract vehicle.
A residual value setting system according to the present invention is a maker.
Name, model grade, product type, contract year, contract
Expiration year, use contract period, sales price, sale after expiration of use contract
Resale, actual usage at resale, assessment at resale, etc.
Using the data on sales products, the remaining
Is a residual value setting system that sets the
Selling price, monthly usage status, full usage contract
New contracted goods from the assumed use situation or assumed use period at the end of
Calculate the expected sale amount for
It is characterized by outputting the residual value of the contract article.
The present invention according to claim 61 is the invention according to claim 59 or claim 60.
In the residual value setting system described in the above, the expected sale amount
Contract expires based on current or past resale market prices
Multiply by the relative value set by forecasting the resale market price at the time
Is calculated. The invention according to claim 62.
The residual value setting system of the manufacturer, the name of the model,
Vehicle shape, vehicle grade, certified model, model designation number, class
Classification number, mission, drive system, displacement, number of doors,
Commonly known model, capacity and load capacity, engine model, engine
Number of cylinders, engine mechanism, tire size, turbocharger, roof type
Status, emission regulations, body size, vehicle tax classification, weight
Tax, insurance class, use contract year, use contract expiration year, use
Contract period, new car price, sale amount after expiration of use contract, resale
Of resold vehicles such as mileage of vehicles, assessment at resale, etc.
Residual value setting that sets residual values for new models using data
The new system is intended for use with new models
Compare prices with existing vehicle models and new vehicle prices
And select the closest existing vehicle type or popularity index
Calculates the residual value of a new model based on the model or popularity index
It is characterized by force. A description of the invention according to claim 63.
63. The storage medium according to any one of claims 59 to 62.
Stores data used for the residual value setting system
It is characterized by. A vehicle resale price according to claim 64 of the present invention.
The analysis system is based on the manufacturer name, years of fall, vehicle type, vehicle type
Condition, displacement, fuel, grade, mission, and driving method
Vehicle specifications such as formulas, and sales price for each resold vehicle
Using the relevant data, the sales amount, residual value,
Or a vehicle resale price analysis system that predicts information about the residual value rate.
Stem, selected by the vehicle specifications
Standard within a predetermined range from the average of the sale price of resold vehicles
Select the resold vehicle that is in deviation again and select it again.
The average value of the sales amount of resold vehicles
It is characterized in that the standard sale price is the expected sale price.

[0006]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A vehicle resale price analysis system according to a first embodiment of the present invention includes a first step of extracting data relating to a resold vehicle that has been resold within a predetermined period, and the first step. A second step of extracting the factors affecting the vehicle resale price by correlation analysis using the data extracted in the above, and obtaining a multiple regression equation from the correlation between the extracted factors and data on the sold amount. And a third step. Then, the multiple regression equation obtained in the third step is calculated based on the estimated sale price of the vehicle before resale,
It is used for forecasting information on expected residual value or expected residual value rate. As described above, in the present embodiment, from the sales data on vehicles that have already been resold, a factor having a large effect on the sales amount is extracted by the correlation analysis, and the extracted factors are extracted from the correlation with the data on the sales amount. By obtaining the multiple regression equation, it is possible to obtain information on an objective expected sale price and the like for a vehicle to be resold.

A vehicle resale price analysis system according to a second embodiment of the present invention divides a new vehicle price and a sale amount or a sale amount obtained from data on resold vehicles resold within a predetermined period by a new vehicle price. Based on the first equation data indicating the correlation with the residual value rate and the second equation data indicating the correlation between the mileage and the sale price or the residual value rate obtained by dividing the sale price by the new car price, First correction equation data taking into account the average mileage and second correction equation data taking into account the average new vehicle price are obtained. From the first correction equation data and the second correction equation data, vehicle type data or vehicle type is obtained. Third equation data indicating a correlation between the popularity index data determined accordingly and the residual value rate or the sale price is acquired. Then, an expected sale price of the vehicle before resale is obtained from the third equation data. The expected sale price of the vehicle can be obtained by inputting data relating to the vehicle type, the popularity index determined according to the vehicle type, the new vehicle price, and the mileage.
As described above, according to the present embodiment, among sales data relating to vehicles that have already been resold, a popularity is determined according to a vehicle type or a vehicle type that is data that has already been empirically recognized as having a large effect on the sales amount. By analyzing the data related to the index, the new car price, and the mileage and setting the correlation as equation data, it is possible to obtain an objective expected sale price for the vehicle to be resold.

[0008] The vehicle resale price analysis system according to the third embodiment of the present invention comprises, based on data on resold vehicles resold within a predetermined period, at least the number of months since the first year registration or use contract year or Using the data on the actual usage period such as the usage contract period, the data on the displacement, the data on the new vehicle price, and the data on the mileage during the actual usage period, the expected sale amount and the expected residual value of the vehicle before resale Or a correlation table for obtaining information on the expected residual value rate or a table in which the correlation is associated. As described above, this embodiment is based on the actual use period, the displacement, and the new vehicle price, which are data that have already been empirically recognized as having a large effect on the sale price from the sale data on the resold vehicles. And a correlation expression or a correlation for obtaining information on an expected sale price, an expected residual value, or an expected residual value rate of the vehicle before resale using the data on the mileage during the actual use period. By obtaining the table, it is possible to obtain an objective expected sale price for the vehicle to be resold.

A vehicle resale price analysis system according to a fourth embodiment of the present invention includes at least the number of months that have passed since the year of registration or use contract for the first year, from among data on resold vehicles resold within a predetermined period. Using the data on the actual use period such as the use contract period, the data on the displacement, and the data on the mileage during the actual use period, the expected sale price, expected residual value, or expected residual value rate of the vehicle before resale This is to acquire a correlation expression or a table in which the correlation is correlated to obtain information on the correlation. As described above, the present embodiment is based on the actual use period, the displacement, and the data that have already been empirically recognized as having a large effect on the sales price from the sales data on the vehicles that have already been resold. Using the data on the mileage during the actual use period, obtain a correlation formula or a table that correlates the correlation to obtain information on the expected sale price, expected residual value, or expected residual value rate of the vehicle before resale By doing so, it is possible to obtain an objective expected sale price for the vehicle to be resold.

A vehicle resale price analysis system according to a fifth embodiment of the present invention comprises at least data on displacement and data on a new vehicle price among data on resold vehicles resold within a predetermined period. Using the data on the mileage during the actual use period, obtain a correlation formula or a table that correlates the correlation to obtain information on the expected sale price, expected residual value, or expected residual value rate of the vehicle before resale Is what you do. As described above, in the present embodiment, from the sales data on vehicles already resold,
Estimated sales amount of the vehicle before resale using data on displacement, new vehicle price, and data on mileage during the actual use period, which are data that has already been empirically recognized as having a large effect on the sales amount, By obtaining a correlation formula or a table in which a correlation is obtained for obtaining information on the expected residual value or the expected residual value rate, an objective expected sale price can be obtained for the vehicle to be resold.

A vehicle resale price analysis system according to a sixth embodiment of the present invention uses at least the number of months elapsed since the year of registration or use contract for the first year from among data on resold vehicles resold within a predetermined period. A correlation formula or correlation for obtaining information on the expected sale price, expected residual value, or expected residual value rate of the vehicle before resale using data on the actual usage period such as the contract period and data on the new vehicle price. This is to acquire the associated table. As described above, the present embodiment includes data on the actual use period and data on the new vehicle price, which are data that has already been empirically recognized as having a large effect on the sales amount from the sales data on the vehicles that have already been resold. By obtaining a correlation equation or a table that correlates correlations to obtain information on the expected sale value, expected residual value, or expected residual value rate of vehicles before resale using Expected sale price can be obtained.

A seventh embodiment of the present invention is directed to a vehicle resale price analysis system according to the sixth embodiment, wherein the estimated sales amount of the vehicle before resale is calculated using data on the mileage during the actual use period. This is to acquire a correlation expression or a table in which a correlation is obtained for obtaining information on the expected residual value or the expected residual value rate. As described above, in the present embodiment, the data on the mileage, which is data that has already been empirically recognized as having a large effect on the sale price, from the sales data on the vehicles that have already been resold, is used for the actual use period and To be resold by using the data on the new car price and acquiring a correlation equation or a table that correlates the correlation to obtain information on the expected sale price, expected residual value, or expected residual value rate of the vehicle before resale Objective sale price can be obtained for this vehicle.

An eighth embodiment of the present invention is directed to a vehicle resale price analysis system according to the sixth embodiment, wherein an estimated sale price of a vehicle before resale is calculated using data on displacement.
This is to acquire a correlation expression or a table in which the correlation is obtained to obtain information on the expected residual value or the expected residual value rate. As described above, in the present embodiment, among the sales data on the vehicles that have already been resold, the data on the displacement, which is data that has already been empirically recognized to have a large effect on the sales amount, is used for the actual use period and To be resold by using the data related to the new car price and obtaining a correlation formula or a table that correlates the correlation to obtain information on the expected sale value, expected residual value, or expected residual value rate of the vehicle before resale Objective sale price can be obtained for this vehicle.

According to a ninth embodiment of the present invention, in the vehicle resale price analysis system according to the third to eighth embodiments, whether or not the vehicle is a mini vehicle is classified and an estimated sale amount of the vehicle before resale is obtained. This is to acquire a correlation expression or a table in which a correlation is obtained for obtaining information on the expected residual value or the expected residual value rate. As described above, according to the present embodiment, the light vehicle is classified from the other vehicles, so that the expected sales amount, the expected residual value, or the expected By obtaining a correlation expression or a table in which the correlation is obtained to obtain information on the residual value rate, an objective expected sale price can be obtained for the vehicle to be resold.

A tenth embodiment of the present invention is directed to a vehicle resale price analysis system according to the third to eighth embodiments, wherein whether or not a vehicle is a luxury vehicle is classified according to a vehicle tax classification to determine whether a vehicle is a luxury vehicle or not. This is to acquire a correlation expression or a table in which a correlation is obtained to obtain information on the expected sale price, the expected residual value, or the expected residual value rate. As described above, the present embodiment classifies so-called high-end vehicles from other vehicles by tax classification, and considers the expected sales amount and the remaining By acquiring a correlation formula or a table in which a correlation is obtained for obtaining information on the price or the expected residual value rate, it is possible to obtain an objective expected sale price for the vehicle to be resold.

An eleventh embodiment of the present invention is directed to the vehicle resale price analysis system according to the third to eighth embodiments, wherein the estimated sales amount of the vehicle before resale is classified by vehicle use or vehicle shape, This is to acquire a correlation expression or a table in which the correlation is obtained to obtain information on the expected residual value or the expected residual value rate. As described above, in the present embodiment, information on the expected sale price, the expected residual value, or the expected residual value rate of the vehicle before resale in consideration of the purpose, popularity, etc. By obtaining a correlation expression or a table in which correlations are obtained, an objective expected sale price can be obtained for a vehicle to be resold.

A twelfth embodiment of the present invention uses a correlation equation or a table in which a correlation is obtained by the vehicle resale price analysis system according to the third to eleventh embodiments, before resale. The information relating to the expected sale price, the expected residual value, or the expected residual value rate of the vehicle is output. According to the present embodiment, an objective expected sale price can be obtained for a vehicle to be resold.

The residual value profit / loss analysis system according to the thirteenth embodiment of the present invention provides a table in which correlation expressions or correlations obtained by the vehicle resale price analysis systems according to the third to eleventh embodiments are associated. Is used to output residual value profit and loss information at any time regarding a vehicle during the use contract period. According to the present embodiment, it is possible to obtain objective residual value profit / loss information on vehicles during the usage contract period.

