JP6270589B2 - Revenue evaluation apparatus, method and program, and vacancy rate calculation apparatus, method and program - Google Patents

Description

  The present invention relates to a profit evaluation apparatus, method and program for evaluating the profit of rental real estate, and a vacancy rate calculation apparatus, method and program.

  Although the income of a real estate rental property is calculated by (income-expense) / yield, it is not easy to calculate income, expense and yield for each property individually (Patent Documents 1 to 5). There are two types of income: rent income and parking lot income, and it is necessary to take into account vacancy loss (so-called non-operating loss). Expenses include maintenance costs, utility costs, repair costs, PM costs, and the like.

  In general, revenue depends on the structure of the rental property (wooden, steel frame, reinforcing bar, etc.), age, station distance, floor plan, etc., while expenses depend on the structure, age, floor plan, etc. of the rental property. In either case, it is not easy to estimate quantitatively.

  Although a quantitative evaluation value can be obtained by a survey / appraisal by a real estate appraiser, it is an individual response and is not suitable for routine processing such as determination of a loan amount.

  Patent Document 5 describes a future price prediction apparatus and method for calculating a cash flow from income and expenditure to the arrival of a useful life and predicting a future price by discounting the present value as a support system for determining a real estate loan amount. ing. The rent that makes up the revenue is determined by applying the component coefficients to the rent model (paragraphs 0058-0061).

JP 2004070535 A JP 2004-171211 A JP 2005-251031 A JP 2011-048597 A JP 2013-120503 A

  Revenue evaluation is mainly for determining the loan amount, and the conventional revenue evaluation system does not refer to realistic values such as rent, vacancy rate, and expenses, but to estimate the revenue of individual rental properties. It was insufficient.

  In other words, in order to evaluate profits, it is necessary to collect the rental housing cases around the target and assess the vacancy rate, expenses, and return on profits as accurately as possible. In addition to this, it requires high know-how for the assessment itself. In particular, it is difficult to estimate realistic values regarding the vacancy rate, the cost, and the profit return yield, which makes computerized or computerized automatic profit evaluation difficult.

  In order to quantitatively evaluate the profits of rental properties, it is necessary to quantitatively calculate the vacancy rate (or occupancy rate) with higher accuracy. However, in the Japanese rental housing market, there is no timely data on the total number of rental housing (stock) and total vacancies for monthly recruitment, so the vacancy rate cannot be calculated in a timely manner. By referring to the residential land statistics survey conducted once every five years by the Ministry of Internal Affairs and Communications, we can only calculate the macro vacancy rate in a wide area once every five years.

  Therefore, the conventional revenue evaluation system calculates revenue assuming the vacancy rate virtually or approximately, and the resulting revenue is not satisfactory in terms of accuracy.

  It is an object of the present invention to present a profit evaluation apparatus, method and program, and a vacancy rate calculation apparatus, method and program for solving such problems.

The revenue evaluation device according to the present invention is a revenue evaluation device for evaluating the revenue of rental property, and a property for inputting property information including the structure of the property to be evaluated and a designation means for designating the location of the property to be evaluated Information input means, access determination means for determining access conditions including the straight line distance from the nearest point to the location and the required time, and rental housing recruitment for a predetermined period extending in the past including the location of the property to be evaluated Rent distribution data showing distribution of rent space and structure from data, vacancy rate distribution data showing distribution of space and structure of vacancy rate, and turnover distribution showing distribution of space and structure of lease contract turnover rate Distribution analysis means for generating data, the property information and the access conditions of the property to be evaluated from the rent distribution data and the vacancy rate distribution data Rent and vacancy rate calculation means for calculating the rent and vacancy rate of the property subject to evaluation by extracting corresponding data, and the rent and vacancy of the property subject to evaluation calculated by the rent / vacancy rate calculation means Operating revenue calculating means for calculating the operating revenue of the property to be evaluated according to the rate, and operating expenditure calculating means for calculating the operating expenditure of the property to be evaluated by extracting data corresponding to the property information from the turnover distribution data And yield setting means for setting the yield of the evaluation target property, and a revenue calculation means for calculating the profit of the evaluation target property according to the operation revenue, the operation expenditure and the yield of the evaluation target property, The distribution analysis means includes a dividing means for dividing the rental housing recruitment data into monthly recruitment data, a recruitment number extracting means for extracting the monthly recruitment number from the monthly recruitment data, The monthly recruitment building is extracted from the monthly recruitment data, multiplied by the average number of units by rank, and the total number of units is calculated by taking the sum, and the number of monthly recruitment units is divided by the total number of units. A division means and an averaging means for calculating a moving average of a plurality of monthly results of division by the division means, and for each of a plurality of areas that divide a wide area including the location of the evaluation target property The vacancy rate distribution data is generated for each structural section.

