KR20220035811A - Investment Valuation System on apartment based on indexation of apartment - Google Patents

Abstract

An apartment investment value evaluation system through apartment indexation is introduced.
To this end, the present invention is an apartment investment value evaluation system through apartment indexing, which includes a smartphone 200 with a separate application installed or a display unit 300 with a separate program stored thereon, and the smartphone 200 or a display unit ( 300) and a central server 100 that is linked in real time, and when the application of the smartphone 200 is executed or the program is executed, the display unit 300 includes a search window through which the user can search for an apartment of interest. However,
When searching for an apartment of interest to the user, the investment value and actual residence value of the apartment are tabulated on one side of the display unit 300, and the actual transaction price of the apartment and the appraised price through indexing of the apartment and the apartment are displayed on one side of the display unit 300. It is characterized by displaying an image of whether investment is recommended, and the central server 100 displays the actual transaction price, publicly announced price, regional characteristics, infrastructure, complex size, area composition, degree of deterioration, and brand for the apartment in question. Each index for the apartment in which the user is interested is pre-stored, and the weight for the corresponding index is also pre-stored, so that the apartment N index is calculated considering the index and the weight, and the central server (100) ), the evaluated price through indexing of the apartment is calculated through [Equation 1] below and displayed on the display unit 300 when the application of the smartphone 200 is executed or the program is executed.
[Equation 1]
Evaluation price = p1 + ( aptn_idx x wp x level_idx / 100)x( aw x pw)
(p1: The publicly announced price in January of the year in which the apartment was searched,
aptn_idx: Apartment N Index at the time of searching for the relevant apartment,
wp: Weighted price already stored in the central server corresponding to the Apartment N Index,
level_idx : [(Transaction Price Index x 50) + (Regional Characteristics Index x 30) + (Infrastructure Index x 20)] /100,
aw: exclusive area weight previously stored in the central server for the apartment,
pw: value already stored in the central server according to the regional characteristic index of the complex to which the apartment belongs)

Description

Apartment investment valuation system through apartment indexation {Investment Valuation System on apartment based on indexation of apartment}

The present invention relates to an apartment investment value evaluation system through apartment indexation.

Various analysis techniques are being proposed to select real estate products with promising future profits.

Conventionally, parametric models such as linear regression models have been used to estimate or determine real estate prices. However, the parametric model has many strict assumptions such as normality of data, independence of explanatory variables, and linearity of the price function, which limits the reliability of the estimated price. Real estate prices have various non-linear factors that cannot be determined by parametric models alone, but existing models cannot reflect these. For example, as the land area increases, transaction costs tend to decrease, but the parametric model could not reflect this characteristic due to the assumption of linearity. In addition, real estate prices vary greatly depending on their physical location, which is called spatial dependence.

In the past, the characteristics of real estate price formation, that is, elements of physical location or distance, could not be reflected, so the accuracy in estimating real estate prices was inevitably low.

Likewise, a system that predicts the future value of real estate requires an evaluation system to verify its effectiveness, but there are not many investment recommendation systems that include such an evaluation system.

Accordingly, the purpose of the present invention is to provide a system for evaluating the investment value of properties for sale by analyzing changes in the causal index that determines apartment prices.

In the past, the reality was that there was a lack of objective judgment on whether the seller's quotation-centered service was provided and whether the quotation was appropriate.

Accordingly, the purpose is to provide an evaluation service that analyzes the asking price rather than the physical characteristics of the property, and the purpose is to provide a system to evaluate the investment holding and holding value of the apartment regardless of external factors.

KR 10-2018-0094987 (published on 2020. 03. 06)

The purpose of the present invention is to provide data that evaluates and comparatively analyzes apartment asking prices, and provides a report on objective investment value evaluation using absolute and relative indices.

An apartment investment value evaluation system through apartment indexation is introduced.