The asset evaluation system according to the fourteenth embodiment of the present invention uses a correlation equation obtained by the vehicle resale price analysis system according to the third to eleventh embodiments or a table in which the correlation is associated. To output market value information at any time regarding the vehicle during the usage contract period. According to the present embodiment, objective market price information can be obtained for a vehicle during a use contract period.

A residual value setting system according to a fifteenth embodiment of the present invention is a system for setting a correlation table obtained by the vehicle resale price analysis system according to the third to eleventh embodiments. To output residual value forecast information relating to a newly contracted vehicle. According to the present embodiment, it is possible to obtain objective residual value prediction information for a new contract vehicle.

The storage medium according to the sixteenth embodiment of the present invention is characterized in that the vehicle resale price analysis system according to the third to eleventh embodiments stores the expected sale price, the expected residual value, or the expected residual value of the vehicle before resale. It stores data used to obtain a correlation equation for obtaining information on the price or a table in which the correlation is associated. According to the present embodiment, it is possible to acquire a correlation expression or a table in which a correlation is obtained for obtaining an objective sale amount or the like for a new contract vehicle.

The storage medium according to the seventeenth embodiment of the present invention stores data used for the vehicle resale price analysis system according to the third to eleventh embodiments. According to the present embodiment, it is possible to obtain an objective sale price or the like for a new contract vehicle.

The storage medium according to the eighteenth embodiment of the present invention includes at least data relating to the actual use period such as the number of months elapsed from the year of registration or contract of use for the first year or the contract period of use, data relating to the displacement, The data on the price and the data on the mileage during the actual use period are stored. According to the present embodiment, it is possible to obtain a correlation equation or a table in which a correlation is obtained for obtaining an objective sale amount or the like for a new contract vehicle, and to obtain a table of the estimated sale amount or the like. Information about the resale vehicle can be output.

A storage medium according to a nineteenth embodiment of the present invention comprises: data relating to an actual use period such as at least the number of months elapsed since the first year registration or use contract year or use contract period; And data on the mileage during the actual use period. According to the present embodiment, it is possible to obtain a correlation equation or a table in which a correlation is obtained for obtaining an objective sale amount or the like for a new contract vehicle, and to obtain a table of the estimated sale amount or the like. Information about the resale vehicle can be output.

The storage medium according to the twentieth embodiment of the present invention stores at least data relating to the displacement, data relating to the price of a new vehicle, and data relating to the mileage during the actual use period. According to the present embodiment, it is possible to obtain a correlation equation or a table in which a correlation is obtained for obtaining an objective sale amount or the like for a new contract vehicle, and to obtain a table of the estimated sale amount or the like. Information about the resale vehicle can be output.

The storage medium according to the twenty-first embodiment of the present invention stores at least data relating to the actual use period such as the number of months elapsed from the first year registration or use contract year or the use contract period and data relating to the new vehicle price. ing. According to the present embodiment, it is possible to obtain a correlation equation or a table in which a correlation is obtained for obtaining an objective sale amount or the like for a new contract vehicle, and to obtain a table of the estimated sale amount or the like. Information about the resale vehicle can be output.

According to a twenty-second embodiment of the present invention, the storage medium according to the twenty-first embodiment stores data relating to a traveling distance during an actual use period. According to the present embodiment, it is possible to obtain a correlation formula or a table in which a correlation is obtained for obtaining an objective sale amount or the like with respect to a resold vehicle. Information about the resale vehicle can be output.

According to the twenty-third embodiment of the present invention, the storage medium according to the twenty-first embodiment stores data relating to the displacement. According to the present embodiment, it is possible to obtain a correlation formula or a table in which a correlation is obtained for obtaining an objective sale amount or the like with respect to a resold vehicle. Information about the resale vehicle can be output.

In the twenty-fourth embodiment of the present invention, the storage medium according to the eighteenth to twenty-third embodiments stores data that can be classified according to whether or not the vehicle is a mini vehicle.
According to the present embodiment, it is possible to obtain a correlation expression or a table in which a correlation is obtained in order to obtain an objective sale price or the like in consideration of the influence at a low price range specific to a mini vehicle with respect to a resold vehicle. And information on the resold vehicles that are the basis of the estimated sale price and the like can be output.

According to the twenty-fifth embodiment of the present invention, the storage medium according to the eighteenth to twenty-third embodiments stores data relating to automobile tax classification. According to the present embodiment, it is necessary to obtain a correlation expression or a table in which a correlation is obtained in order to obtain an objective sale price or the like in consideration of the influence at a high price range specific to a luxury vehicle for a resold vehicle. And information on the resold vehicles that became the basis of the estimated sale price and the like can be output.

The twenty-sixth embodiment of the present invention is directed to a storage medium according to the eighteenth to twenty-third embodiments, wherein the storage medium is used for a vehicle such as a passenger, commercial, freight, or bus, or a sedan type, a hatchback type, or a one-way type. Data that can be classified according to the vehicle shape such as a box type is stored. According to the present embodiment, it is possible to obtain a table that associates a correlation equation or a correlation for obtaining an objective sale price or the like in consideration of the influence of the purpose, popularity, or the like with respect to the resold vehicles, It is possible to output information on the resold vehicles that are the basis of the estimated sale price and the like.

The display device according to the twenty-seventh embodiment of the present invention displays the data stored in the storage medium according to the eighteenth to twenty-sixth embodiments, so that the estimated sales amount and the like can be obtained. Information about the resale vehicle can be output.

The vehicle resale price analysis system according to the twenty-eighth embodiment of the present invention uses the data stored in the storage medium according to the eighteenth to twenty-sixth embodiments to estimate the expected sale price and the expected sale of the vehicle before resale. By outputting information on the residual value or the expected residual value rate, an objective sale amount or the like can be output.

The residual value profit / loss analysis system according to the twenty-ninth embodiment of the present invention uses the data stored in the storage medium according to the eighteenth to twenty-sixth embodiments at any time regarding a vehicle during a use contract period. By outputting the residual value profit and loss information in the above, objective residual value profit and loss information can be output.

The asset evaluation system according to the thirtieth embodiment of the present invention uses the data stored in the storage medium according to the eighteenth to twenty-sixth embodiments at any time regarding a vehicle during a use contract period. By outputting the market price information, objective market price information can be output.

A residual value setting system according to a thirty-first embodiment of the present invention outputs residual value expected information relating to a new contract vehicle using data stored in a storage medium according to the eighteenth to twenty-sixth embodiments. Thus, objective residual value prediction information can be output.

The vehicle resale price analysis system according to the thirty-second embodiment of the present invention comprises a period of use or a period of use from the registration in the first year, a vehicle type or a popularity index determined according to the vehicle type, a new vehicle price, and a mileage. By inputting or selecting data regarding the above, information on the expected sale price, expected residual value, or expected residual value rate at the time of resale is output.

The article resale price analysis system according to the thirty-third embodiment of the present invention provides a resale price by inputting or selecting data relating to an elapsed period or use period from a manufacturing or sale time, a selling price, and actual use. Expected sale price at the time,
It outputs information on the expected residual value or the expected residual value rate.

The vehicle resale price analysis system according to the thirty-fourth embodiment of the present invention comprises data on a vehicle type name, a model designation number, or an approved model, a lease period or a use period, a first year registration year, an estimated mileage, an assessment. Or data on a new car price is input or selected to output information on the expected sale price, expected residual value, or expected residual value rate at the time of resale.

The vehicle resale price analysis system according to the thirty-fifth embodiment of the present invention provides an expected sales amount at the time of resale by inputting or selecting data relating to a new vehicle price or mileage,
It outputs information on the expected residual value or the expected residual value rate.

An article resale price analysis system according to a thirty-sixth embodiment of the present invention provides an expected sale price, expected residual value, or expected residual value rate at the time of resale by inputting or selecting data on a selling price or actual use. It outputs information about

A vehicle resale price analysis system according to a thirty-seventh embodiment of the present invention outputs information on an individual vehicle related to a resold vehicle, together with information on an expected sale price, an expected residual value, or an expected residual value rate at the time of resale. Is what you do.

According to a thirty-eighth embodiment of the present invention, in the vehicle resale price analysis system according to the thirty-seventh embodiment, the sales rate, manufacturer name, model name, vehicle shape, Displacement, grade,
Includes elapsed months, year, new vehicle price, mileage, mission, fuel, drive, or year of sale.

A vehicle resale price analysis system according to a thirty-ninth embodiment of the present invention provides an average mileage and an average sale for a resold vehicle, together with information on an expected sale amount, an expected residual value, or an expected residual value rate at the time of resale. It outputs the amount, the average sales rate, the average new vehicle price, or the standard mileage, the standard sales amount, the standard sales rate, or the standard new vehicle price for the resold vehicles within a predetermined deviation value among the resold vehicles.

A vehicle resale price analysis system according to a fortieth embodiment of the present invention comprises data on a vehicle type name, a model designation number, or an approved model, a lease period or a use period, a first year registration year, an expected mileage, and an assessment. , Or by entering or selecting data on the new car price, along with information on the expected sale price, expected residual value, or expected residual value rate at the time of resale, the sale rate, manufacturer name, model name, vehicle shape, displacement, It outputs information on individual vehicles related to resold vehicles including grade, elapsed months, year, new vehicle amount, mileage, mission, fuel, drive system, or year of sale.

The vehicle resale price analysis system according to the forty-first embodiment of the present invention uses a graph in which the new vehicle price is set as one axis, and the sale price or the residual value rate obtained by dividing the sale price by the new vehicle price is set as the other axis. This is to display, on a graph, actual data of a new vehicle price and a sale amount or a residual value rate relating to a resold vehicle, and to display a correlation between the new vehicle price and the sale amount or the residual value ratio. As described above, in the present embodiment, the correlation between the new vehicle price and the sales amount or the residual value rate, which has already been empirically recognized from the sales data on the vehicles that have already been resold, to have a large effect on the sales amount, is The relationship can be visually grasped, and an objective expected sale price can be recognized for the vehicle to be resold.

The vehicle resale price analysis system according to the forty-second embodiment of the present invention uses a graph in which the mileage is set as one axis, and the sale price or the residual value rate obtained by dividing the sale price by the new vehicle price is set as the other axis. This is to display, on a graph, actual data of the mileage and the sale amount or the residual value rate of the resold vehicle, and to display the correlation between the mileage and the sale amount or the residual value rate. As described above, in the present embodiment, the correlation between the mileage and the sales amount or the residual value rate, which has already been empirically recognized from the sales data on the resold vehicles, as having a large effect on the sales amount, has been recognized. The relationship can be visually grasped, and an objective expected sale price can be recognized for the vehicle to be resold.

The vehicle resale price analysis system according to the forty-third embodiment of the present invention uses the vehicle type or popularity index as one axis, and the sale price or the residual value rate obtained by dividing the sale price by the new vehicle price as the other axis. Display a graph, and on the graph, display the actual data of the vehicle type or popularity index and the sale price or residual value rate for the resold vehicles, and also display the correlation between the vehicle type or popularity index and the sales price or residual value rate Is what you do. As described above, in the present embodiment, from the sales data on vehicles that have already been resold, a vehicle type or a popularity index that has already empirically recognized that the influence on the sales amount is large, the sales amount or the residual value rate, Can be visually grasped, and an objective expected sale price can be recognized for the vehicle to be resold.

According to a forty-fourth embodiment of the present invention, in the vehicle resale price analysis system according to the forty-first to forty-third embodiments, a plurality of correlations are displayed for each elapsed period or first use period from the first year registration. It is. As described above, in the present embodiment, the correlation between the new vehicle price and the sales amount or the residual value rate, which has already been empirically recognized from the sales data on the vehicles that have already been resold, to have a large effect on the sales amount, is The relationship can be visually grasped, and the difference depending on the elapsed period from the first year registration or the use period can be recognized together.