The revenue evaluation method according to the present invention is a revenue evaluation method for evaluating the revenue of rental real estate using a computer, the step of inputting the location of the property to be evaluated to the computer, and the property of the property to be evaluated to the computer, A property information input step for inputting property information including a structure, an access determination step for the computer to determine an access condition including a linear distance from the nearest point to the location and a required time, and the computer to be evaluated Rent distribution data indicating the distribution of space and structure of rent, vacancy rate distribution data indicating the distribution of space and structure of vacancy rate, from rental housing solicitation data in a wide area including the location of the property and dating back to the past, Distribution analysis that generates turnover distribution data showing the space and structure distribution of turnover of rental contracts And the computer extracts the property information of the property to be evaluated and the data corresponding to the access conditions from the rent distribution data and the vacancy rate distribution data, and calculates the rent and vacancy rate of the property to be evaluated. Rent / vacancy rate calculation step to be calculated, and operation in which the computer calculates the operating revenue of the target property according to the rent and vacancy rate of the target property calculated in the rent / vacancy rate calculation step An income calculation step, an operation expenditure calculation step in which the computer extracts data corresponding to the property information from the turnover distribution data and calculates an operation expenditure of the property to be evaluated, and either the computer or the user Yield setting step for setting the yield of the property to be evaluated on the computer, and the computer A revenue calculation step for calculating the revenue of the property to be evaluated in accordance with the operational revenue, operational expenditure and yield of the elephant property, and the distribution analysis step includes a monthly recruitment of the rental housing recruitment data by the computer. A division step for dividing the data into data, a step for extracting the number of units to be recruited from the monthly recruitment data by the computer, and a step for extracting the monthly recruitment building from the data for the monthly recruitment by the computer. Multiplying the average number of houses and calculating the total number of units by calculating the total number of units, a division step in which the computer divides the monthly recruited number of units by the total number of units, and a division result of the division step in the computer And calculating a moving average for a plurality of months, and classifying a wide area including the location of the property to be evaluated The vacancy rate distribution data is generated for each of a plurality of regions and for each predetermined structural section.

The revenue evaluation program according to the present invention includes a location for the property to be evaluated, a function for capturing property information including the structure of the property to be evaluated, and an access condition including a linear distance from the nearest point to the location and the required time. Rent distribution data indicating the distribution of rent space and structure, vacancy rate space and structure, from the access determination function to be determined, and rental housing recruitment data for a predetermined period that extends back to the past including the location of the property to be evaluated Vacancy rate distribution data indicating the distribution of the rent and the distribution analysis function for generating the rotation rate distribution data indicating the distribution of the rotation rate space and structure of the lease contract, and the evaluation from the rent distribution data and the vacancy rate distribution data Rent that extracts the property information of the target property and data corresponding to the access conditions, and calculates the rent and vacancy rate of the target property Vacancy rate calculation function, operating revenue calculation function to calculate the operating revenue of the evaluated property according to the rent and vacancy rate of the evaluated property calculated by the rent / vacancy rate calculation function, and the turnover rate Extract data corresponding to the property information from the distribution data, calculate the operating expenditure of the property under evaluation, yield setting function to set the yield of the property under evaluation, A revenue evaluation program for evaluating the revenue of rental properties, which enables a computer to realize a revenue calculation function for calculating the revenue of the property subject to evaluation in accordance with the management revenue, the management expenditure and the yield, and the distribution analysis function However, the division function that divides the rental housing recruitment data into the monthly recruitment data and the recruitment number extraction function that extracts the monthly recruitment number from the monthly recruitment data , Extract the monthly recruitment building from the monthly recruitment data, multiply the average number of houses by rank, and calculate the total number of houses by taking the sum, and the number of monthly recruitment units in the total number of houses For each region of multiple regions that have a division function that divides and an averaging function that calculates a moving average of multiple division results of the division function, and that divides the wide area including the location of the property to be evaluated The vacancy rate distribution data is generated for each predetermined structural section.

The vacancy rate calculation device according to the present invention is a vacancy rate calculation device for calculating the vacancy rate of a rental house, the nearest station designating means for designating the nearest station of the real estate to be calculated, and the location of the real estate to be calculated Data for rental housing that is located within a specified range from the nearest station and that matches or approximates the property information of the subject real estate is extracted Extraction means, dividing means for dividing the recruitment data extracted by the extraction means into monthly recruitment data, recruitment number extraction means for extracting the monthly recruitment number from the monthly recruitment data, and the monthly recruitment data Extract the monthly recruitment building from the number, multiply the average number of houses by hierarchy, and calculate the total number of houses by taking the sum, and the division means to divide the number of monthly recruitment by the total number of houses Calculates a moving average of a plurality of monthly division result of the division means, characterized in that the moving average comprising an averaging means for the vacancy rate for the calculation subject property.

The vacancy rate calculation method according to the present invention is a vacancy rate calculation method for calculating the vacancy rate of rental real estate using a computer, the nearest station designation step for designating the nearest station of the real estate to be calculated, and the computer Is a rental housing that is located within a specified range from the nearest station based on rental housing recruitment data for a specified period going back to the past in a wide area including the location of the calculated property. An extraction step for extracting housing recruitment data, a dividing step in which the computer divides the recruitment data extracted in the extraction step into monthly recruitment data, and the computer calculates the number of monthly recruitment units from the monthly recruitment data. The number of recruitment units to be extracted and the computer extracts the monthly recruitment building from the monthly recruitment data. Multiplying the number of homes and calculating the total number of units by calculating the total number of units, a division step in which the computer divides the number of monthly recruited units by the total number of units, and a result of the division by the computer And calculating a moving average for a plurality of months, and setting the moving average as a vacancy rate for the calculation target real estate .

The vacancy rate calculation program according to the present invention is a vacancy rate calculation program for calculating the vacancy rate of rental real estate, the nearest station designation function for designating the nearest station of the real estate to be calculated, and the location of the real estate to be calculated Data for rental housing that is located within a specified range from the nearest station and that matches or approximates the property information of the subject real estate is extracted An extraction function, a division function for dividing the recruitment data extracted by the extraction function into monthly recruitment data, a recruitment number extraction function for extracting the monthly recruitment number from the monthly recruitment data, and the monthly recruitment data The monthly recruitment building is extracted, the average number of houses by rank is multiplied, and the total number of houses is calculated by taking the sum, and the number of monthly recruitment units is divided by the total number of houses. A division function for, calculates a moving average of a plurality of monthly division result of the division function, a program for realizing the moving average averaging function and a computer to check rate with respect to the calculated target property It is.

  According to the present invention, since the rent and the vacancy rate are determined based on the recruitment results, it is possible to accurately estimate the profit even if it is not an expert.