To this end, the present invention is an apartment investment value evaluation system through apartment indexing, which includes a smartphone 200 with a separate application installed or a display unit 300 with a separate program stored thereon, and the smartphone 200 or a display unit ( 300) and a central server 100 that is linked in real time, and when the application of the smartphone 200 is executed or the program is executed, the display unit 300 includes a search window through which the user can search for an apartment of interest. However,

When searching for an apartment of interest to the user, the investment value and actual residence value of the apartment are tabulated on one side of the display unit 300, and the actual transaction price of the apartment and the appraised price through indexing of the apartment and the apartment are displayed on one side of the display unit 300. It is characterized by displaying an image of whether investment is recommended, and the central server 100 displays the actual transaction price, publicly announced price, regional characteristics, infrastructure, complex size, area composition, degree of deterioration, and brand for the apartment in question. Each index for the apartment in which the user is interested is pre-stored, and the weight for the corresponding index is also pre-stored, so that the apartment N index is calculated considering the index and the weight, and the central server (100) ), the evaluated price through indexing of the apartment is calculated through [Equation 1] below and displayed on the display unit 300 when the application of the smartphone 200 is executed or the program is executed.

[Equation 1]

Evaluation price = p1 + ( aptn_idx x wp x level_idx / 100)x( aw x pw)

(p1: The publicly announced price in January of the year in which the apartment was searched,

aptn_idx: Apartment N Index at the time of searching for the relevant apartment,

wp: Weighted price already stored in the central server corresponding to the Apartment N Index,

level_idx : [(Transaction Price Index x 50) + (Regional Characteristics Index x 30) + (Infrastructure Index x 20)] /100,

aw: exclusive area weight previously stored in the central server for the apartment,

pw: value already stored in the central server according to the regional characteristic index of the complex to which the apartment belongs)

According to the present invention configured as described above, there is an advantage in that investment risks due to increased uncertainty can be minimized and objective investment information can be provided.

1 is a schematic configuration diagram of the present invention;
Figure 2 shows an existing apartment information providing app or system,
3 is a screen of the display unit visible when the present invention is implemented;
Figure 4 is a screen that informs the user about the profit when investing in the apartment when searching for an apartment in which the user is interested;
Figure 5 is a screen that provides information including actual residential value and investment value for the apartment in question;
Figure 6a is a table showing the absolute index and relative index that can be used when calculating the apartment N index.
Figure 6b is an example of the Apartment N Index,
7 to 24 are screens showing information that can be provided to the user when running the smartphone or display unit, which is a component of the present invention.

Hereinafter, with reference to the attached drawings, a preferred embodiment of the present inventor's apartment investment value evaluation system through indexing of apartments will be described.

1 is a schematic configuration diagram of the present invention.

The present invention broadly includes a smartphone 200 with a separate application installed or a display unit 300 in which a separate program is stored, and a central server 100 that is linked in real time with the smartphone 200 or the display unit 300. Includes.

The present invention is a new concept model that first objectively classifies the causal index that determines the price of an apartment, scores each, and analyzes changes in each causal index in real time to determine the investment value of the apartment. .

Meanwhile, Figure 2 shows an existing apartment information providing app or system.

As shown, it has the disadvantage of not being able to provide a service centered on the seller's quotation or provide analysis or analysis results on whether the seller's quotation is appropriate.

Accordingly, as will be described in detail below, the present invention analyzes the asking price rather than the physical characteristics of the property, that is, the apartment, and ensures the validity and objectivity of the asking price to provide analysis results for the apartment and the investment value of the apartment. It is about a new system that is provided.

To this end, the present invention evaluates the investment value of an apartment by indexing the evaluation result that provides the appraised price of the apartment based on an absolute index that scores the absolute value of the apartment and a relative index that scores the relative value of the apartment.