According to a forty-fifth embodiment of the present invention, in the vehicle resale price analysis system according to the forty-first to forty-third embodiments, the correlation is defined by an equation obtained by regression analysis from actual data on resold vehicles. It was done.

The article resale price analysis system according to the forty-sixth embodiment of the present invention provides a graph in which the sales price is set as one axis, and the sale price or the residual value rate obtained by dividing the sale price by the sales price is set as the other axis. It displays the actual data of the selling price and the sale price or the residual value rate of the resale articles on the graph, and also displays the correlation between the sales price and the sale price or the residual value rate. As described above, this embodiment is based on the correlation between the selling price and the selling price or the residual value rate, which has already been empirically recognized as having a large effect on the selling price, from the selling data on the articles already resold. The relationship can be visually grasped, and an objective expected sale price can be recognized for the article to be resold.

The goods resale price analysis system according to the forty-seventh embodiment of the present invention uses a graph in which the mileage is set as one axis, and the sale price or the residual value rate obtained by dividing the sale price by the sale price is used as the other axis. In addition to displaying the actual use data and the actual value of the sale amount or the residual value rate on the resold articles on the graph, the correlation between the actual use data and the sale amount or the residual value ratio is displayed. As described above, the present embodiment is based on a comparison between actual use data, which has already been empirically recognized as having a large effect on the sale price, and sale price or the residual value rate, from the sale data on articles already resold. The correlation can be visually grasped, and an objective expected sale price can be recognized for the article to be resold.

In the article resale price analysis system according to the forty-eighth embodiment of the present invention, the model or popularity index is used as one axis, and the sale price or the residual value rate obtained by dividing the sale price by the sales price is used as the other axis. Display a graph, display the actual data of the model or popularity index and the sale price or residual value rate on the resale items on the graph, and display the correlation between the model or popularity index and the sale price or residual value ratio Things. As described above, the present embodiment is based on the sales data or the residual index and the model or the popularity index, which has already empirically recognized that the influence on the sales price is large, from the sales data on the products already resold. Can be visually grasped, and an objective expected sale price can be recognized for the article to be resold.

According to a forty-ninth embodiment of the present invention, in the article resale price analysis system according to the forty-sixth to forty-eighth embodiments, a plurality of correlations are displayed for each of an elapsed period from a manufacturing or sales period or a use period. It is. As described above, this embodiment is based on the correlation between the selling price and the selling price or the residual value rate, which has already been empirically recognized as having a large effect on the selling price, from the selling data on the articles already resold. You can visually understand the relationship,
It is also possible to recognize differences depending on the elapsed period from the manufacturing or sale time or the use period.

According to a fiftieth embodiment of the present invention, in the article resale price analysis system according to the forty-sixth to forty-eighth embodiments, the correlation is defined by an equation obtained by regression analysis from actual data on the resold articles. It was done.

The system for analyzing residual value loss according to the fifty-first embodiment of the present invention relates to a system for analyzing a new vehicle price, a monthly average mileage, an assumed mileage at the expiration of a use contract, or an estimated mileage at the end of a use contract. Calculate the expected sale price of
The residual value profit and loss is output from the expected sale amount and the planned sale amount set at the time of the use contract. As described above, in the present embodiment, the expected sale price at the time of resale is calculated using the sale data on the products already resold, and the residual value at the time of resale at the time of resale is calculated from the expected sale price and the planned sale price set at the time of the use contract. Profit and loss can be predicted. In this way, the residual value profit and loss at the time of contract expiration can be predicted from objective data, so that, for example, the risk that the evaluation of vehicles will decrease from the time of contract to the present and cumulative loss will occur can be predicted in advance. it can. Therefore, by grasping in advance the profit and loss that can occur when the contract expires, an appropriate residual value can be set in a new contract.

The residual value profit / loss analysis system according to the fifty-second embodiment of the present invention provides a sales price, a monthly usage status, an assumed usage status at the expiration of a usage contract or an estimated usage status at the time of resale from an assumed usage period. The expected sale amount is calculated, and a residual value profit or loss is output from the expected sale amount and the planned sale amount set at the time of the use contract. As described above, in the present embodiment, the expected sale price at the time of resale is calculated using the sale data on the products already resold, and the residual value at the time of resale at the time of resale is calculated from the expected sale price and the planned sale price set at the time of the use contract. Profit and loss can be predicted. In this way, the residual value profit and loss at the time of contract expiration can be predicted from objective data. it can. Therefore, by grasping in advance the profit and loss that can occur when the contract expires, an appropriate residual value can be set in a new contract.

According to a fifty-third embodiment of the present invention, in the residual value profit / loss analysis system according to the fifty-first to fifty-third embodiments, the expected sales amount is calculated based on the current market price in the resale market at the time of contract expiration. Is calculated by multiplying the relative value set by predicting the resale market price of the market. According to the present embodiment, it is possible to more accurately predict the residual value profit and loss at the time of contract expiration.

The storage medium according to the fifty-fourth embodiment of the present invention stores data used in the residual value profit / loss analysis system according to the fifty-first to fifty-third embodiments.

The asset evaluation system according to the fifty-fifth embodiment of the present invention provides a new vehicle price, a monthly average mileage, an assumed mileage at the expiration of a use contract, and an assumed mileage at any time during a use contract period. Alternatively, an expected sale price at an arbitrary point in time from an assumed use period is calculated, and a market price at an arbitrary point regarding a vehicle during a use contract period is output from the expected sale amount. As described above, in the present embodiment, it is possible to calculate the expected sale price at the time of resale using the sale data relating to the articles already resold, and to predict the market value at any time from the expected sale price.

The asset evaluation system according to the fifty-sixth embodiment of the present invention provides a sales price, a monthly usage status, an assumed usage status at the expiration of a usage contract, or an arbitrary usage time from an assumed usage period for an article during a usage contract period. Calculate the expected sale amount,
The market value at an arbitrary point in time of the article during the use contract period is output from the expected sale price. As described above, in the present embodiment, it is possible to calculate the expected sale price at the time of resale using the sale data relating to the articles already resold, and to predict the market value at any time from the expected sale price.

According to a fifty-seventh embodiment of the present invention, in the asset valuation system according to the fifty-fifth to fifty-sixth embodiments, the expected sale price is calculated based on the current market price in the resale market at the time of resale of the contract. This is calculated by multiplying a relative value set by predicting the market price. According to the present embodiment,
The market value at any time can be more accurately predicted.

The storage medium according to the fifty-eighth embodiment of the present invention stores data used for the asset evaluation system according to the fifty-fifth to fifty-seventh embodiments.

The remaining value setting system according to the fifty-ninth embodiment of the present invention provides a new contract vehicle based on a new vehicle price, a monthly average mileage, an assumed mileage at the expiration of the use contract or an assumed use period for the vehicle during the use contract period. Is calculated, and the residual value relating to the new contract vehicle is output from the expected sales amount. As described above, in the present embodiment, it is possible to calculate the expected sale amount for the new contract vehicle using the sale data for the already resold articles, and to set the residual value for the new contract vehicle from the expected sale amount.

The residual value setting system according to the 60th embodiment of the present invention relates to a new contract article based on the selling price, the monthly use situation, the assumed use situation at the expiration of the use contract or the assumed use term of the article during the use contract period. The expected sale price is calculated, and the residual value of the new contract article is output from the expected sale price. As described above, in the present embodiment, it is possible to calculate the expected sale amount of the new contract article by using the sale data of the already resold article, and to set the residual value of the new contract article from the expected sale amount.

The sixty-first embodiment of the present invention relates to the residual value setting system according to the fifty-sixth to sixty-sixth embodiments, wherein the expected sale amount is calculated based on the current or past market price in the resale market at the time of contract expiration. Is calculated by multiplying by a relative value set by predicting the resale market market price. According to the present embodiment, it is possible to more accurately predict the residual value of a new contract article.

The residual value setting system according to the 62nd embodiment of the present invention compares a vehicle type application and a new vehicle price of a new vehicle type with a vehicle type application and a new vehicle price of an existing vehicle to determine the closest available vehicle type or popularity index. It outputs the remaining value of the selected model and the new model based on the selected existing model or popularity index. As described above, the present embodiment selects the closest available vehicle type or popularity index from the new vehicle type application and new vehicle price and the vehicle type application and new vehicle price related to the existing vehicle. Based on this, the residual value for the new model can be set.

The storage medium according to the 63rd embodiment of the present invention stores data used in the remaining value setting system according to the 59th to 62nd embodiments.

The vehicle resale price analysis system according to the sixty-fourth embodiment of the present invention reassembles resold vehicles having a standard deviation within a predetermined range from the average value of the sales amount of the resold vehicles selected according to the vehicle specifications. The average value of the sales amounts of the selected and reselected resold vehicles is set as the standard sales amount, and the standard sales amount is set as the expected sales amount. According to the present embodiment, vehicles resold for a special reason can be excluded by re-selecting resold vehicles that have a standard deviation within a predetermined range from the average value of the sales amount. Therefore, it is possible to more accurately obtain the expected sales amount for an average vehicle having no special reason.

[0070]

An embodiment of the present invention will be described below with reference to the drawings. First, in the present invention, a use contract is a contract for granting use or ownership for a predetermined period, such as a lease contract, a rental contract, or a residual value loan contract. It is intended to terminate the contract due to early termination. Hereinafter, in the description of the embodiment of the present invention, a vehicle resale price analysis system based on vehicle data resold at a bid or an auction after a rental contract expires will be described as an example.

FIG. 1 is a block diagram showing the overall configuration including the vehicle resale price analysis system according to the embodiment. The resale support system 10 includes a support-side vehicle resale system 11 and a bid support system 12. The support-side vehicle resale system 11 includes a vehicle type database 13, a resold vehicle database 14, and an expected sale amount calculation system 15. Here, the vehicle type database 13 includes a maker name, a vehicle type name, a vehicle use, a vehicle shape, a vehicle type grade (vehicle type name, grade name), a certification type, a common name type (type designation number, a classification number), a mission, a driving method, Displacement,
Number of doors, capacity, loading capacity, engine model (motor model),
Number of engine cylinders, engine mechanism, tire size, turbocharger, roof shape, emission control, body size, body color, automobile tax classification, weight tax, insurance class, popularity index, vehicle application, vehicle shape, initial release, release It has data such as the end date. Here, the popularity index is an index that is ranked according to the residual value rate in the classification by vehicle type.
For example, if Corolla and Civic have the same residual value ratio and Sunny's residual value ratio is two ranks lower than Corolla, Corolla's popularity index is set to 25, Civic's popularity index is set to 25, and Sunny's popularity index is set to 22. Is done. The vehicle use is a classification of the vehicle according to the use, and is classified into a passenger car, a van, a bus, a truck, and the like. The vehicle shape is a classification based on the number of doors and the outer shape. For example, a sedan (SD) for four doors and a trunk, a hatchback (HB) for two doors and a tailgate (no 4-door specification), two doors + Coupe or sports (CP) for trunk, bonnet wagon (BW) for 2 to 4 doors + tailgate or 4-door base full bonnet, cab wagon for 3 to 4 doors + tailgate or semi-cab over (CW). Further, the resold vehicle database 14 includes information on the resold vehicles such as a use contract year, a use contract expiration year, a use contract period, a new car price, a sale amount after the use contract expires, a mileage at the time of resale, an evaluation evaluation at the time of resale, and the like. Has data. In addition, the expected sale price calculation system 15 uses the vehicle type database 13
And a table that associates a multiple regression equation, a correlation equation, or a correlation from the data of the resold vehicle database 14 and calculates information about the expected sale price, the expected residual value, or the expected residual value rate before resale. System. Further, the bidding system 12 is a system for selecting and exhibiting a domestic bidding event, an overseas bidding event, a bidding event on the web using the Internet, an auction, a retail at a store, or the like. For example, the bidding system 12 transmits exhibition data on exhibited vehicles to the bidding hall system 16 of the bidding hall.