It is a schematic block diagram of one Example of this invention. It is an operation | movement flowchart of the profit evaluation of a present Example. It is an operation | movement flowchart of the vacancy rate calculation for every area by a distribution analysis function. It is a flowchart of the process performed as a pre-process of the process shown in FIG. 3 for the vacancy rate calculation of a designated area.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

  FIG. 1 shows a schematic block diagram of an embodiment of the present invention, and FIG. 2 shows an operation flowchart of a profit evaluation program of this embodiment.

  The present embodiment is realized by a profit evaluation program operating on a computer. That is, the revenue evaluation program operates on the CPU 10, and the user inputs the location and property information of the rental property to be evaluated (hereinafter referred to as “evaluation target property”) to the CPU 10 using the keyboard 12. The input location is, for example, the prefecture where the evaluation target property exists, the municipality, and the town chome, but the latitude and longitude of the ground coordinate system or the method of specifying the location on the map data Good. Wide-area map data 14 including the location of the property to be evaluated, station data 16, city planning data 18, published rental housing recruitment data 20, and cost unit price and return yield survey data 22 can be referred to by the CPU 10. Stored on the hard disk or server.

  The map data 14 includes not only a map but also various geospatial information constituting a geographic information system (GIS).

  The station data 16 constitutes a database including information such as a name, a location (latitude / longitude), and an arrival time from a station as a starting point regarding a plurality of routes and stations on each route.

  The rental housing recruitment data 20 is a collection of data published on the Web, for example, for recruitment of rental housing such as apartments and condominiums, and is accumulated by tracking a period of about 10 years. Since the recruitment data 20 includes rents for various buildings, it can be used to calculate rents. In addition, it is possible to predict the vacancy rate and the recruitment turnover rate from the recruitment of the same property and its termination (posting cancellation).

  Survey data 22 consists of cost data such as unit cost of maintenance and repair costs collected in the area including the location of the property to be evaluated, and return yield data. For example, by conducting a questionnaire survey with a real estate appraiser, Collected in advance.

  As for the cost unit price, for each prefecture, the unit cost of maintenance and management costs, utility costs, repair costs, PM costs, tenant recruitment costs, property insurance premiums, and other costs for properties centered on single-family residences, apartments, condominiums ( Collected in three categories: no elevator) and apartment (with elevator). Also, the premium rate of 10 years or less, 20 years or less, and 21 years or more, the premium rate when the property is located in the suburbs, and the premium rate when the property is a family residence can be collected. The unit price is calculated according to the property conditions (structure, building age, elevator presence, etc.), and the value of each expense item is calculated.

  Yield data relating to the capitalization yield includes, for example, a basic yield for a standard property and adjustment items for the basic yield, and is collected as specific numerical values.

The basic yield is in the case of Tokyo, and is divided into wards within the Yamanote Line, 23 wards outside the Yamanote Line, and outside the 23 wards. Standard properties are, for example,
・ Structure: RC construction (apartment)
・ Built-in age: 5 years ・ Total number of floors: 7th floor, with elevator ・ Station distance: 5 minutes on foot ・ Number of rooms: 35 rooms ・ Room type: Single (one room, 1K)
・ Location: The area where the prefectural office is located or where rental housing is concentrated in cities designated by government ordinance. As the vacancy rate, the condominium vacancy rate by region of the prefecture is assumed, and as the turnover rate, the turnover rate of the prefecture or government-designated city is assumed.

The adjustment items are as follows. That is,
・ Built-in: Yield change due to year-round change ・ Total number of floors: Yield change as floors increase / decrease ・ Station distance: Yield change as station distance increases / decreases ・ Bus: With bus Yield change / room type: Yield change for family / rented land: Yield change when land is leased.

  Functions (or means) realized by the profit evaluation program operating on the CPU 10 include a distribution analysis function 30, a position coordinate specifying function 32, an access / regulation determining function 34, a rent / vacancy rate calculating function 36, an operating revenue. There are a calculation function 38, an operation expenditure calculation function 40, a yield calculation function 42, a profit calculation function 44, a CF (cash flow) calculation function 46, and an output function 48.

The profit evaluation operation of this embodiment will be described. In preparation for the calculation of the rent and vacancy rate of the property to be evaluated, the distribution analysis function 30 uses a statistical analysis of the published rental housing recruitment data 20 to determine the predetermined area (administrative unit, range from the nearest station, etc.) Rent distribution data indicating the distribution of the rent space and structure, vacancy rate distribution data indicating the distribution of the vacancy space and structure, and the rotation rate distribution indicating the space and structure distribution of the turnover rate of the rental contract Data is generated and stored internally. The elements of space and structure are generally different depending on the rent, vacancy rate and turnover rate, and can be appropriately selected according to each purpose. The distribution relating to the space is, for example, a distribution relating to the walking distance from the nearest station, and the distribution relating to the structure is, for example, a wooden or steel frame, a building age, a floor number, or the like.

  Specifically, the distribution analysis function 30 creates hedonic formulas for single and family residences for each prefecture from the rental housing recruitment data 20 as rent distribution data. Rent can be calculated by substituting various conditions (station distance, building age, structure, etc.) of the property to be evaluated into this hedonic equation.

  Regarding the vacancy rate distribution, the distribution analysis function 30 refers to the recruitment status of the rental housing solicitation data 20 for a certain period in the past (for example, one year), and vacancy rate distribution in a plurality of areas that are likely to be evaluated for profit. Is calculated. It can be presumed that the rental properties that were recruited in the rental housing recruitment data were vacant during the recruitment period. Therefore, the vacancy rate is calculated based on the ratio of the leased properties being offered as vacancy and the sample value of the period, to the total number of rental properties in the area where the property to be evaluated exists. Although details will be described later, for example, the distribution analysis function 30 divides prefectures into ordinance-designated cities and other areas, the ordinance-designated cities are divided into wards, and other areas are divided into multiple areas based on the data amount. The vacancy rate is calculated by dividing into an apartment system (wooden structure, lightweight steel structure) and an apartment system (steel structure, reinforced concrete structure, steel reinforced concrete structure). By applying the location and structure of the evaluation target property to the vacancy rate distribution data obtained by the analysis of the distribution analysis function 30, the vacancy rate of the evaluation target property can be calculated.