Specifically, the actual transaction price (transaction price), publicly announced price, regional characteristics, infrastructure, complex size, area composition, age, and brand for each apartment of interest to the user are already stored. , the weight for the corresponding index is also previously stored, so the Apartment N index is calculated considering the index and the weight, and based on this Apartment N index, the evaluation price proposed by the present invention is provided to the user, as well as the central server ( The adequacy of the investment value for the apartment in question is also provided to the user through a separate mathematical equation previously stored in 100).

At this time, it includes a smartphone 200 with a separate application installed or a display unit 300 in which a separate program is stored, and a central server 100 that is linked in real time with the smartphone 200 or the display unit 300. When an application or program is executed on the phone 200, the display unit 300 includes a search window through which the user can search for an apartment of interest.

It is obvious that the display unit 300 can be applied to any device that can execute the program, including a general computer, in the present invention.

In other words, as shown in Figure 3, a window is created where the user can search for an apartment of interest, and when the apartment name is entered into the window, a shape similar to a traffic light is created on one side of the window, which allows the user to invest in the apartment. Then you will be able to know the level of risk.

In addition, as shown in Figure 4, not only are the prices of the corresponding apartments displayed in color on the map, but also information on investment recommendations, cautious approaches, and purchase holds is provided in real time.

Meanwhile, when a user searches for an apartment of interest, the investment value and actual residence value of the apartment in question are tabulated on one side of the display unit 300.

As shown in Figure 5, the closer it is displayed to the upper right, the relatively higher the investment value, and the higher the value is, the higher the actual residence value is.

The actual residential value other than the investment value is formed between -1 and 1, and this part is explained later.

In addition, the latest actual transaction price for the apartment in question is displayed, as well as the appraised price, which is the core of the present invention.

This evaluation price provides objective information on whether or not to invest in the apartment.

In other words, the actual transaction price of the apartment and the assessed price based on the absolute index and relative index are displayed, and at the same time, an image of whether investment in the apartment is recommended is displayed.

Below, the actual transaction price, publicly announced price, regional characteristics, infrastructure, complex size, area composition, deterioration, and brand of the apartment, which can be said to be the core of the present invention, are indexes for each apartment of interest to the user. It is already stored, and the weight for the corresponding index is also already stored, so the calculation of the Apartment N index considering the index and weight is explained with reference to [Table 1] below and FIG. 6b as follows.

Component

data source
renewal cycle
explanation
A. Transaction price index

Actual transaction price

Once a month

A rating score of 1 to 100 is given to complexes across the country based on the actual transaction price per exclusive area in the base month.

B. Published price index

Published price

Once a year

Ratings of complexes across the country from 1 to 100 are based on the price by exclusive area of the apartment price, which is announced every year and serves as a tax base.

C. Regional characteristics index

Actual transaction price, facilities

Once a month

The score calculated from the average transaction price of the town, township, and dong (e.g. Daechi-dong) to which the complex belongs
A rating of 1 to 100 is given by combining scores for the presence or absence of preferred facilities (3 types), the presence or absence of facilities to be avoided (4 types), and the number of elementary schools, middle schools, high schools, and childcare facilities.

D. Infrastructure Index

Actual transaction price, facilities

Once a month

The score calculated from the average transaction price of the city, county, and district to which the complex belongs (e.g., Gangnam-gu, Bundang-gu, Seongnam-si, Andong-si, Gyeongsangbuk-do)
If a first-class general hospital, large store, etc. are right next to the complex, it causes traffic congestion and causes inconvenience in life as the floating population seems to be concentrated, but it is calculated from the presence or absence of facilities that exist in close proximity, such as in the same city, county, and district, and can be easily used when needed. Give a rating from 1 to 100 by combining scores

E. Complex size index


Complex standard information

First time

Scores given at intervals of 10 from 20 to 100 based on the number of households in the complex (e.g., 100 for over 2,000 households)

F. Area composition index

Complex standard information

First time

The score is given based on the diversity of area composition of the complex, and it is divided into five types (ultra-small, small, medium-sized, medium-large, and large) based on the exclusive area.
Scores given at intervals of 20 from 40 to 100 depending on the number of area types (e.g. 2 or less, 40)