The user-side system 20 used by a leasing company or the like has a user-side vehicle resale price analysis system 21. This user-side vehicle resale price analysis system 21
The system includes a residual value setting system 22 for setting a residual value for a new contract vehicle, and a residual value simulation system 23 for performing a residual value simulation. Here, as the residual value simulation system 23, for example, a residual value profit / loss analysis system 24 for predicting residual value gain / loss of a vehicle before resale, or an asset evaluation system 25 for predicting a market value of a vehicle during a use contract period at any time. There is. The user-side system 20 includes an estimation system 26 and a core system 27 used at the time of a lease contract, in addition to the user-side vehicle resale price analysis system 21. Here, the core system 27 includes a lease contract database 28 for storing lease contract data.
It has. The use side system 20 has an exhibition support system 29. This exhibition support system 29
Is a system that sends contract expiration data to the bidding system 12 for vehicles whose contract has expired, or preferably for vehicles whose contract will expire after a predetermined period of time.

Next, the flow of exhibition data to a bidding party or the like will be described. Contract expiration data relating to a vehicle whose contract has expired, or preferably a vehicle whose contract is to expire after a predetermined period of time, is transmitted from the core system 27 to the exhibition support system 2.
9 The exhibition support system 29 transmits the contract expiration data to the user-side vehicle resale price analysis system 21. The user-side vehicle resale price analysis system 21 transmits expected sale amount data based on the latest data to the exhibition support system 29. The exhibition support system 29 that has received the expected sale amount data transmits the exhibition data including the expected sale amount data (desired sale price) to the contract expiration data to the bidding system 12. In the bidding system 12, based on the received exhibition data, the most suitable selling destination is selected from domestic bidding, overseas bidding, bidding on the Internet using the Internet, auction, retailing at stores, etc.
For example, when the domestic bidding party is selected, the exhibition data is transmitted to the bidding hall system.

Next, the flow of resold vehicle data for which a bid has been made will be described. The bid resale vehicle data is sent from the bid site system 16 to the resale vehicle database 14. The resale vehicle data sent to the resale vehicle database 14 is periodically used by the expected sale amount calculation system 15 and is also periodically transmitted to the user-side vehicle resale price analysis system 21 as update data.

Next, the vehicle resale price analysis system 10, 2
1 will be described. First, the vehicle type database 13 additionally updates the vehicle type data relating to the new vehicle type every time a new vehicle type to be newly produced is announced or manufactured. Here, the new model includes a case where the model approval number is changed. The data stored in the vehicle type database 13 is periodically used for the expected sale price calculation system 15 and is transmitted as update data to the user-side vehicle resale price analysis system 21 periodically or when data is updated. The expected sale price calculation system 15 is also periodically updated with new data, and the updated module such as the correlation equation is sent to the user-side vehicle resale price analysis system as update data. The data in the lease contract database 28 is used for various analyzes in the residual value simulation system 23.

Next, an embodiment of a method for obtaining a residual value calculation equation used for analyzing a vehicle resale price will be described with reference to FIGS. FIG. 2 is a processing flow showing a method for obtaining a residual value calculation equation. First, as a first step, sales performance data on resold vehicles is prepared, and predetermined data on resold vehicles is extracted (S1). The data extracted here is data on the resold vehicles, such as vehicle type data, use contract year, use contract expiration year, use contract period, new vehicle price, sale price after use contract expiration, and mileage when resold. Here, the vehicle type data is data specifying a vehicle such as a maker name, a vehicle type name, a certified model, a vehicle shape, a displacement, a fuel, a shift, a drive system, a door number, a grade, and the like. The use contract year, the expiration date of the use contract, and the use contract period are data determined by the use contract, and do not necessarily require all of these data.For example, along with other data such as the first year registration, Any data can be used as long as it can determine the contract period, contract time, or contract expiration time. Data such as model name, approved model, displacement, vehicle shape, fuel, shift, drive system, number of doors, equipment and other grades and grade options are attached to vehicles to determine weight tax. Since it can be estimated from the model designation number and the classification number, the model designation number and the classification number can be used as data instead of these individual data. Further, it is preferable to include data such as a vehicle number, a first year registration, a registration number, and a vehicle inspection deadline date described in the vehicle verification. The new car price is a standard selling price for a new car. When the standard selling price differs depending on the region, the standard selling price in the reference region is used, but regional differences may be considered. In addition to the standard selling price, the actual selling price can be used. Further, when various equipment such as an air conditioner and a navigation system are provided at the time of delivery of a new vehicle, since the vehicle value differs depending on the equipment, it is preferable to treat a selling price including these equipment as a new vehicle price. The predetermined period for extracting data is determined in consideration of the economy, market trends, product cycles, data parameters, and the like. In other words, it is preferable to set a shorter period for the economic and market trends if the fluctuation is large. For the product cycle, if the cycle period is long, the period may be set long. It is important that the number of data parameters be sufficient for statistical processing.
For example, sale data whose sale date (bid party date) is within the past two years is extracted. In addition, the actual use data on the article is data on the use state of the target article,
In the case of a vehicle, in addition to the distance traveled, the data is status data such as scratches, dents, and paint conditions. This actual use data includes user classification such as lease, rental, etc. even for individuals, corporations, and corporations. Further, the actual use data may be data relating to a use period, a use condition, a use application, or equipment or an accessory added during the use period. For example, in the case of personal computers, equipment, and the like, the presence or absence of software for operating these devices also has value as actual use data.

Next, as a second step, data normalization is performed (S2). First, in order to normalize the data, the data bias is corrected. To eliminate data skew,
Extract data randomly. If there is a bias, the data selection is corrected theoretically or data is added in consideration of the cause of the bias. In addition, for normalization of the data, a car with a bid or an unlisted car is considered. That is, after the expiration of the use period,
Cars that have not been resold and vehicles that have not been exhibited are considered as risks and are excluded (deleted) from the data. In addition, it is preferable that tabulation data such as a list of cars and unsold cars be tabulated for each type of vehicle, and a rate of bids be calculated for each product characteristic or market.

Next, as a third step, the division of the residual value table is set in consideration of the product characteristics and the market (S).
3). That is, the resale articles are distinguished by the characteristic of the product or the market. In this embodiment, the vehicle is used for passenger, commercial,
Freight or vehicle use such as bus, or sedan type,
One section is selected by dividing according to a vehicle shape such as a hatchback type or a one-box type. Then, for example, data for which the vehicle application is classified as riding is extracted.

Next, as a fourth step, an analysis target period to be analyzed is set (S4). For example, classification is made for each lease period, and it is divided into several categories. Then, some periods having a large data parameter are selected as representative periods. In the case where there is a large variation in the use period or a continuous case, an appropriate period is selected in consideration of each category or each product cycle. For example, select vehicles whose lease has expired for 3, 4 or 5 years from past sales data,
Among them, data whose elapsed time at the time of sale is 35 to 37 months is extracted as a representative period for vehicles whose lease has expired for three years.

Next, as a fifth step, among the sales data, items that can be known or set at the time of sale are correlated at various angles, and those having a positive / negative correlation are picked up to create a scatter diagram. (S5). Here, regarding vehicles, the period of use or period of use since the first year registration, popularity index determined according to vehicle type or vehicle type, new vehicle price, resale price at resale, mileage at resale, actual use other than mileage Data can be picked up as items and the correlation between them can be considered. In addition,
For vehicles, the relationship between the new car price and the sale price or the residual value rate obtained by dividing the sale price by the new vehicle price, the relationship between the mileage and the residual value rate obtained by dividing the sale price or the sale price by the new vehicle price, and vehicle type data or The fact that the correlation between the popularity index data determined according to the vehicle type and the residual value rate or the sale price is high is obtained from actual analysis. Here, regarding the articles, the selling time or period of use, the selling price, the sales amount at the time of resale, and the actual use data at the time of resale are picked up as items, and the correlation between them can be considered. In addition,
Among these items, the correlation between the selling price and the selling price or the residual value rate that is the selling price divided by the selling price, and the correlation between the actual use data and the selling price or the residual value rate that is the selling price divided by the selling price. It is preferable to consider the relationship and the correlation between the vehicle type data or the popularity index data determined according to the vehicle type and the residual value rate or the sale price. The scatter diagrams created in this way are shown in FIGS. In the present embodiment, using the data extracted in the fourth step (S4), a scatter diagram shown in FIG. 3 with the X axis as the new vehicle price and the Y axis as the sale price, the X axis as the mileage, and the Y axis as the remaining A scatter diagram shown in FIG. 4 is created as a price.

Next, as a sixth step, an approximate curve (normal equation) is created from each scatter diagram, and the tendency is converted into a function (S6). In the present embodiment, approximate curves (normal equations fa (x) and fb (x)) are created from FIGS. 3 and 4, respectively, and the tendency is made a function to obtain equation data. Here, fa (x) is equation data indicating the correlation between the new vehicle price and the sale price, and fb (x) is the correlation between the mileage and the residual value rate obtained by dividing the sale price by the new vehicle price. It is equation data showing a relationship.

Next, as a seventh step, the base is mutually corrected to the average value using each normal equation to obtain corrected equation data (S7). With this correction equation data, mutual influence is removed from each of the acquired normal equations, and a more accurate normal equation with respect to XY correlation is obtained. Specifically, first, the average new vehicle price and the average mileage of the entire data C3 are calculated. Then, using the average new vehicle price and the average mileage, an average distance converted sales amount and an average new vehicle price converted sales residual value ratio are obtained by the following formula. Average distance conversion sale amount = fa (new car price)-fb (actual mileage) * [new car price] + fb (average mileage) * [new car price] Average new car price conversion sale residual value = fb (actual mileage)- f
a (new car price) / [new car price] + fa (average new car price)
/ [New car price] Then, the scatter diagram in FIG. 5 is plotted with the X axis as the new car price and the Y axis as the average distance converted sales amount, and the scatter plot in FIG. Scatter plots are respectively prepared, and approximate curves (normal equations fa ′ (x), fb ′ (x)) are obtained from FIGS.
And functionalize the trend. Here, the normal equation fa ′
(X) is correction equation data considering the average traveling distance, and fb '(x) is correction equation data considering the average new vehicle price.

Next, as an eighth step, a standard expected sales amount is obtained by calculation from the new vehicle price and the mileage of the sales data by using the normal equation obtained in the seventh step (S8). The standard expected sale price can be obtained by the following formula. Standard expected sale amount = fa '(new car price) + fb' (actual mileage) * [new car price]-k where k is a distance constant determined by the following. k (distance constant) = fb (average mileage) * [new car price] Note that this standard expected sale price can be used as the expected sale price, but it is more accurate by further classifying product characteristics / markets. It is possible to obtain a large expected sale price.