  The distribution analysis function 30 also refers to the recruitment status of the rental housing solicitation data 20 for a certain period in the past (for example, one year), calculates the contract renewal probability and the mid-term cancellation probability for each prefecture / designated city, The turnover rate (recruitment frequency) is calculated from the probability. If the number of data is large, calculate by structure. Rental contracts are usually in units of 2 years, the contract renewal probability indicates the probability of being renewed even if the contract period (2 years) expires, and the midterm cancellation probability is canceled (exited) before the contract period expires The maturity cancellation probability indicates the probability of leaving without renewing the contract.

Specifically, the distribution analysis function 30 counts the number of months (re-recruitment months) until the contracted property appears on the market again (recruitment starts) on the rental housing solicitation data 20. If the re-recruitment is less than 6 months, there is a possibility of an input error, so this will be deleted from consideration. In addition, the distribution analysis function 30 has a re-recruitment period of 7 months as the balance between those whose re-recruitment is 49 months or more is less than 10% of the total and those whose re-recruitment is less than 6 months is not considered. or that of 48 months, to evaluate the update probability and early termination probability. That is,
Contract renewal probability = (number of re-recruited units from 27 to 48 months) / (total number of re-recruited units from 7 to 48 months)
Probability of mid-term cancellation = (7 to 22 months re-recruited units) / (7 to 48 months total re-recruited units)
age,
Expiration probability at maturity = 100 (%)-(Contract renewal probability + Midway termination probability)
And Rotation rate is
Turnover rate = maturity cancellation probability + midway cancellation probability / 2
Is calculated by

  An operation for evaluating the profit of a specific property (evaluation target property) will be described. The user inputs location data such as a prefecture, a city, a town, and a town where the evaluation target property exists to the CPU 10 using the keyboard 12 (S1). The position coordinate specifying function 32 refers to the map data 14 and determines the position coordinates (latitude and longitude) in the geodetic coordinate system of the input location (S2).

  The access / legal regulation decision function 34 refers to the station data 16 and specifies the access conditions (the nearest station, the straight distance from the nearest station and the required time (walking or busing)) for the property to be evaluated, and city planning. With reference to the data 18, the laws and regulations (use area, building coverage ratio and floor area ratio) for the property to be evaluated are specified (S3). The user can correct the contents of the laws and regulations defined in the city planning data 18. This is because the laws and regulations are subject to change.

  The CPU 10 causes the user to input property information using the keyboard 12 (S4). Property information that can be entered includes, for example, the accumulated evaluation value, site area, rights (ownership / leased land / ground rights, etc.), structure (wooden / steel / steel, etc.), presence / absence of elevator, total floor area, number of floors, exclusive area The date and the number of parking lots.

  The rent / vacancy rate calculation function 36 compares the access conditions and regulations determined in step S3 and the property information input in step S4 with the results analyzed in advance by the distribution analysis function 30, and is subject to evaluation. Calculate the rent (annual amount) and vacancy rate of the property (S5, S6). The rent / vacancy rate calculation function 36 checks whether or not the property information of the property to be evaluated falls under the laws and regulations determined by the access / law regulation determination function 34. Prompt the user for correction.

  With regard to rent, the rent / vacancy rate calculation function 36 calculates the rent of the property to be evaluated based on the hedonic formula that covers the location of the property to be evaluated and the conditions of the property to be evaluated (station distance, building age, structure, etc.). Calculate (S5). Specifically, the rent / vacancy rate calculation function 36 extracts a hedonic expression that covers the location of the evaluation target property from the hedonic expression generated by the distribution analysis function 30 and determines various conditions (station distance, Substituting the building age and structure, etc., and calculating the rent unit price. Then, the rent / vacancy rate calculating function 36 calculates the rent by multiplying the obtained rent unit price by the exclusive area of the property to be evaluated.

  Regarding the vacancy rate, the rent / vacancy rate calculation function 36 extracts the vacancy rate distribution data covering the location of the property to be evaluated from the vacancy rate distribution data analyzed by the distribution analysis function 30 and evaluates it. The vacancy rate of a property that is close to the target property and that corresponds to or approximates the structure of the evaluation target property is selected (S6). When the vacancy rate of multiple properties with the same or similar structure is found near the evaluation target property, the vacancy rate at the location of the evaluation target property is calculated by spatially calculating the vacancy rate of those properties May be calculated or determined.

  The management revenue calculation function 38 calculates the management revenue of the property to be evaluated from the rent calculated in S5 and the vacancy rate calculated in S6 (S7). Operating revenue is calculated by subtracting the rent for the period corresponding to the vacancy rate from the annual revenue calculated from the rent. If there is parking revenue, collect parking cases for a certain period (for example, one year) with a radius of 400m (or within a 5-minute walk) centered on the location where the property to be evaluated is located. Parking lot rent. The management revenue calculation function 38 outputs the total of the calculated revenues to the revenue calculation function 44 as management revenue. The calculation result of the operating revenue calculation function 38 may be modified by the user.

  The operation expenditure calculation function 40 calculates the operation expenditure of the property to be evaluated according to the input property information, the turnover information from the distribution analysis function 30 and the expense unit price of the survey data 22, and outputs it to the income calculation function 44 (S8). ). Operating expenses are in accordance with real estate appraisal standards and include maintenance costs, utility costs, repair costs, PM costs, tenant solicitation costs, taxes and public charges, property insurance premiums and other costs.