G. Aging Index

Complex standard information

Once a year

Points awarded based on the period (in years) that has elapsed at the time of index calculation based on the year the complex was approved for use

H.Brand Index

Complex standard information

First time

Scores are given at intervals of 10 from 40 to 100 depending on the constructor's awareness (e.g. Daewoo 100)

The apartment N index, which is updated and previously stored in the central server 100 of the present invention, is characterized in that it is calculated by [Equation 2] below.

[Equation 2]

Apartment N Index = (Transaction price index )/100

As an example, when explaining the transaction price index based on the actual transaction price, the central server 100 updates the transaction price index reflecting the actual transaction price once a month.

At this time, a rating score of 1 to 100 is given to complexes across the country based on the price by exclusive area of the actual transaction price in the reference month, and each rating score is already stored in the central server (100).

For example, in the case of 'Eunma Apartment, Daechi-dong, Gangnam-gu', this transaction price index is already stored in the central server (100) as '100'.

Likewise, the publicly announced price index is already stored in the central server (100) on a once-a-year basis, and nationwide complexes are assigned a rating of 1 to 100 based on the price by exclusive area of the apartment price, which is announced every year and becomes the tax base. .

In the case of 'Eunma Apartment, Daechi-dong, Gangnam-gu', this publicly announced price index is already stored in the central server (100) as '99'.

Figure 6b is an embodiment of the present invention, showing that the Apartment N Index was calculated when the user entered 'Eunma Apartment, Daechi-dong, Gangnam-gu' in the search box, and the specific formula is shown in [Table 2] below. .

Next, in the central server 100, the assessed price through indexing of the apartment is calculated through [Equation 1] below and displayed on the display unit 300 when the application on the smartphone 200 is executed or the program is executed. It is characterized by being

[Equation 1]

Evaluation price = p1 + ( aptn_idx x wp x level_idx / 100)x( aw x pw)

(p1: The publicly announced price in January of the year in which the apartment was searched,

aptn_idx: Apartment N Index at the time of searching for the relevant apartment,

wp: Corresponds to the Apartment N Index and the weighted price already stored in the central server (100),

level_idx : [(Transaction Price Index x 50) + (Regional Characteristics Index x 30) + (Infrastructure Index x 20)] /100,

aw: exclusive area weight previously stored in the central server (100) for the apartment,

pw: value already stored in the central server (100) according to the regional characteristic index of the complex to which the apartment belongs)

At this time, wp is the weighted price previously stored in the central server 100 corresponding to the Apartment N Index. (The higher the Apartment N Index, the higher the weighted price is set, and this weighted price is also updated on the central server 100 every year. do.)

As an example, the weighted prices for each Apartment Yen Index are shown in the table below.

As previously explained, the higher the apartment yen index, the higher the weighted price is set, and this weighted price is also updated annually on the central server 100.

In other words, the weight applied according to changes in the actual trading price or environment is a variable value, and these values are continuously updated and stored as changed in the central server 100.

Meanwhile, the level_idx factor is included in Equation 1, which is a factor that can reflect the standard of living of the complex where the apartment selected by the user belongs, and is specifically defined as the equation below.

[(Transaction Price Index x 50) + (Regional Characteristics Index x 30) + (Infrastructure Index x 20)] /100

A high transaction price index means that the living and school districts are generally at a high level compared to other regions, and a high regional characteristic index means that there are many preferred facilities and few avoided facilities in the complex to which the apartment belongs. , the infrastructure index also means that there are hospitals, large stores, etc. in the complex to which the apartment belongs.

Next, aw is the exclusive area weight previously stored in the central server 100 for the corresponding apartment, and is explained in detail as follows.

