The lack or unavailability of data poses one of the greatest obstacles hindering the exploration of real estate market information. Due to the small number of observations (cases), there are limited possibilities of using statistical methods, which are generally based on the assumption of a larger number of cases compared to the data describing them. This work provides an application of Rough Set Theory to a small sample of commercial properties as an Automatic Valuation Method. RST has been proposed as an automatic procedure for small sample (d’Amato 2002). It may happen in the application of RST that it is possible to deal with small samples. The rough set theory was applied taking into account the specific nature of information referring to the real property market. This theory is dedicated to examine imprecision, generality and unavailability in the process of data analysis that often occurs on the real estate market. It has been highlighted that one of the problem in AVM application may be the scarcity of data (Downie and Robertson 2007). The model allows the opportunity to reach the results of a single point estimate using if then rules providing a causal non deterministic relationship between price and property characteristics. The model has been applied to a small sample of commercial properties in the city of Bari.
An Application of RST as Automated Valuation Methodology to Commercial Properties. A Case in Bari / D’Amato, Maurizio; Renigier-Biłozor, Malgorzata (STUDIES IN SYSTEMS, DECISION AND CONTROL). - In: Advances in Automated Valuation Modeling: AVM After the Non-Agency Mortgage Crisis / [a cura di] Maurizio d'Amato,Tom Kauko. - Cham, CH : Springer, 2017. - ISBN 978-3-319-49744-0. - pp. 279-302 [10.1007/978-3-319-49746-4_16]
An Application of RST as Automated Valuation Methodology to Commercial Properties. A Case in Bari
Maurizio d’Amato;
2017-01-01
Abstract
The lack or unavailability of data poses one of the greatest obstacles hindering the exploration of real estate market information. Due to the small number of observations (cases), there are limited possibilities of using statistical methods, which are generally based on the assumption of a larger number of cases compared to the data describing them. This work provides an application of Rough Set Theory to a small sample of commercial properties as an Automatic Valuation Method. RST has been proposed as an automatic procedure for small sample (d’Amato 2002). It may happen in the application of RST that it is possible to deal with small samples. The rough set theory was applied taking into account the specific nature of information referring to the real property market. This theory is dedicated to examine imprecision, generality and unavailability in the process of data analysis that often occurs on the real estate market. It has been highlighted that one of the problem in AVM application may be the scarcity of data (Downie and Robertson 2007). The model allows the opportunity to reach the results of a single point estimate using if then rules providing a causal non deterministic relationship between price and property characteristics. The model has been applied to a small sample of commercial properties in the city of Bari.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