  For maintenance costs, utility costs, repair costs, PM costs, tenant solicitation costs, non-life insurance fees and other costs, the operation expenditure calculation function 40 extracts the repair cost survey results of the area including the property to be evaluated from the survey data 22 Then, the repair cost of each cost is calculated in terms of property information.

  For tenant solicitation costs, the operation expenditure calculation function 40 extracts the turnover rate of the location from the turnover rate of each prefecture / designated city calculated by the distribution analysis function 30 and obtains the general unit price of the tenant solicitation cost. Multiply to calculate tenant recruitment costs. When the turnover rate classified or distinguished for each structure is obtained, the operation expenditure calculation function 40 refers to the property information of the property to be evaluated, and calculates the tenant soliciting cost from the turnover rate of the corresponding structure.

  With regard to taxes and public dues, the operation expenditure calculation function 40 calculates the amount of taxes and public dues based on the fixed asset tax rate, the city planning tax rate, and the reduction measures for small residential land, with 70% of the accumulated evaluation amount as the fixed asset evaluation amount. In addition, you may enable it for a user to correct the result calculated by the operating expenditure calculation function 40. FIG.

  The yield calculation function 42 refers to the yield data (basic yield and adjustment items) of the survey data 22, and calculates the return yield of the property to be evaluated (S9). Specifically, the yield calculation function 42 selects the basic yield of the location value of the property to be evaluated from the yield data (basic yield and adjustment items) of the survey data 22 and adjusts according to the property information of the property to be evaluated. Calculate the value. Then, the yield calculation function 42 sets the result of adding each adjustment value to the selected basic yield as the return yield of the property to be evaluated, and outputs it to the profit calculation function 44. The result calculated by the yield calculation function 42 may be adjusted by the user.

  The revenue calculation function 44 subtracts the operation expenditure calculated by the operation expenditure calculation function 40 from the operation revenue calculated by the operation revenue calculation function 38, and divides the subtraction result by the return yield calculated by the yield calculation function 38. To do. The result of the division is the revenue price, and the revenue calculation function 44 outputs the calculated revenue price to the output function 48.

  The CF (cash flow) calculation function 46 calculates the rent and the rate of decline, the vacancy rate and the age transition rate, and the cost unit price from the survey data 22 and the rate of change due to the age of the building under the condition of the property information to be evaluated. Is used to calculate the cash flow for 35 years (S11). The rate of decline in rent is taken from the prefecture where the target property is located. This can be calculated from the hedonic formula of the rent assessment calculated by the distribution analysis function 30. If the property to be evaluated is mainly for singles, the rate of decline in rent for singles is used. Adopt the family rent decline rate. The building age transition rate of the vacancy rate is expressed in terms of a rate of change with a prefecture / designated city unit, for example, 5 years old as 100%. The CF calculation function 46 calculates the vacancy rate for each year from the vacancy rate calculated by the rent / vacancy rate calculation function 36 using the change rate.

  The output function 48 outputs the profit calculated by the profit calculation function 44 and the cash flow calculated by the CF calculation function 46 as a report of a predetermined file format, and outputs it to a printer for printing or for display. The data is output to the display device (S12).

  Since the distribution analysis function 30 analyzes and acquires the basic data of rent and vacancy rate necessary for calculating the rent and vacancy rate of the property to be evaluated in many areas where there is a possibility of revenue evaluation. In this embodiment, it is possible to quickly evaluate the profits of individual evaluation target properties.

  There are a large number of rental properties that match or approximate property information (building age, structure, number of floors, and for singles / family members) around the location of the property to be evaluated (for example, within a radius of 400m or within a 5-minute walk) In this case, the following method may be adopted for calculating the rent and the vacancy rate. That is, the rental property recruitment data that matches or approximates the property information around the location of the property to be evaluated is extracted from the rental housing recruitment data. Then, the rent of the extracted rental property (the average in a plurality of cases) is set as the rent of the evaluation target property, and the ratio of the vacancy period (the average in the case of a plurality of cases) is set as the vacancy rate of the evaluation target property.

  FIG. 3 shows a flowchart of a process for quantitatively evaluating the vacancy rate in units of regions in the distribution analysis function 30. The distribution analysis function 30 calculates the vacancy rate according to the flow shown in FIG. 3 for the designated regional units in prefecture units, government-designated city units, and narrower regions (for example, station units, town chome units, etc.). . In addition, the number of recruited houses at a certain time is the number of vacant samples in the area, and the total number of houses in the building at the same time is considered the number of samples of the total number of houses in the area. In this embodiment, the vacancy rate is obtained by dividing the former by the latter.

  The distribution analysis function 30 reads the recruitment data for a certain period in any designated area unit from the published rental housing recruitment data 20 (S21), and deletes abnormal values and duplicates from the read data (S22).

  The distribution analysis function 30 divides the read data into monthly recruitment data (S23), and extracts the number of monthly recruitment units from the monthly recruitment data (S24). This monthly recruitment number is the number of vacant units.

  In order to obtain the number of samples of the total number of units, the distribution analysis function 30 extracts the monthly recruitment building from the monthly recruitment data (S25), and classifies each monthly recruitment building by level (S26). In order to quantitatively evaluate the total number of houses per floor, the distribution analysis function 30 refers to the public adjustment information of the national census and residential land statistics survey separately, and the average number of houses per rental house by floor in each prefecture Is calculated (S27). The distribution analysis function 30 calculates the total number of houses for each level by multiplying the average number of houses per building calculated in S27 by the number of buildings in the corresponding level calculated in S26 (S28). The distribution analysis function 30 calculates the sum of the total number of houses for each level obtained in S28 (S29). This sum corresponds to the total number of samples in the area of interest.