This is a value already stored in the central server 100 according to the exclusive area of the apartment selected by the user. The values are 0.4 for ultra-small, 0.7 for small, 1.0 for medium-sized, 1.3 for medium-large, and 1.6 for large.

For reference, the table below provides a classification table for each exclusive area for ultra-small, small, medium-sized, etc. described above.

The larger the exclusive area, the higher the constant value is multiplied when calculating the appraised price of the apartment.

Next, pw is a value already stored in the central server 100 according to the regional characteristic index of the complex to which the apartment belongs. 1 or 0.9 is pre-stored in the central server 100, and in the case of 0.9, it is the value of the complex. If the regional characteristics index is 10 or more higher than the transaction price index, a weight of 0.9 is applied.

This constant is a constant that takes into account complexes in the area that are old or have inconveniences in living.

Meanwhile, p1 is the publicly announced price in January of the year in which the apartment is searched, and to ensure objectivity, the central server 100 already stores the publicly announced price of the Korea Appraisal Board, which serves as the tax base, and this publicly announced price is used in the present invention. Applies to.

An embodiment of the present invention to which the above formula is applied is described based on [Table 5] below.

The calculation according to Table 5 is explained in detail as follows.

p1 is the publicly announced price, which is a value already stored in the central server (100), and the average value of the small and medium-sized publicly announced price of 'Eunma Apartment in Daechi-dong, Gangnam-gu' as of January 2020 was calculated as 1,452,592,728 won.

Next, the Apartment N Index, aptn_idx, was calculated to be 96 as of August 2020, as previously explained.

Next, as previously explained, wp is calculated as 8,800,000 won as the weighted price per index of the Apartment N Index, and this value is also previously stored in the central server (100).

Next, the previously described level_idx is calculated, which is calculated as [(Transaction Price Index * 50) + (Regional Characteristics Index * 30) + (Infrastructure Index * 20)] / 100, and the specific figure is [(100 * 50) + (99*30) + (100 *20)] /100 = 99.7.

Next, as previously described, aw corrects wp according to the area with an exclusive area weight, and the weight of 1.0 is applied to Eunma Apartment, which is a small to medium-sized apartment in this example.

Next, pw is applied at 1.0 or 0.9. If the regional characteristic index of the complex is 1.0 or more higher than the transaction price index, a weight of 0.9 is applied. In the case of Eunma Apartment, 1.0 is applied because there is no difference between the regional characteristic index and the transaction price index. Applies.

The specific calculation formula using the above values is as follows.

1452592728 + (96 * 8,800,000 * 99.7 / 100 * 1.0 * 1.0) = 2,297,392,728

In other words, as shown in Figure 5, in the case of Eunma Apartment in Daechi-dong, Gangnam-gu, 2.222 billion won was recently traded as an actual transaction, but the appraised price of the apartment calculated by the present invention is 2.297 billion won, so the apartment It is confirmed that an investment return of approximately 77 million won is expected upon purchase.

Next, when explaining the investment value shown in FIG. 5, the investment value is characterized by being calculated by [Equation 3] below.

[Equation 3]

Investment value = (x1 + x2 + x3 + x4 )/4

(X1 = a value between -1 and +1 considering the average transaction price of the relevant year at the time of search for the relevant apartment,

X2 = The value between -1 and 1 considering the average transaction price of the month at the time of the search point of the apartment,

X3 = If the number of transactions is relatively high at the time of search, the value between -1 and 1 considering the actual average transaction price,

X4 = Complex size index/50 - 1

)

X1 is the evaluation amount that determines whether the apartment value is continuously maintained.

As the years go by, the more the price increases, the closer it is to 1, and if it falls, the closer it gets to -1.

As an example, the average transaction price by year is already stored in the central server 100, and if the average transaction price by year increases by more than 30%, it is set to 1, and if it falls by more than 30%, it can be set to -1. .