Next, as a ninth step, a function for obtaining the expected sale price is performed (S9). First, product characteristics /
It is divided into groups by market and grouped into the residual value table group. Then, the difference between the actual sales amount and the theoretical standard expected sales amount is obtained, and the residual is reflected for each group. That is, the value or popularity of each group's characteristics that cannot be compensated for by the analysis results alone is taken into account. Specifically, minus the theoretical standard expected sale price / new car price from the actual sale price / new car price, obtain the difference between the actual residual sale value rate and the theoretical residual sale value rate, and average it by vehicle type Rank in descending order in the positive direction. That is, first, individual (sale price-standard expected sale price) / new car price = RZ of the data extracted in the fourth step is obtained. Here, RZ is defined as a deviation, and the sale amount-standard expected sale amount is defined as Z. And
RZ by vehicle type and vehicle shape of data extracted in the fourth step
Of the standard deviation (HRZ) is determined. Then, (RZ + HRZ) is obtained from (RZ-HRZ) for each vehicle type and the average deviation (ARZ) of RZ (deviation) is obtained. After that, the grouping by vehicle type and vehicle shape is indexed in order of increasing average deviation (ARZ) in the positive direction to obtain popularity index data.
Then, this popularity index data is calculated using the rank on the X axis and the ARZ
Is plotted on the Y axis, and a normal equation (fc (x)) is obtained by regression analysis on the correlation between the average values.

Next, as a tenth step, normal equations are adjusted (S10). The adjustment of the normal equation is performed by determining the difference in the degree of wear caused by a factor that is not known or cannot be set at the time of sale by using the variance of the sale price / new car price of the same group. Specifically, it is considered that standard deviation = difference in degree of wear / assessment, and when the degree of return is assumed in advance, the deviation value and the assessment score are linked and reflected in the residual. If not, consider risk hedging and rank down according to certain criteria (Figure 8). That is, it is considered that standard deviation = difference in degree of wear / assessment. For example, if assessment score 2 is defined as a deviation value 45, a value given from residual value rate (fc (x)) of deviation value 45 from assessment expected score 2 Can obtain the deviation value 50). In addition, if the deviation 47 is defined as a standard for risk hedging, a profit for three sections of the deviation is theoretically secured.
This risk hedging process is based on the theoretical average selling price ≤
The adjustment is made by lowering the rank so that it becomes the actual average selling price.

Next, as an eleventh step, the necessity of selecting another predetermined period is determined (S11). That is, when it is necessary to obtain a function for a representative period different from the already selected section, the process returns to step 4 and the representative period is set again. If it is not necessary to set another representative period within the currently selected residual value table section, the process proceeds to step S12.

Next, as a twelfth step, the necessity of another division setting is determined (S12). If it is necessary to change the section of the already selected residual value table and obtain a function for another section, the procedure returns to step 3 and sets another section again. If you do not need to set another category,
End acquisition of equation data.

If it is necessary to add a new model, the model which is considered to be of the same class or the popularity index based on the type of use and the price of the new model is compared with the existing model. Apply the popularity index. As a specific method, when adding a new type of vehicle, a popularity index of a vehicle type vehicle shape group assumed to be equivalent is applied with reference to HRZ or ARZ for each vehicle type. In addition, the new model includes a model change when the model approval number is changed. In addition, the expected standard sale amount in any period is calculated by obtaining the expected standard sale amount from the representative period statistically analyzed in the closest period before and after this arbitrary period, and determining the equation as proportional to that period . If the representative period is only on either side before or after the arbitrary period, two representative periods are selected from those closer to the arbitrary period on the side where the representative period exists.
The two periods are calculated as proportional. Then, with respect to the sampled period, if a condition that is picked up by a group in the residual value table and subjected to regression analysis is given, an expected standard sale amount can be output. Specifically, if the data such as the new vehicle price, the expected mileage, and the type of vehicle (rank) for the sampled period are picked up in the group of the residual value table and given to the regression-analyzed normal equation, the expected sale price can be obtained. it can. The expected standard sales amount can be calculated by the following equation. Expected standard sale amount = fa '(new vehicle price) + fb' (actual mileage) * [new vehicle price]-k + ARZ of vehicle-specific vehicle shape group * [new vehicle price] + HRZ / 10 * of vehicle-specific vehicle shape group ((Designated deviation value) -50) * [new car price]

Note that it is preferable to consider the reasons for showing a certain tendency. In a vehicle, the evaluation is influenced by the model year. Therefore, in order to predict the resale amount of a vehicle, it is important to reduce the amount in consideration of this specialty, the number of years of omission. For example, if a vehicle whose three-year lease expires in December for the first year registration is sold in the following month, the vehicle will fall off by four years.
As described above, in the case of articles that are often evaluated on a year-by-year basis, consideration is given to a slight reduction in the sales amount. In addition, since the expected standard sale price is a pure sale price, the amount of increase or decrease should be determined by adding, as necessary, indirect costs such as sales expenses, sales profits, etc., or strategic profits such as strategic products as the residual value. Is preferred. Further, it is preferable to use the variance and standard deviation of the data for each group as a risk hedge of the expected standard sale amount to increase or decrease the price by converting the deviation value.

Next, another embodiment of a method for obtaining a residual value calculation equation used for analyzing a vehicle resale price will be described with reference to FIG. FIG. 9 is a processing flow showing a method for obtaining the residual value calculation equation. Note that the same steps as those in the embodiment shown in FIG. In the fifth step, a scatter diagram may be created as in the above embodiment,
An item may be selected by performing a correlation analysis on data that seems to affect the residual value rate.

In the sixth step, multiple regression analysis is performed on the hit item, and the correlation is confirmed to select an appropriate item (S16). As a result of multiple regression analysis by extracting the sales data within the past two years with the sale date (bid party date), the number of months passed,
Monthly mileage, new car price, displacement, light automatic classification (660
CC or not), automobile tax classification (luxury car = 3)
000CC or more), vehicle application category (passenger or not), old and new category (elapsed months 30 months or less), fuel (gasoline or not), ABS equipment or not A correlation could be found. In addition, specific vehicle classification (here, particularly popular,
For example, a vehicle type / vehicle shape that indicates a special tendency, such as a corolla or a sprinter, which indicates whether or not the vehicle type / vehicle shape is present, also indicates a tendency to be considered. Where elapsed months, monthly mileage,
New vehicle price and displacement are independent variables, and light automatic classification, automobile tax classification, vehicle shape classification, new old classification, fuel classification, and specific vehicle classification are dummy variables of "1" or "0". Regression analysis is performed on each selected item and the residual value rate, and the data is indexed (logarithmic, exponentiated, exponential, or the like) in some cases so as to well fit linear regression. For example, the number of elapsed months is indexed logarithmically. Then, (raw data−average value) / standard deviation = standardized data, and the data is used as statistical standardized data. And
The correlation between the selected item and the residual value rate is obtained by multiple regression analysis, and the partial regression coefficient and intercept (constant term) of each item are obtained.

As a seventh step, whether or not the result is reliable is evaluated by a determination coefficient, a multiple determination coefficient, a t-test, or the like (S17). As an eighth step, the values of the partial regression coefficient and the intercept (constant term) are applied to the multiple regression equation, the theoretical residual value rate is determined from the selected item, and the difference from the actual residual value rate is determined as the residual (S18). ). As a ninth step, the residual value rate is determined (S19). The average and standard deviation of the residuals are obtained for each category and used as the theoretical residual value rate. The standard deviation is defined as a variable factor of the sale price due to factors that cannot be predicted in advance or a variable factor of the sale price due to factors that cannot be grasped at present. And the risk of hedging;
As an assessment, the residual value rate is determined by adding or subtracting from the theoretical residual value rate.
For example, the difference in the degree of wear is defined in five stages (1 = deviation value 40,
2 = deviation value 45, 3 = deviation value 50, 4 = deviation value 55, 5
= Deviation value 60) to obtain the expected assessment score, and the theoretical residual value rate as the deviation value 50 is added to or subtracted from the expected assessment score to the theoretical residual value rate to obtain the residual value rate. The case of adding a new model is the same as that of the above embodiment, and the description is omitted.

Using the multiple regression equation obtained by the above steps, the popularity index and standard deviation for each category, and the vehicle type database, specifying the vehicle type from the vehicle type database,
The sale price after the expiration of the contract can be calculated from the contracted months, the estimated monthly mileage, the new vehicle price, and the estimated assessment score. The popularity index / standard deviation by category, mini vehicle category, automobile tax category (luxury car), and vehicle shape category can be obtained from the vehicle model database, and the old and new categories must be obtained from the number of months elapsed from the contract by arithmetic processing. Can be.
FIG. 10 shows multiple determination indices for each item considered, as a result of extracting multiple sales data (the number of data is 35,000) within the last two years and performing multiple regression analysis. The prerequisites are light automatic classification, automobile tax classification, vehicle usage classification,
Old and new, fuel, and specific vehicle categories were considered as dummy variables. The selected items are the number of elapsed months, the displacement, the new car price, and the monthly mileage. The first embodiment takes into account the elapsed months, the displacement, the new vehicle price, and the monthly mileage, the second embodiment takes into account the elapsed months, the new vehicle price, and the monthly mileage, and the third embodiment takes the In the fourth embodiment, the number of elapsed months, the displacement, and the monthly mileage are taken into account.
Is the one that takes into account the displacement, the new car price, and the monthly mileage, and the sixth embodiment is the one that takes into account the elapsed months and the new car price,
The seventh embodiment takes into account the new vehicle price and the monthly mileage,
The eighth embodiment takes into account the number of elapsed months and the displacement, and the ninth embodiment takes into account the displacement and the monthly traveling distance. As shown in FIG. 10, Example 1 in which four items are considered has the highest matching rate, but Example 2 shows a matching rate close to Example 1 regardless of the three items. In Example 3,
In Example 4 and Example 6, the multiple determination index was also the second highest. In particular, Example 6 shows a high matching rate despite two items.

Next, referring to FIG. 11 to FIG.
An analysis system for predicting residual value profit / loss, assets, and determining the residual value of a new contract vehicle will be described. FIG. 11 to FIG.
All are screen image diagrams of the same system. FIG.
Is a screen image diagram for obtaining an expected sale price and an expected residual value rate for a specific vehicle during a contract period or a specific vehicle at the time of a new contract, for example. In the figure, the model name is “Corolla”, the specification is “Diesel DX 4FAT 2WD”, the lease period is “60” months, the scheduled registration date is “00/05/15”, the expected mileage is “100” 1,000 km, the rating is “3”, By inputting the new vehicle amount of “1,272” thousand yen, the expected sale amount is “191” thousand yen, the standard sale amount is “197” thousand yen, the average sale amount is “186” thousand yen, and the expected residual value rate is “15. 0% ", the standard sales rate" 15.6% ", the average sales rate" 14.7% ", the standard sales amount and the number of resold vehicles that were subject to the standard sales rate" 12 ", and the number of vehicles resold The standard distance of “12 vehicles” is “102” thousand km, the average sale amount and the average sale rate are “18 vehicles”, and the average distance of the “18 vehicles” is “101” thousand. km, and vehicles sold in the past (successful bid price, sale rate, manufacturer, model, Both applications,
Displacement, grade, months, year, new car price, mileage,
Mission, fuel, drive, date of the event). Model name "Corolla" and specifications "Diesel
"DX 4FAT 2WD" can also be selected and input by a pull-down method. In the same figure, "Corolla" and specification "Diesel DX 4FAT 2W
By inputting "D", the manufacturer name "Toyota", the certified model "KA-CE106V", the vehicle shape "BV", and the displacement "2000" are displayed, but the "Corolla" and the specification "Diesel DX4FAT 2WD" are displayed. Instead of inputting the manufacturer name "Toyota" and the certified model "KA-CE10
6V ", vehicle shape" BV ", and displacement" 2000 "may be input. Instead of inputting "Corolla" and specification "Diesel DX 4FAT 2WD", a model designation number or a classification number may be input. Also, the expected mileage of “100” thousand km may be output without being input and linked to the lease period of “60” months. New car price "1,2
The "72" thousand yen is also an item that can be determined according to the vehicle type and specifications, and can be output and displayed from a database that is previously associated with the vehicle type name and the like. Rating "3"
The term “evaluation and evaluation” means, for example, classification based on a user such as a leasing person, a place of use, or a purpose of use (commercial or private use). The “expected sale price” and the “expected residual value rate” are calculated and output using the equation data and the multiple regression equation acquired in advance in the above embodiment. On the other hand, “Average sales amount”, “Average sales rate” and “Average distance”
Are calculated and output from the actual data of the resold vehicles that match the vehicle specified by the “vehicle type name”. In the case of the drawing, it is indicated that there are 18 corresponding vehicles. On the other hand, the “standard sales amount”, “standard sales rate”, and “standard distance” are obtained by correcting data bias as (actual data−average value) / standard deviation. In the case of the drawing, there are 12 corresponding vehicles after the correction. It is sufficient for the output to indicate the expected sale price or the expected residual value rate. However, by indicating both the expected sale price and the expected residual value rate, the effect is obtained that the residual value and the like can be easily grasped.
In addition, by showing the standard sale price, average sale price, standard sale rate, average sale rate, etc., it is easy to grasp the accuracy of the expected sale price and the expected residual value rate, as well as the presence or absence of specificity depending on the model be able to. In addition, vehicles sold in the past (successful bid price, sale rate, manufacturer, vehicle type, vehicle shape, displacement, grade, months, year, new vehicle price, mileage, mission,
By displaying a list of (fuel, driving, date of holding), it is possible to confirm the factors that cause the value to be higher or lower than the average value.