  The distribution analysis function 30 divides the monthly recruitment number extracted in S24 by the total number calculated in S29 (S30). By executing S24 to S29 for another month (S31), the vacancy rates for a plurality of months can be obtained.

  When the calculation of the continuous monthly vacancy rate for 12 months or more is completed (S31), the distribution analysis function 30 eliminates seasonal fluctuations by calculating the moving average of the monthly vacancy rate for 12 months (S32). ). Let this moving average value be the vacancy rate of the area of interest.

  The distribution analysis function 30 calculates the distribution of the vacancy rate in a narrower region unit for a wide region range where revenue evaluation is possible, but the region range necessary for revenue evaluation (for example, about a town level) The vacancy rate may be calculated for the area or the vicinity of the designated station. In this case, the position information obtained by the position coordinate specifying function 32 and / or the access information determined by the access / legal regulation determining function 34 are input to the distribution analysis function 30.

  FIG. 4 shows a flowchart of processing for designating an area prior to the processing shown in FIG.

  The user or the operator designates the area for which the vacancy rate is to be calculated by using the keyboard 12 with the area name (for example, a prefecture, a town, a town, a town, etc.) or a station name (S41). The CPU 10 specifies the latitude and longitude of the designated point / station with reference to the map data 14 and / or the station data 16 (S42).

  CPU10 reads the recruitment data of the fixed period within a fixed distance centering | focusing on the specified latitude longitude from the rental housing recruitment data 20 (S43). If a predetermined number of recruitment data cannot be read after removing abnormal values and duplication, the extraction area is expanded until the predetermined number of recruitment data can be read. For example, a radius of 400 m is expanded to a radius of 800 m, further expanded to a municipality, and further expanded to a prefecture.

  The user or operator uses the keyboard 12 to input analysis conditions such as the structure, floor plan, building age, and area of the property for which the vacancy rate is to be calculated (or selected from the options) (S44). The CPU 10 extracts recruitment data that matches the analysis conditions input / selected in S44 from the recruitment data read in S43 (S45).

  Thereafter, the CPU 10 executes the processing after S23 shown in FIG.

By such processing, the user or operator can know with a vacancy rate based on the most recent recruitment data area any desired. In other words, in the vicinity of the location of the property to be evaluated for revenue evaluation (for example, within a radius of 400 m or within a 5-minute walk), a number of items that match or approximate property information (building age, structure, number of floors, single / family use) If there are rental properties, the following method may be adopted. That is, the rental property recruitment data that matches or approximates the property information around the location of the property to be evaluated is extracted from the rental housing recruitment data. Then, the rent of the extracted rental property (the average in a plurality of cases) is set as the rent of the evaluation target property, and the ratio of the vacancy period (the average in the case of a plurality of cases) is set as the vacancy rate of the evaluation target property.

The rent and the vacancy rate (or the intermediate value on which these are calculated) can be calculated in advance from the rental housing data. Thus, when the pre-rents or vacancy rate (or these intermediate values) are calculated, steps S5, S6, in fact, rent or calculated in advance with respect to various regions and listing From the vacancy rate, the location of the property to be evaluated and the rent or vacancy rate for the property information are selected. When the intermediate value is calculated, the CPU applies the parameter processing depending on the property to be evaluated to the intermediate value in steps S5 and S6.

  In order to facilitate understanding, the map data 14, the station data 16, the city planning data 18, the rental housing recruitment data 20, and the survey data 22 have been described as if they were stored in a hard disk that is an auxiliary storage of the computer. Of course, one or more of these data 14 to 22 may be on a server connected via a network, or may be provided by a specific business operator.

  Although the invention has been described with reference to specific illustrative embodiments, various modifications and alterations may be made to the above-described embodiments without departing from the scope of the invention as defined in the claims. This is obvious to an engineer in the field to which the present invention belongs, and such changes and modifications are also included in the technical scope of the present invention.

10: CPU
12: Keyboard 14: Map data 16: Station data 18: City planning data 20: Rental housing recruitment data 22: Survey data (expense unit price, yield data)
24: Public statistical information 30: Distribution analysis function 32: Location coordinate identification function 34: Access / law regulation determination function 36: Rent / vacancy rate calculation function 38: Operating revenue calculation function 40: Operational expenditure calculation function 42: Yield calculation Function 44: Revenue calculation function 46: CF (cash flow) calculation function 48: Output function

Claims (18)