This value is also stored in real time on the central server (100) as the average transaction price for the relevant transaction year for the apartment, and if it is determined that the price increase is clear within the central server (100), it is a value close to 1, and the price is falling. If it is judged to be clear, it is calculated as a value close to -1.

The If so, it will be a value close to -1.

This also stores the monthly average transaction price. For example, if the average transaction price this month increases by more than 30% compared to the previous month, it can be set to 1, and if it falls by more than 30%, it can be set to -1.

X3 is an evaluation amount based on analysis of the correlation between transaction volume and transaction price, and is stored in real time on the central server (100) between -1 and 1 depending on whether the price rose or fell when the number of transactions was high.

For example, in the central server 100, if the number of apartments actually traded increases by 30% compared to the previous year, the number of transactions is assumed to be high, and if the actual traded price increases by more than 30% compared to the previous year, it is set to 1, and 30 If it falls by more than %, it can be set at -1.

X4 is an evaluation amount that reflects that the larger the complex, the higher the investment value.

Meanwhile, the actual residence value is characterized as the average value of [Equation 4] below.

[Equation 4]

(Number of hazardous facilities, including entertainment facilities, factories, waste facilities, and oil-related facilities, within a set distance centered on the point where the relevant apartment is located) x (-1) + (Number of preferred facilities, including hospitals, shopping malls, and cultural facilities) x ( 1) + (Number of educational facilities including elementary schools, middle schools, high schools, and childcare facilities) Weighted by -1, 0, and +1, respectively, depending on whether the apartment is under 25 years old or over 25 years old) weighted to +1, 0, and -1 respectively)

In other words, it can be explained in Table 6 below.

The image regarding whether the investment is recommended is characterized by displaying to the user one of the following: withhold purchase, cautious approach, and investment recommendation based on [Equation 5] below.

[Equation 5]

[(Investment value x 60) + (Actual residential value x 40)]/100

(As a result of [Equation 5] above, if it is less than -0.4, a hold purchase is indicated, if it is between -0.4 and 0.4, a cautious approach is indicated, and if it is 0.4 or more, an investment recommendation is indicated)

The X-axis of the graph shown in Figure 5 is placed between investment value (-1.0 to 1.0), and the Y-axis of the graph is placed between actual residence value (-1.0 to 1.0).

As shown in Table 7 below, the pending purchase, cautious approach, and investment recommendations indicated by traffic lights are calculated through a weighted average of 60% of the investment value and 40% of the actual residence value (weights are adjusted by year).

(( Investment value * 60) + (Actual residential value * 40)) / 100 = -1.0 ~ 1.0

Afterwards, the calculated value is divided into sections and each section is judged as a hold-off purchase, cautious approach, or investment recommendation.

In the central server 100, an absolute index with scores set for the actual transaction price, turnover rate, and publicly announced price for the apartment in question is stored in real time.

More preferably, this absolute index further includes scoring set for the year of completion of the apartment in question, the size of the complex, the brand of the apartment in question, and transportation convenience.

In addition, the relative index with the score set for the comparison of the actual transaction price and inflation rate for the apartment in question is stored in real time.

More preferably, this relative index further includes a scoring set for similar complexes nearby the apartment in question.

Figure 6a shows a table of these absolute and relative indices.

The previously described Apartment N Index based on these absolute and relative indices is transmitted in real time when the smartphone 200 or the display unit 300 is running, and the appropriateness of investment in the corresponding apartment is determined based on the Apartment N Index again. It is provided to the user.

As shown in FIG. 6B, when the user searches for an apartment of interest after executing the application or display unit 300 of the smartphone 200, the transaction price, published price, regional characteristics, infrastructure, complex size, and area composition for the apartment in question are displayed. A detailed evaluation information window is formed with each score for , age, and brand, and the apartment index score is displayed accordingly.

Meanwhile, as shown in FIG. 7, when the user searches for an apartment of interest after executing the application or the display unit 300 of the smartphone 200, a window regarding the accessibility of major points for the apartment is formed.