FIG. 12 is a screen image diagram for estimating the residual value profit and loss based on the expected residual value for a specific vehicle during the contract period, for example. In the present embodiment, the market at the time of contract expiration is predicted based on the current market, and a relative value based on relative evaluation is set. Then, an expected standard sale amount at that time is obtained from the unsold contract data, and the expected standard sale amount at the time of contract expiration is obtained by multiplying the relative value at the time of contract expiration. Then, a residual value profit and loss is obtained from the contract residual value and the expected standard sale amount. Specifically, new car prices in unsold contract data,
The expected standard sales amount at the time is calculated from the estimated mileage, the vehicle type, and (the expected evaluation score at the time of return), and the relative value at the time of expiration of the contract is multiplied to obtain the expected standard sales amount at the time of the expiration of the contract.
Then, based on the contract residual value-expected standard sale amount, an appropriate management unit and product characteristics / market and vehicle type are collected based on the accounting unit, and the residual value profit / loss for each management unit is obtained.

In the figure, for the vehicle type name “Corolla” currently contracted, “Contract residual value” by vehicle shape and year,
“Expected residual value” and “residual value gain / loss” are shown. Here, "contract residual value" is the residual value set at the time of contract,
The “expected residual value” is a residual value calculated and output using equation data or a multiple regression equation acquired in advance in the above embodiment. "Residual value" is the difference between "Contract residual value" and "Estimated residual value". If it is close to zero, it means that it is expected to be sold at the residual value set at the time of the contract and no profit or loss has been generated. I do. For example, "Corolla BV" would be expected to generate a profit of "968" for vehicles whose contract expires in 2000, but would generate a loss of "9039" for vehicles whose contract expires in 2003. It shows that it becomes prediction. Note that, although the vehicle type display is shown in FIG. 3, the display may be performed for all contract vehicles or a specific manufacturer name. In addition, by registering the store division and the salesperson division in the database, it is possible to output the residual value profit and loss for each store and each salesperson. Also, although omitted in the figure, by displaying the number of target vehicles,
You can also know the profit and loss per vehicle. FIG. 13 is a screen image diagram for estimating the residual value profit and loss of each vehicle type during the contract period. As shown in the figure, the residual value profit and loss are displayed for each vehicle type and vehicle shape. In this manner, by displaying the residual value profit and loss for each vehicle type and vehicle shape, it is possible to compare the respective profit and loss situations.

FIGS. 14 and 15 are screen image diagrams for estimating the residual value profit and loss based on the expected residual value for a specific vehicle during the contract period, for example, and are substantially the same as FIG. 14 and 15 are characterized in that they are systems capable of coping with economic fluctuations. "2000
“100” is displayed in the upper column of the year display column of “Year” to “2006”.
%) Is displayed, but if all are displayed as "100%",
It does not take into account economic fluctuations. With respect to this economic fluctuation, it is possible to display a fluctuation rate based on other economic situation analysis data and the like, and to apply it to each expected residual value. In addition, by giving future fluctuation factors to the residual value such as fluctuations in the future market and sales volume, the expected standard sales amount will fluctuate for each residual value group (management unit, model), and how the residual value profit and loss will be. You can also simulate what will happen. In such a simulation, it is preferable to perform a simulation including the future by giving a planned sales amount (budget). With the above simulation, the direction of the optimization can be determined. That is, it is possible to determine whether the residual value profit / loss is a specified amount, the residual value profit / loss is secured at a specified rate, the fixed rate collection is performed at a contract new vehicle price, the fixed rate collection is performed for each contract, or the fixed amount collection is performed for each contract. . If a residual value group or a model (vehicle type) is specified within a range that gives the expected sales volume for each new vehicle price, the new vehicle price and the expected sales volume are given for each specified residual value group or model (vehicle type). If the new vehicle price and the expected sales volume can be given for each residual value group or model (vehicle type), the accuracy will be further increased. If the sales prospect is not given, the sales results can be substituted. The management unit,
The expected standard sales amount + adjustment amount is set as the residual value for each residual value table, residual value group, or model (vehicle type). It is also preferable to consider risks, profits, overhead costs, etc., which are recalculated every management unit period.

FIGS. 16 to 18 are screen image diagrams for obtaining the overall tendency of the expected sale price and the expected residual value rate. FIG. 16 is a screen image diagram showing the tendency of the new car price and the contract price for each lease period, FIG. 17 is a screen image diagram showing the tendency of the mileage and the residual value rate for each leasing agency, and FIG. 18 is the lease period and the residual value rate. It is a screen image figure showing the tendency. FIG.
6 displays a graph with the new car price as one axis and the contract price as the other axis, and displays the actual data of the new car price and the contract price on the resold vehicles on the graph, as well as the new car price and the contract price. The correlation with is displayed. The correlation between the new car price and the contract price, and the actual data on which it is based, are displayed in different colors for a three-year lease and a five-year lease. The successful bid price (sale price) may be a residual value rate obtained by dividing the sale price by the new vehicle price. In the embodiment shown in FIG. 16, the correlation with the new vehicle price, which is already empirically recognized as having a large effect on the sale price, from the sale data on the vehicles that have already been resold is visually grasped. And an objective anticipated sale value for vehicles to be resold.

FIG. 17 shows a graph in which the mileage is set on one axis and the residual value rate obtained by dividing the sale price by the new car price is set on the other axis. Is displayed, and the correlation between the mileage and the residual value rate is displayed. The correlation between the mileage and the residual value rate and the actual data on which it is based are displayed in different colors for a three-year lease and a five-year lease. Note that the residual value rate may be a successful bid price (sale price). In the embodiment shown in FIG. 17, the correlation with the mileage, which is already empirically recognized as having a large effect on the sale price, is visually grasped from the sale data regarding the vehicles that have already been resold. And an objective anticipated sale value for vehicles to be resold.

FIG. 18 shows a graph in which the lease period is set on one axis, and the residual value rate obtained by dividing the sale price by the new vehicle price is set on the other axis. The mileage and the residual value rate for the resold vehicles are shown on the graph. Is displayed, and the correlation between the mileage and the residual value rate is displayed. Note that the residual value rate may be a successful bid price (sale price). In the embodiment shown in FIG. 18, it is possible to visually grasp the correlation with the lease period, which is already empirically recognized as having a large effect on the sale price, from the sale data on the vehicles that have already been resold. And an objective anticipated sale value for vehicles to be resold. 3 to 8 which have already been described in the analysis of the correlation, the same effects as described above can be obtained by displaying them as screen image diagrams for obtaining the overall tendency of the expected sale price and the expected residual value rate. It should be noted that the actual travel situation can be more accurately represented by using the average travel distance within a predetermined period, such as a month or year, in addition to the total travel distance, as the travel distance described in the above embodiment. Further, in the above-described embodiment, the vehicle has been described as an example, but the present invention is also applicable to articles other than the vehicle, such as ships, machine tools, equipment, and personal computers. Further, the article in the present invention may be software such as a program, and is a concept including real estate such as a house or a building, and equipment, even if it is not necessarily a personal property.

[0101]

As described above, according to the present invention, it is possible to objectively predict the sale price of an article before resale from the sale data of an article such as a resold vehicle without relying on human experience. Can be provided. Further, the present invention can provide a vehicle resale price analysis system capable of obtaining information on an objective expected sale price and the like for a vehicle to be resold. Further, the present invention can provide a residual value profit / loss analysis system capable of obtaining objective residual value profit / loss information at the time of contract expiration for a vehicle during a use contract period. Further, the present invention can provide an asset evaluation system capable of obtaining objective market value information at any time regarding a vehicle during a use contract period. Further, the present invention can provide a residual value setting system capable of obtaining objective residual value prediction information on a new contract vehicle. Further, the present invention can provide a storage medium capable of acquiring a correlation equation for obtaining an objective sale price or the like for a new contract vehicle or a table in which the correlation is associated. Further, the present invention can provide a storage medium capable of obtaining an objective sale price or the like for a new contract vehicle. In addition, the present invention can obtain a correlation formula or a table in which a correlation is obtained for obtaining an objective sale price or the like with respect to a new contracted vehicle. Storage medium capable of outputting information about the storage medium. Further, the present invention can provide a display device capable of outputting information on a resold vehicle that is a source of a predicted sale amount or the like. Further, the present invention can provide a residual value setting system that can set a residual value for a new contract vehicle. Further, the present invention can provide a residual value setting system capable of setting a residual value for a new contract article. Further, the present invention can provide a residual value setting system capable of setting a residual value for a new type of vehicle. Further, the present invention can provide a vehicle resale price analysis system capable of more accurately obtaining an expected sale price for an average vehicle having no special reason.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an overall configuration including a vehicle resale price analysis system according to an embodiment of the present invention.

FIG. 2 is a process flow showing a method for obtaining a residual value calculation equation according to an embodiment of the present invention.

FIG. 3 is a scatter diagram in which the X-axis according to the embodiment is a new vehicle price and the Y-axis is a sale price.

FIG. 4 is a scatter diagram in which the X-axis according to the present embodiment is a mileage and the Y-axis is a residual value rate.

FIG. 5 is a scatter diagram in which the X-axis according to the present embodiment is a new vehicle price and the Y-axis is an average distance conversion sale price

FIG. 6 is a scatter diagram in which the X-axis and the Y-axis according to the present embodiment are plotted with the mileage and the average new vehicle price conversion residual value, respectively.

FIG. 7 is a scatter diagram in which a rank according to the present embodiment is set on the X axis and ARZ is set on the Y axis.

8 is a scatter diagram obtained by adjusting the normal equation in FIG. 7;

FIG. 9 is a process flow showing a method for obtaining a residual value calculation equation according to another embodiment of the present invention.