A revenue evaluation device for evaluating the revenue of rental properties,
A designation means for designating the location of the property to be evaluated;
Property information input means for inputting property information including the structure of the property to be evaluated,
An access determining means for determining access conditions including a straight line distance and a required time from the nearest point to the location;
Rent distribution data indicating the distribution of rent space and structure, and the vacancy rate indicating the distribution of space and structure of vacancy rate, from the rental housing recruitment data for a specified period that extends back to the past, including the location of the subject property Distribution analysis means for generating distribution data and turnover distribution data indicating a distribution relating to the space and structure of the turnover rate of the rental contract;
Rent / vacancy rate for calculating the rent and vacancy rate of the property to be evaluated by extracting the property information and data corresponding to the access conditions of the property to be evaluated from the rent distribution data and the vacancy rate distribution data A calculation means;
Operating revenue calculation means for calculating operating revenue of the property subject to evaluation in accordance with the rent and vacancy rate of the property subject to evaluation calculated by the means for calculating the rent / vacancy rate;
An operation expenditure calculating means for extracting data corresponding to the property information from the turnover distribution data and calculating an operation expenditure of the evaluation target property;
Yield setting means for setting the yield of the property to be evaluated;
A revenue calculation means for calculating the revenue of the property subject to evaluation in accordance with the operation revenue, the operation expenditure and the yield of the property subject to evaluation;
The distribution analysis means is
A dividing means for dividing the rental housing recruitment data into monthly recruitment data;
Recruitment unit extraction means for extracting monthly recruitment units from the monthly recruitment data,
A total number of units calculating means for calculating the total number of units by extracting the monthly number from the monthly recruitment data, multiplying the average number of units by level, and taking the sum;
Dividing means for dividing the monthly recruitment number by the total number of units,
A means for calculating a plurality of monthly moving averages of the division results of the division means, and for each of a plurality of regions that divide a wide area including the location of the property to be evaluated and for each predetermined structural division And generating the vacancy rate distribution data. The management expenditure calculation means extracts the expense information corresponding to the property information from the survey data including the expense information and the yield information in the area including the location of the property to be evaluated, and corresponds to the property information from the turnover distribution data. Data to be calculated, calculate the operating expenses of the property to be evaluated,
The profit evaluation apparatus according to claim 1, wherein the yield setting means is a yield calculation means for calculating a yield of the evaluation target property with reference to the yield information of the survey data.   The distribution analysis means contracts the result of dividing the number of re-recruited units between the period exceeding one contract period and the expiration of the two contract periods by the total number of re-recruited units within the period of two contract periods. The renewal probability, the number of re-recruited units from the middle of one contract period to the time before the expiration of one contract period divided by the total number of re-recruited units within the period of two contract periods, The profit evaluation apparatus according to claim 1 or 2, wherein a result obtained by subtracting the contract renewal probability and half of the midway cancellation probability from 100 (%) is set as the turnover rate. A revenue evaluation method for evaluating the income of rental properties using a computer,
Entering the location of the property to be evaluated on the computer;
A property information input step for inputting property information including the structure of the property to be evaluated to the computer;
An access determining step in which the computer determines an access condition including a linear distance from the nearest point to the location and the time required;
Rent distribution data indicating the distribution of the rent space and structure, the vacancy rate distribution and the distribution of the vacancy rate from the rental housing solicitation data for a predetermined period going back to the past in a wide area including the location of the property to be evaluated. A distribution analysis step for generating vacancy rate distribution data to indicate, and rotation rate distribution data indicating a distribution relating to space and structure of the rotation rate of the rental contract
Rent by which the computer extracts the property information of the property to be evaluated and the data corresponding to the access conditions from the rent distribution data and the vacancy rate distribution data, and calculates the rent and vacancy rate of the property to be evaluated・ Vacancy rate calculation step,
A management revenue calculation step in which the computer calculates a management revenue of the property to be evaluated according to the rent and vacancy rate of the property to be evaluated calculated in the rent / vacancy rate calculation step;
An operation expenditure calculating step in which the computer extracts data corresponding to the property information from the turnover distribution data and calculates an operation expenditure of the evaluation target property;
A yield setting step in which either the computer or the user sets the yield of the property to be evaluated on the computer;
The computer comprises a revenue calculating step for calculating the revenue of the property to be evaluated according to the operating revenue, the operating expenditure and the yield of the property to be evaluated,
The distribution analysis step is
A dividing step in which the computer divides the rental housing solicitation data into monthly solicitation data;
A step of extracting the number of units to be recruited in which the computer extracts the number of units to be recruited from the monthly recruitment data;
A step of calculating the total number of units, in which the computer extracts the monthly recruitment building from the monthly recruitment data, multiplies the average number of units by hierarchy, and calculates the total number of units by taking the sum;
A division step in which the computer divides the number of monthly subscriptions by the total number of units;
The computer having an averaging step for calculating a plurality of monthly moving averages of the division results of the division step, for each of a plurality of regions that divide a wide area including the location of the property to be evaluated and a predetermined amount A revenue evaluation method characterized by generating the vacancy rate distribution data for each structural division. The operation expenditure calculation step extracts the expense information corresponding to the property information from the survey data including the expense information and the yield information in the area including the location of the evaluated property, and corresponds to the property information from the turnover distribution data Data to be calculated, calculate the operating expenses of the property to be evaluated,
The profit evaluation method according to claim 4, wherein the yield setting step calculates the yield of the evaluation target property with reference to the yield information of the survey data.   The distribution analysis step is based on the result of dividing the number of re-recruited units between the period exceeding one contract period and the expiration of the second contract period by the total number of re-recruited units within the period of two contract periods. The renewal probability, the number of re-recruited units from the middle of one contract period to the time before the expiration of one contract period divided by the total number of re-recruited units within the period of two contract periods, 6. The profit evaluation method according to claim 4, wherein the turnover rate is a result of subtracting the contract renewal probability and half of the midway cancellation probability from 100 (%). The location of the property to be evaluated and the function to capture property information including the structure of the property to be evaluated,
An access decision function for determining access conditions including the straight line distance from the nearest point to the location and the required time;
Rent distribution data indicating the distribution of rent space and structure, and the vacancy rate indicating the distribution of space and structure of vacancy rate, from the rental housing recruitment data for a specified period that extends back to the past, including the location of the subject property A distribution analysis function for generating distribution data and turnover distribution data indicating the distribution of space and structure of the turnover rate of the rental contract;