It is clear that this information is taken into consideration when investing in the apartment.

Meanwhile, as shown in FIGS. 8 and 9, when the user searches for an apartment of interest after executing the application or display unit 300 of the smartphone 200, the actual transaction trend of the apartment by year is graphed, and the corresponding graph It is characterized in that the starting actual transaction amount, closing actual transaction amount, minimum actual transaction amount, maximum actual transaction amount, and average actual transaction amount of the actual transaction amount by year are displayed in a chart.

As shown in Figures 10 and 11, when the user searches for an apartment of interest after executing the application or display unit 300 of the smartphone 200, the average transaction price of the apartment by year and the apartment index are tabulated. It is characterized by being displayed.

As shown in FIGS. 12 and 13, when searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200, the change in sunlight access to the apartment according to the date and time zone desired by the user It is characterized by being displayed.

As shown in Figures 14 and 15, when the user searches for an apartment of interest after executing the application or display unit 300 of the smartphone 200, a graph of the actual transaction price increase rate by year and the consumer price increase rate of the corresponding apartment are simultaneously displayed. It is characterized by displaying the investment profit or investment loss for the apartment in question.

As shown in Figures 16 and 17, when the user searches for an apartment of interest after executing the application or display unit 300 of the smartphone 200, a comparison graph of price changes for the apartment is displayed. .

As shown in Figures 18 and 19, when searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200, the annual turnover rate, asking price increase rate, and number of transactions are displayed for the apartment in question. It is characterized by being

As shown in FIG. 20, when the user searches for an apartment of interest after executing the application or display unit 300 of the smartphone 200, convenience information about the number of subways and schools per distance set around the apartment is provided. It is characterized by being

As shown in FIG. 21, when searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200, the address, number of units, total floor area of the building register, corridor type, heating type, and developer for the apartment in question are searched. and apartment standard information on the date of approval for use is provided.

As shown in FIGS. 22 and 23, when searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200, the actual transaction price by year, the publicly announced price, and the publicly announced price compared to the actual transaction price for the apartment in question are displayed. An apartment investment value evaluation system through indexation of apartments, characterized in that a ratio is displayed.

As shown in FIG. 24, when the user searches for an apartment of interest after executing the application or the display unit 300 of the smartphone 200, a list of similar complexes for the corresponding apartment is displayed.

100: central server 200: smartphone
300: Display unit

Claims (8)

In the apartment investment value evaluation system through apartment indexation,
It includes a smartphone 200 with a separate application installed or a display unit 300 in which a separate program is stored, and a central server 100 that is linked in real time with the smartphone 200 or the display unit 300, and the smart phone 200 When running an application on the phone 200 or executing the program, the display unit 300 includes a search box for searching for an apartment of interest to the user,
When searching for an apartment of interest to the user, the investment value and actual residence value of the apartment are tabulated on one side of the display unit 300,
It is characterized by displaying an image of the actual transaction price of the apartment, the appraised price through indexing of the apartment, and whether investment in the apartment is recommended.
The central server 100 contains the actual transaction price (transaction price), publicly announced price, regional characteristics, infrastructure, complex size, area composition, deterioration, and brand for each index for the apartment of interest to the user. It is pre-stored, and the weight for the index is also pre-stored, so that the Apartment N Index is calculated considering the index and the weight.
In the central server 100, the assessed price through indexing of the apartment is calculated through [Equation 1] below and displayed on the display unit 300 when the application of the smartphone 200 is executed or the program is executed. An apartment investment value evaluation system through apartment indexation, characterized by:

[Equation 1]
Evaluation price = p1 + ( aptn_idx x wp x level_idx / 100)x( aw x pw)
(p1: The publicly announced price in January of the year in which the apartment was searched,
aptn_idx: Apartment N Index at the time of searching for the relevant apartment,
wp: Weighted price already stored in the central server corresponding to the Apartment N Index,
level_idx : [(Transaction Price Index x 50) + (Regional Characteristics Index x 30) + (Infrastructure Index x 20)] /100,
aw: exclusive area weight previously stored in the central server for the apartment,
pw: value already stored in the central server according to the regional characteristic index of the complex to which the apartment belongs) In claim 1,
The Apartment N Index is an apartment investment value evaluation system through apartment indexation, characterized in that calculated by [Equation 2] below.

