When a market oriented approach is not applicable because of the lack of comparable sales data (Ciuna et al., 2014), International Valuation Standards suggest the use of the Income Approach, which has the task of simulating the market through an economic and financial scheme. The central question of this approach is due to the quantification of the capitalization rate, whereas it is generally extracted in a market segment different from that of the subject. This paper intends to propose an automated valuation model of the capitalization rate based on a real estate database built through a computerized geocoding automatic procedure, starting from the application of statistical models of multiple regression analysis, performed to separately build the prediction function of the price and the prediction function of the income.
Ciuna, M., Salvo, F., Simonotti, M., De Ruggiero, M. (2017). Automatic research of the capitalization rate for the residential automated valuation: an experimental study in Cosenza (Italy).. In M. d'Amato (a cura di), Advances in Automated Valuation Modeling AVM After the Non-Agency Mortgage Crisis (pp. 361-380) [10.1007/978-3-319-49746-4].
Automatic research of the capitalization rate for the residential automated valuation: an experimental study in Cosenza (Italy).
CIUNA, Marina;SIMONOTTI, Marco;
2017-01-01
Abstract
When a market oriented approach is not applicable because of the lack of comparable sales data (Ciuna et al., 2014), International Valuation Standards suggest the use of the Income Approach, which has the task of simulating the market through an economic and financial scheme. The central question of this approach is due to the quantification of the capitalization rate, whereas it is generally extracted in a market segment different from that of the subject. This paper intends to propose an automated valuation model of the capitalization rate based on a real estate database built through a computerized geocoding automatic procedure, starting from the application of statistical models of multiple regression analysis, performed to separately build the prediction function of the price and the prediction function of the income.File | Dimensione | Formato | |
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