FIG. 10 is a graph showing multiple determination indices when the number of elapsed months, the displacement, the price of a new vehicle, and the mileage per month are selected as items according to the embodiment;

FIG. 11 illustrates a system according to an embodiment of the present invention.
Image of the screen for obtaining the expected sale price and expected residual value rate for a specific vehicle during the contract period or a specific vehicle at the time of a new contract

FIG. 12 shows a system according to an embodiment of the present invention.
Screen image diagram for estimating residual value gain or loss based on expected residual value for a specific vehicle during the contract period

FIG. 13 illustrates a system according to an embodiment of the present invention.
Image of the screen for estimating the residual value profit and loss of each vehicle type during the contract period

FIG. 14 illustrates a system according to an embodiment of the present invention.
Screen image diagram for estimating residual value gain or loss based on expected residual value for a specific vehicle during the contract period

FIG. 15 illustrates a system according to an embodiment of the present invention.
Screen image diagram for estimating residual value gain or loss based on expected residual value for a specific vehicle during the contract period

FIG. 16 illustrates a system according to an embodiment of the present invention.
Screen image showing trends in new car prices and contract prices by lease period

FIG. 17 shows a system according to an embodiment of the present invention.
Screen image showing trends in mileage and residual value rate by leasing agency

FIG. 18 illustrates a system according to an embodiment of the present invention.
Screen image showing trends in lease period and residual value rate

[Explanation of symbols]

 Reference Signs List 10 resale support system 11 support side vehicle resale system 12 bid support system 13 model database 14 already resale vehicle database 15 expected sale price calculation system 16 bid hall system 20 user side system 21 user side vehicle resale price analysis system 22 residual value setting system 23 Residual value simulation system 24 Residual value profit / loss analysis system 25 Asset valuation system 26 Estimation system 27 Core system 28 Lease contract database 29 Exhibition support system

Claims (64)