[Equation 2]
Apartment N Index = (Transaction price index )/100 In claim 2,
The investment value is characterized by being calculated using Equation 3 below,

[Equation 3]
Investment value = (x1 + x2 + x3 + x4) / 4
(X1 = a value between -1 and +1 considering the average transaction price of the year at the time of search for the apartment,
X2 = The value between -1 and 1 considering the average transaction price of the month at the time of the search point of the apartment,
X3 = If the number of transactions is relatively high at the time of search, the value between -1 and 1 considering the actual average transaction price,
X4 = Complex size index/50 - 1
)

The actual residential value is characterized in that it is the average value of [Equation 4] below,

[Equation 4]
(Number of hazardous facilities, including entertainment facilities, factories, waste facilities, and oil-related facilities, within a set distance centered on the point where the relevant apartment is located) x (-1) + (Number of preferred facilities, including hospitals, shopping malls, and cultural facilities) x ( 1) + (Number of educational facilities including elementary schools, middle schools, high schools, and childcare facilities) Weighted by -1, 0, and +1, respectively, depending on whether the apartment is under 25 years old or over 25 years old) weighted to +1, 0, and -1 respectively)

The image of whether the investment is recommended is an evaluation of the investment value of an apartment through indexing of the apartment, characterized by displaying to the user one of the following: withhold purchase, cautious approach, and investment recommendation based on [Equation 5] below. system.

[Equation 5]
[(Investment value x 60) + (Actual residential value x 40)]/100

(As a result of [Equation 5] above, if it is less than -0.4, a hold purchase is indicated, if it is between -0.4 and 0.4, a cautious approach is indicated, and if it is 0.4 or more, an investment recommendation is indicated) In claim 3,
When searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200,
A detailed evaluation information window is created with each score for the transaction price, publicly announced price, regional characteristics, infrastructure, complex size, area composition, deterioration, and brand for the apartment in question, and the apartment index score is displayed accordingly. and
An apartment investment value evaluation system through indexation of apartments, characterized by the formation of a window on the accessibility of major bases for the apartment in question. In claim 3 or claim 4,
When searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200,
The yearly actual transaction trend of the apartment in question is graphed, and the graph displays the starting actual transaction amount, closing actual transaction amount, minimum actual transaction amount, maximum actual transaction amount, and average actual transaction amount of the actual transaction amount by year in a tabular form.
An apartment investment value evaluation system through apartment indexation, characterized in that the annual average transaction price of the apartment and the apartment index are displayed in a diagram. In claim 5,
When searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200,
It is characterized by displaying the change in sunlight for the apartment according to the date and time zone desired by the user,
An apartment investment value evaluation system through the indexation of apartments, characterized in that the actual transaction price increase rate graph and the consumer price increase rate of the apartment by year are simultaneously displayed to indicate the investment profit or investment loss for the apartment. In claim 5,
When searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200,
It is characterized by displaying a comparison graph of price changes for the apartment in question,
An apartment investment value evaluation system through apartment indexation, characterized by displaying the annual turnover rate, asking price increase rate, and number of transactions for the relevant apartment. In claim 5,
When searching for an apartment of interest to the user after executing the application or display unit 300 of the smartphone 200,
It is characterized by displaying the actual transaction price, publicly announced price, and the ratio of the publicly announced price to the actual transaction price by year for the apartment in question,
An apartment investment value evaluation system through apartment indexing, characterized by displaying a list of similar complexes for the apartment in question.