Rent / vacancy rate for calculating the rent and vacancy rate of the property to be evaluated by extracting the property information and data corresponding to the access conditions of the property to be evaluated from the rent distribution data and the vacancy rate distribution data A calculation function;
An operating revenue calculation function for calculating operating revenue of the property subject to evaluation according to the rent and vacancy rate of the property subject to evaluation calculated by the rent / vacancy rate calculating function;
An operation expenditure calculation function that extracts data corresponding to the property information from the turnover distribution data and calculates the operation expenditure of the property to be evaluated,
Yield setting function to set the yield of the property subject to evaluation,
This is a revenue evaluation program that evaluates the revenue of rental properties so that the computer can realize the revenue calculation function that calculates the revenue of the property under evaluation in accordance with the operation revenue, the operation expenditure and the yield of the property under evaluation. And
The distribution analysis function
A division function for dividing the rental housing recruitment data into monthly recruitment data;
Recruitment number extraction function to extract monthly recruitment number from the monthly recruitment data,
A function to calculate the total number of units by extracting the monthly number from the monthly recruitment data, multiplying the average number of units by rank, and calculating the total number of units by taking the sum,
A division function that divides the number of monthly subscriptions by the total number of units;
A function that averages multiple monthly moving averages of the division results of the division function, and for each of a plurality of regions that divide a wide area including the location of the property to be evaluated and for each predetermined structural category A profit evaluation program characterized by generating the vacancy rate distribution data. The operation expenditure calculation function extracts the expense information corresponding to the property information from the survey data including the expense information and the yield information in the area including the location of the evaluated property, and corresponds to the property information from the turnover distribution data Data to be calculated, calculate the operating expenses of the property to be evaluated,
8. The profit evaluation program according to claim 7, wherein the yield setting function calculates the yield of the property to be evaluated with reference to the yield information of the survey data.   The distribution analysis function contracts the result of dividing the number of re-recruited units between the period exceeding one contract period and the expiration of the second contract period by the total number of re-recruited units within the period of the two contract periods. The renewal probability, the number of re-recruited units from the middle of one contract period to the time before the expiration of one contract period divided by the total number of re-recruited units within the period of two contract periods, The profit evaluation program according to claim 7 or 8, wherein the turnover rate is a result of subtracting the contract renewal probability and half of the midway cancellation probability from 100 (%). A vacancy rate calculation device for calculating the vacancy rate of rental housing,
The nearest station designation means for designating the nearest station of the real estate to be calculated;
Rental housing that is located within a specified range from the nearest station based on rental housing recruitment data for a specified period that extends back to the past, including the location of the target real estate, and that matches or approximates the property information of the target real estate Extracting means for extracting the recruitment data of
Dividing means for dividing the recruitment data extracted by the extraction means into monthly recruitment data;
Recruitment unit extraction means for extracting monthly recruitment units from the monthly recruitment data,
A total number of units calculating means for calculating the total number of units by extracting the monthly number from the monthly recruitment data, multiplying the average number of units by level, and taking the sum;
Dividing means for dividing the monthly recruitment number by the total number of units,
A vacancy rate calculating apparatus comprising: a moving average for a plurality of monthly results of division by the dividing means; and an averaging means for setting the moving average as a vacancy rate for the calculation target property . The nearest station designation means is
A designation means for designating the location of the subject real estate,
11. The vacancy rate calculating device according to claim 10, further comprising: nearest station determining means for determining the nearest station to the location by referring to station data that stores location information of the railway line and the station. .   11. The vacancy rate calculating apparatus according to claim 10, wherein the nearest station specifying means is means for a user to input information for specifying the nearest station. A vacancy rate calculation method for calculating the vacancy rate of rental properties using a computer,
The nearest station designation step for designating the nearest station of the property to be calculated;
The rental computer is located within a specified range from the nearest station based on rental housing recruitment data for a specified period that extends back to the past in a wide area including the location of the calculated property, and matches or approximates the property information of the calculated property An extraction step of extracting recruitment data for rental housing to be
A division step in which the computer divides the recruitment data extracted in the extraction step into monthly recruitment data;
A step of extracting the number of units to be recruited in which the computer extracts the number of units to be recruited from the monthly recruitment data;
A step of calculating the total number of units, in which the computer extracts the monthly recruitment building from the monthly recruitment data, multiplies the average number of units by hierarchy, and calculates the total number of units by taking the sum;
A division step in which the computer divides the number of monthly subscriptions by the total number of units;
Vacancy characterized in that said computer comprises an averaging step of calculating a moving average of a plurality of monthly results of division in said division step and setting said moving average as a vacancy rate for said calculation target property Rate calculation method. The nearest station designation step is
A designation step for designating the location of the subject real estate for calculation;
14. The vacancy rate calculation method according to claim 13, further comprising: nearest station determination means for determining the nearest station to the location by referring to station data that stores location information of railway lines and stations. .   14. The vacancy rate calculation method according to claim 13, wherein the nearest station designation step is a step in which a user inputs information for identifying the nearest station to the computer. A vacancy rate calculation program for calculating the vacancy rate of rental properties,
The nearest station designation function that designates the nearest station of the real estate subject to calculation,
Rental housing that is located within a specified range from the nearest station based on rental housing recruitment data for a specified period that extends back to the past, including the location of the target real estate, and that matches or approximates the property information of the target real estate An extraction function to extract recruitment data of
A division function for dividing the recruitment data extracted by the extraction function into monthly recruitment data;
Recruitment number extraction function to extract monthly recruitment number from the monthly recruitment data,
A function to calculate the total number of units by extracting the monthly number from the monthly recruitment data, multiplying the average number of units by rank, and calculating the total number of units by taking the sum,
A division function that divides the number of monthly subscriptions by the total number of units;
A vacancy rate calculation program for causing a computer to realize a moving average of a plurality of monthly division results of the division function and using the moving average as a vacancy rate for the calculation target property . The nearest station designation function is
A designated function for designating the location of the subject real estate,
The vacancy rate calculation program according to claim 16, further comprising a nearest station determination function for determining a nearest station to the location by referring to station data that stores location information of railway lines and stations. .   The vacancy rate calculation program according to claim 16, wherein the nearest station designation function is a function for a user to input information for identifying the nearest station to the computer.

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