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Appraisals are based on regression models. Its major application limits are all in situations in which the real estate market doesn’t offer a sufficient number of comparables to implement statistical tools. In low-transaction real estate markets, the most effective appraisal method is the market comparison approach (MCA). The application limits of MCA depend on the degree of similarity between the properties’ characteristics and the reliability of the prices of comparables. In this paper, we introduce some rational measurements in order to guarantee a scientific approach to MCA is associated with the correct prices. Our method is able to restore appraisals of the market value of any type of property, even in situations in which the comparables are limited or when the reliability of the buying and selling prices could be better.

This study concerns the analytical formulation and relative implications of bottom value (BV) and mortgage lending value (MLV) regarding properties where the existing building provides an income during its useful life, leaving thereafter only the land value. The bottom value is equal to the overall property’s market value minus all incomes not collected by the end of the building’s economic life. Furthermore, it considers the income rates for land and buildings differently according to the investment type, while the mortgage lending value considers, instead, a unique rate. The mortgage lending value assessment is conducted under restrictive assumptions on long-term aspects, future marketability, and local market conditions. For the first time, mathematical and appraisal models have been applied to determine the mortgage lending value and the bottom value in particular cases, such as that mentioned above and considered in the present study (existing buildings providing income during their useful life). Some of the indexes introduced in the paper are completely original with respect to the current reference literature.

In international and metropolitan real estate markets, it has been detected the growing relevance of Green Buildings with respect to non-Green Building. In this paper the green premium for buildings has been singled out and then quantified through a market analysis of an urban central area of Reggio Calabria (Italy), i.e. the positive differential in terms of higher price toward sold real estate units having ecological characteristics and energy efficiency. This goal has been pursued comparing the results obtained by different methods: Multiple Regression Analysis (MRA), Appraisal System Approach (ASA) and Market Comparison Approach (MCA).

Purpose – A useful instrument to understand and examine the inner workings of the property trade is devising index numbers of property prices based on historical sequences of market prices. The present work aims at the definition of index numbers of property prices, proposing an innovative methodology compared with what usually recurs in literature. The purpose of this paper is to discuss these issues. Design/methodology/approach – The analysis proposed, based on the mechanisms of formation of stock indices, investigates the analogies between stock and property information, according to the peculiarities of the property trade, leading to a methodology approach, derived from Simple Price Index Method, able to consider possible anomalies in the collected sample of purchase prices, using weighting coefficients based on reliability coefficients of sale prices of properties. Findings – The novel approach proposed has led to the definition of a original methodology useful to appraise property price index numbers and other derived indicators, effective for interpreting and identifying real estate market dynamics in a given area of study, regarded as a standard estimating methodology applicable to any geographical context and kind of property. Practical implications – Methodology proposed in this work is useful to revalue real estate sales price and to consider presence of anomalous sales price in property samples. Originality/value – The calculation of index numbers of prices is usually based on Simple Price Index Methods. Literature shows large use of different methods, such as Repeat Sales Method, Hedonic Price Method, Repeat Value Model. The present work propose an innovative methodology able to detect the presence of possible anomalous market prices in the representative sample, using an appropriate vector of weights in order to take into account the level of reliability of market data.

When a market oriented approach is not applicable because of the lack of comparable sales data (Ciuna et al. 2014a), 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.