[Claims] 1. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, approved model, model designation number, classification number, mission, drive system, displacement, number of doors, common name model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, exhaust gas regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the sale amount, residual value, or residual value rate of vehicles before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. A first step of extracting data on resold vehicles resold within a predetermined period, and correlating a factor affecting a vehicle resale price using the data extracted in the first step. A second step of extracting by analysis;
A third step of obtaining a multiple regression equation from a correlation between the extracted factor and data on the sold amount, and calculating the multiple regression equation obtained in the third step based on an estimated sale amount of the vehicle before resale. A vehicle resale price analysis system for use in predicting information on an expected residual value or an expected residual value rate. 2. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, common model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, exhaust gas regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the sale amount, residual value, or residual value rate of vehicles before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. A first step of extracting data on resold vehicles resold within a predetermined period, and using the data extracted in the first step, a new car price and a sale price or a sale price in a new car price. A second step of obtaining first equation data indicating a correlation with the residual value rate obtained by the division, and using the data extracted in the first step, the mileage and the sales amount or the sales amount to the new vehicle price. A third step of obtaining second equation data indicating a correlation with the divided residual value rate, and a first step in which an average mileage is considered using the first equation data and the second equation data. A fourth step of obtaining correction equation data, a fifth step of obtaining second correction equation data in consideration of an average new vehicle price using the first equation data and the second equation data,
Using the first correction equation data and the second correction equation data, third equation data indicating the correlation between the vehicle type data or the popularity index data determined according to the vehicle type and the residual value rate or the sale price is calculated. And a sixth step of obtaining
The third equation data is used to calculate the expected sale price of the vehicle before resale,
A vehicle resale price analysis system for use in predicting information regarding an expected residual value or an expected residual value rate. 3. Manufacturer name, vehicle type name, vehicle application, vehicle shape, vehicle type grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, common model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, exhaust gas regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the sale amount, residual value, or residual value rate of vehicles before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. Data from the data on resold vehicles resold within a predetermined period, at least data on the actual use period such as the number of months since the first year registration or use contract year or use contract period, and data on the displacement. And using the data on the new vehicle price and the data on the mileage during the actual use period, with respect to the expected sale price, the expected residual value, or the expected residual value rate of the vehicle before resale. Vehicle resold price analysis system and obtaining a table that associates a correlation equation or correlation for obtaining the distribution. 4. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, approved model, model designation number, classification number, mission, drive system, displacement, number of doors, common model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, exhaust gas regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the sale amount, residual value, or residual value rate of vehicles before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. Data from the data on resold vehicles resold within a predetermined period, at least data on the actual use period such as the number of months since the first year registration or use contract year or use contract period, and data on the displacement. And a correlation equation for obtaining information on the expected sale price, expected residual value, or expected residual value rate of the vehicle before resale using the data on the mileage during the actual use period. Vehicle resold price analysis system and obtaining a table that associates correlation. 5. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, approved model, model designation number, classification number, mission, drive system, displacement, number of doors, common model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, exhaust gas regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the sale amount, residual value, or residual value rate of vehicles before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. And, from among the data on the resold vehicles resold within a predetermined period, at least data on the displacement, data on the new vehicle price, and data on the mileage during the actual use period before resale using data. A vehicle for acquiring a correlation equation or a table in which a correlation is obtained for obtaining information on an expected sale value, an expected residual value, or an expected residual value rate of the vehicle. Resale price analysis system. 6. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, common model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, exhaust gas regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the sale amount, residual value, or residual value rate of vehicles before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. And among data on resold vehicles resold within a predetermined period, at least data on the actual use period such as the number of months since the first year registration or use contract year or use contract period and data on the new vehicle price. To obtain a correlation formula or a table that correlates the correlation to obtain information on the expected sale price, expected residual value, or expected residual value rate of the vehicle before resale. Vehicle resale price analysis system according to claim. 7. The vehicle resale price analysis system according to claim 6, wherein data relating to a traveling distance during the actual use period is used. 8. The vehicle resale price analysis system according to claim 6, wherein data on the displacement is used. 9. The vehicle resale price analysis system according to claim 3, wherein the data is classified according to whether the vehicle is a mini vehicle or not and data on the classified resold vehicles is used. 10. The vehicle resale price according to claim 3, wherein whether or not the vehicle is a luxury vehicle is classified according to a vehicle tax classification, and data on the classified resold vehicles is used. Analysis system. 11. The resold vehicles are classified according to vehicle applications such as passenger, commercial, freight, or bus, or according to vehicle shapes such as sedan type, hatchback type, or one-box type. 9. The vehicle resale price analysis system according to claim 3, wherein data is used. 12. An estimated sale amount of a vehicle before resale using an acquired correlation equation or a table in which the correlation is associated,
The vehicle resale price analysis system according to any one of claims 3 to 11, wherein information relating to an expected residual value or an expected residual value rate is output. 13. An arbitrary point in time of a vehicle during a use contract period using a correlation equation or a table in which a correlation is obtained by the vehicle resale price analysis system according to any one of claims 3 to 11. Residual value profit and loss analysis system characterized by outputting residual value profit and loss information in the system. 14. An arbitrary point in time of a vehicle during a use contract period using a correlation expression or a table in which a correlation is obtained by the vehicle resale price analysis system according to any one of claims 3 to 11. An asset valuation system characterized by outputting market value information at a time. 15. A residual value forecast information relating to a newly contracted vehicle is output using a correlation equation or a table in which the correlation is obtained by the vehicle resale price analysis system according to any one of claims 3 to 11. A residual value setting system. 16. A correlation for obtaining information on an expected sale price, an expected residual value, or an expected residual value rate of a vehicle before resale by the vehicle resale price analysis system according to any one of claims 3 to 11. A storage medium storing data used for acquiring a table in which an expression or a correlation is associated. 17. A storage medium storing data used in the vehicle resale price analysis system according to claim 3. Description: 18. A storage medium storing data used in a vehicle resale price analysis system for predicting information on a sale amount, a residual value, or a residual value rate of a vehicle before resale using data on a resold vehicle, Regarding resold vehicles resold within a predetermined period, at least data on the actual use period such as the number of months elapsed from the first year registration or use contract year or use contract period, data on displacement, data on new vehicle price, A storage medium storing data on a traveling distance during the actual use period. 19. A storage medium storing data used in a vehicle resale price analysis system for predicting information on a sale amount, a residual value, or a residual value rate of a vehicle before resale using data on a resold vehicle, Regarding resold vehicles resold within a predetermined period, at least data on the actual use period such as the number of months elapsed from the year of registration or use contract or the use contract period, data on the displacement, and data on the displacement during the actual use period A storage medium storing data on a traveling distance. 20. A storage medium storing data used for a vehicle resale price analysis system for predicting information on a sale amount, a residual value, or a residual value rate of a vehicle before resale using data on a resold vehicle, For resold vehicles resold within a predetermined period, at least data on displacement,
A storage medium storing data relating to a new vehicle price and data relating to a mileage during the actual use period. 21. A storage medium storing data used in a vehicle resale price analysis system for predicting information on a sale amount, a residual value, or a residual value rate of a vehicle before resale using data on a resold vehicle, Regarding the resold vehicles resold within a predetermined period, at least data on the actual use period such as the number of months elapsed from the year of registration or use contract or the use contract period and data on the new vehicle price are stored. Storage medium. 22. The storage medium according to claim 21, wherein data relating to a travel distance during the actual use period is stored. 23. The storage medium according to claim 21, wherein data relating to the displacement is stored. 24. The storage medium according to claim 18, wherein data that can be classified according to whether the vehicle is a mini vehicle or not is stored. 25. The storage medium according to claim 18, wherein data related to a vehicle tax classification is stored. 26. Data that can be classified according to vehicle usage such as passenger, commercial, freight, or bus, or vehicle shape such as sedan type, hatchback type, or one-box type. 18
24. The storage medium according to claim 23. 27. A display device for displaying data stored in the storage medium according to claim 18. Description: 28. Output of information relating to an expected sale price, an expected residual value, or an expected residual value rate of a vehicle before resale using data stored in the storage medium according to any one of claims 18 to 26. A vehicle resale price analysis system characterized by: 29. A method for outputting residual value profit / loss information at an arbitrary point in time of a vehicle during a use contract period using data stored in the storage medium according to claim 18. The residual value profit and loss analysis system. 30. A method for outputting market value information at an arbitrary time point regarding a vehicle during a use contract period using data stored in a storage medium according to claim 18. Asset valuation system. 31. A residual value setting system for outputting residual value expected information relating to a newly contracted vehicle using data stored in the storage medium according to any one of claims 18 to 26. 32. Correlation of at least the elapsed period or use period from the first year registration, the popularity index determined according to the vehicle type or the vehicle type, the new vehicle price, the resale amount at the time of resale, and the mileage at the time of resale for the resale vehicle. A vehicle resale price analysis system for predicting information on the sale price, residual value, or residual value rate of a vehicle before resale using a correlation formula derived from the above or a table in which the correlation is associated, wherein the first year registration Estimated sales amount at the time of resale by inputting or selecting data on elapsed time or usage period, popularity index determined according to vehicle type or vehicle type, new vehicle price, mileage,
A vehicle resale price analysis system, which outputs information relating to an expected residual value or an expected residual value rate. 33. Correlate at least a manufacturing formula or a sales period or a use period, a selling price, a sales amount at the time of resale, and a correlation expression derived from a correlation of actual use data at the time of resale, or associating the correlation with respect to already resold articles. An article resale price analysis system that predicts information about the sale price, residual value, or residual value rate of goods before resale using a table that has been manufactured or sold. An article resale price analysis system, which outputs information on an expected sale amount, an expected residual value, or an expected residual value rate at the time of resale by inputting or selecting data on actual use. 34. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, common model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, emission regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the amount of sale, residual value, or residual value rate of a vehicle before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. At the time of resale by entering or selecting data on the model name, model designation number, or approved model, and data on the lease period or use period, first year registration year, expected mileage, assessment, or new car price A vehicle resale price analysis system, which outputs information relating to an expected sale price, an expected residual value, or an expected residual value rate. 35. A vehicle before resale using at least a new vehicle price, a sale amount at the time of resale, or a correlation formula derived from a mileage at the time of resale or a table in which the correlation is correlated with respect to a resold vehicle. A vehicle resale price analysis system that predicts information about the sale price, residual value, or residual value rate of a vehicle, and by inputting or selecting data on a new vehicle price or mileage, the expected sale price at resale, the expected residual value, Alternatively, a vehicle resale price analysis system that outputs information on an expected residual value rate. 36. For a resale item that has not been resold, at least a selling price, a resale amount at the time of resale, or a correlation formula derived from a correlation between actual use data at the time of resale or a table in which the correlation is associated is used. An article resale price analysis system that predicts information about the sale price, residual value, or residual value rate of goods, and inputs or selects data on sales prices or actual use to estimate the expected sale price and residual value at resale. Or information about an expected residual value rate, which is output from the article resale price analysis system. 37. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, authorized model, model designation number, classification number, mission, drive system, displacement, number of doors, common model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, emission regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the amount of sale, residual value, or residual value rate of a vehicle before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. A vehicle resale price analysis system, which outputs information on individual vehicles related to resold vehicles, together with information on an expected sale amount, an expected residual value, or an expected residual value rate at the time of resale. 38. Information on individual vehicles related to resold vehicles includes a sale rate, a manufacturer name, a vehicle type name, a vehicle type, a displacement, a grade, an elapsed month, a year, a new vehicle amount, a mileage,
38. The vehicle resale price analysis system of claim 37, wherein the system includes a mission, fuel, drive scheme, or year of sale. 39. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, approved model, model designation number, classification number, mission, drive system, displacement, number of doors, common name model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, emission regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A vehicle resale price analysis system that predicts information about the amount of sale, residual value, or residual value rate of a vehicle before resale using data on resold vehicles, such as sales price, mileage at resale, assessment at resale, etc. And information on the expected sale price, expected residual value, or expected residual value rate at the time of resale, as well as the average mileage, average sale price, average sale rate, or average new car price for the resold vehicles,
Alternatively, a vehicle resale price analysis system for outputting a standard mileage, a standard sale amount, a standard sale rate, or a standard new vehicle price for a resold vehicle within a predetermined deviation value among the resold vehicles. 40. Entering or selecting data relating to a vehicle type name, a model designation number, or an approved model, and data relating to a lease period or a use period, a first year registration year, an expected mileage, an assessment, or a new vehicle price, Information on the expected sale price, expected residual value, or expected residual value rate at the time of resale, along with the sale rate, manufacturer name, model name, vehicle shape, displacement,
A vehicle resale price analysis system, which outputs information on individual vehicles related to resold vehicles including grade, elapsed months, year, new vehicle amount, mileage, mission, fuel, drive system, or year of sale. 41. A vehicle resale price analysis system for predicting information on a sale amount, a residual value, or a residual value rate of a vehicle before resale from at least a correlation between a new vehicle price and a sale amount at the time of resale regarding an already resold vehicle. Displaying a graph using the new vehicle price as one axis and the remaining value obtained by dividing the sale amount or the sale amount by the new vehicle price as the other axis, and displaying the new vehicle related to the resold vehicle on the graph. While displaying the actual data of the price and the sale price or the residual value rate,
A vehicle resale price analysis system for displaying a correlation between the new vehicle price and the sale price or the residual value rate. 42. A vehicle resale price analysis system for predicting information on a sale amount, a residual value, or a residual value rate of a vehicle before resale from at least a correlation between a sale amount at the time of resale and a mileage at the time of resale for a resold vehicle. And displaying a graph using the mileage as one axis and the sale price or the residual value rate obtained by dividing the sale price by a new vehicle price as the other axis, on the graph, regarding the resold vehicle. A vehicle resale price analysis system displaying actual data of the mileage and the sale price or the residual value rate and displaying a correlation between the mileage and the sale price or the residual value rate. . 43. Information on a sale price, a residual value, or a residual value rate of a vehicle before resale is predicted from at least the resale amount of the resold vehicle at the time of resale and the correlation between the vehicle type or a popularity index determined according to the vehicle type. A vehicle resale price analysis system, wherein the vehicle type or the popularity index is used as one axis, and the sale price or the residual value rate obtained by dividing the sale price by a new vehicle price is used as a second axis, and the graph is displayed. Above, the actual data of the vehicle type or the popularity index and the sale price or the residual value rate for the resold vehicle is displayed, and the correlation between the vehicle type or the popularity index and the sale price or the residual value ratio is displayed. A vehicle resale price analysis system characterized by displaying a relationship. 44. The vehicle resale price analysis system according to claim 41, wherein a plurality of the correlations are displayed for each elapsed period or use period since the first year registration. 45. The vehicle resale price according to claim 41, wherein said correlation is defined by an equation obtained by regression analysis from actual data on said resold vehicles. Analysis system. 46. An article resale price analysis system for predicting information on the sale price, residual value, or residual value rate of an article before resale from at least the correlation between the selling price and the sale price at the time of resale of the already resold article. Displaying a graph using the selling price as one axis and the remaining value obtained by dividing the selling price or the selling price by the selling price as the other axis, and displaying the sales related to the resold articles on the graph. While displaying the actual data of the price and the sale price or the residual value rate,
An article resale price analysis system for displaying a correlation between the sale price and the sale price or the residual value rate. 47. An article resale price analysis for predicting information on the sale amount, residual value, or residual value rate of an item before resale from at least the correlation between the sale amount at the time of resale and the actual use data at the time of resale for the already resale item. The system, wherein the actual use data is used as one axis, and a graph is used in which the sale price or the residual value rate obtained by dividing the sale price by the sale price is used as the other axis, and the resale is performed on the graph. An article characterized by displaying the actual data of the actual use data and the sale price or the residual value rate relating to the article and displaying the correlation between the actual use data and the sale price or the residual value rate. Resale price analysis system. 48. Information on the sale price, residual value, or residual value rate of the product before resale is predicted from at least the resale value of the resale item at the time of resale and the correlation between the model and the popularity index determined according to the model. An article resale price analysis system, wherein the model or the popularity index is used as one axis, and the sale price or the residual value rate obtained by dividing the sale price by the sale price is used as the other axis. Above, the actual data of the model or the popularity index and the sale price or the residual value rate for the resold article is displayed, and the correlation between the model or the popularity index and the sale price or the residual value rate is displayed. An article resale price analysis system characterized by displaying a relationship. 49. The article resale price analysis system according to claim 46, wherein a plurality of the correlations are displayed according to an elapsed period from a manufacturing or sales time or a use period. 50. The article resale price according to any one of claims 46 to 48, wherein said correlation is defined by an equation obtained by regression analysis from actual data on said resold articles. Analysis system. 51. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, approved model, model designation number, category classification number, mission, drive system, displacement, number of doors, common name model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, emission regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires Is a residual value profit / loss analysis system that predicts the residual value gain / loss of vehicles before resale using data on resold vehicles, such as the amount sold, mileage at resale, and assessment at resale. Calculate the expected sale price at the time of resale from the new vehicle price, monthly average mileage, estimated mileage at the end of the usage contract or the assumed usage period for the vehicle, and calculate the residual value from the expected sale amount and the planned sale amount set at the time of the usage contract. A residual value profit and loss analysis system that outputs profit and loss. 52. Manufacturer name, model grade, article type,
Before resale using data on resale items such as use contract year, use contract expiration year, use contract period, sales price, sales amount after use contract expiration, actual use status at resale, assessment at resale, etc. A residual value profit / loss analysis system for predicting the residual value gain / loss of an article, comprising:
Calculate the expected sales amount at the time of resale from the monthly usage status, the expected usage status at the end of the usage contract, or the expected usage period, and output the residual value profit and loss from the expected sales amount and the planned sales amount set at the time of the usage contract. Characteristic residual value profit and loss analysis system. 53. The method according to claim 53, wherein the expected sale amount is calculated by multiplying a relative value set by predicting a resale market price at the time of contract expiration based on a current or past resale market price. 53. The residual value profit / loss analysis system according to claim 51 or 52. 54. A storage medium storing data used in the residual value profit / loss analysis system according to claim 51. 55. Manufacturer name, vehicle type name, vehicle application, vehicle shape, vehicle type grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, common name model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, emission regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires An asset valuation system that predicts the market value of a vehicle during a period of use contract at any time using data on resold vehicles, such as the sale price of the vehicle, mileage at resale, and assessment at resale. Calculate the new car price, average monthly mileage, estimated mileage at the end of the usage contract, estimated mileage at any time, or estimated sales amount at any time from the assumed use period, regarding the vehicle during the period, An asset valuation system for outputting a market price at an arbitrary point in time of a vehicle during a use contract period from a sale price. 56. Manufacturer name, model grade, article type,
Use contract period using data on resale items such as use contract year, use contract expiration year, use contract period, sales price, sales amount after use contract expiration, actual use status at resale, assessment at resale, etc. An asset valuation system that predicts the market value of goods in stock at any point in time, at any time from the selling price, monthly usage status, assumed usage status at the end of the usage contract, or assumed usage period for the goods during the usage contract period The asset evaluation system calculates the expected sale price of the article and outputs the market price at any time of the article during the use contract period from the expected sale price. 57. The expected sale price is calculated by multiplying a relative value set by predicting a resale market price at an arbitrary time based on a current or past resale market price. 57. The asset evaluation system according to claim 55 or 56. 58. A storage medium storing data used in the asset evaluation system according to any one of claims 55 to 57. 59. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, approved model, model designation number, classification number, mission, drive system, displacement, number of doors, common name model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, emission regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A residual value setting system that sets the residual value of a newly contracted vehicle using data on the resold vehicles, such as the sale price of the vehicle, the mileage at the time of resale, the assessment at the time of resale, etc. Calculating an expected sale amount for the new contract vehicle from the price, the average mileage per month, the assumed mileage at the expiration of the use contract or the assumed use period, and outputting a residual value for the new contract vehicle from the expected sale amount. Residual value setting system. 60. Manufacturer name, model grade, article type,
New contract goods using data on resold goods such as use contract year, use contract expiration year, use contract period, sales price, sale amount after expiration of use contract, actual use status at resale, assessment at resale, etc. Is a residual value setting system that calculates the expected sale price for new contracted goods from the selling price, monthly usage status, expected usage status at the end of the usage contract, or the expected usage period for the goods during the usage contract period. And
A residual value setting system for outputting a residual value relating to a new contract article from the expected sale price. 61. The method according to claim 61, wherein the expected sale price is calculated by multiplying a relative value set by predicting a resale market price at the time of contract expiration based on a current or past resale market price. 61. The residual value setting system according to claim 59 or 60. 62. Manufacturer name, vehicle type name, vehicle use, vehicle shape, vehicle type grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, common name model, capacity and load capacity, Engine type, number of engine cylinders,
Engine mechanism, tire size, turbocharger, roof shape, emission regulations, body size, automobile tax classification, weight tax, insurance class, use contract year, use contract expiration year, use contract period, new car price, after use contract expires A residual value setting system for setting a residual value for a new model using data on a resold vehicle, such as a sale price, a mileage at the time of resale, an evaluation at the time of resale, etc. And the vehicle type application and new vehicle price of the existing vehicle are compared to select the closest vehicle type or popularity index, and the residual value of the new vehicle type is output based on the selected vehicle type or popularity index. Residual value setting system. 63. A storage medium storing data used in the residual value setting system according to claim 59. 64. Before resale using data on vehicle specifications such as manufacturer name, years of fall, vehicle type, vehicle shape, displacement, fuel, grade, mission, and drive system, and the sales amount for each resold vehicle Vehicle sales, residual value,
Or a vehicle resale price analysis system that predicts information about the residual value rate, and reselects a resale vehicle having a standard deviation within a predetermined range from an average value of the sales amount of the resale vehicle selected by the vehicle specifications. A vehicle resale price analysis system, wherein the average value of the resale value of the reselected resold vehicles is set as a standard sale price, and the standard sales amount is set as an expected sale price.