Valori e Valutazioni (Nov 2024)

OPTIMIZING PROPERTY VALUATION: A SYSTEMATIC APPROACH FOR SELECTING COMPARABLE SALES BASED ON SIMILARITY AND RELIABILITY CRITERIA IN THE MARKET COMPARISON APPROACH

  • Francesca Salvo,
  • Daniela Tavano

DOI
https://doi.org/10.48264/VVSIEV-20243606
Journal volume & issue
Vol. 36
pp. 69 – 100

Abstract

Read online

The Market Comparison Approach (MCA) is the most widely utilized method for assessing a property’s market value. This approach entails comparing the property to a selection of similar properties with known sale prices. It operates on the premise that the market assigns a property’s price in a manner akin to how it prices comparable properties. The accuracy of the MCA is closely linked to the quality of the process used for selecting these comparable properties; the closer the similarities and the more reliable the sale prices, the higher the precision of the assessment. The valuer’s objective is to identify the optimal combination of comparable sales that meet the standards of similarity and reliability. This study introduces a systematic procedure for selecting the most suitable comparable sales, employing quantitative metrics to evaluate both property similarity and the transparency and dependability of their sale prices. The methodology leverages the «Ideal Point Method» operational principles to classify and select the most appropriate comparables. This ensures a thorough and replicable process in choosing reference properties for accurate market value assessment. This research underscores the critical significance of selecting comparable properties, as this choice can substantially influence the diversity of valuation outcomes. With proper evaluation criteria, interpreting and justifying these results can prove easier. The findings from case studies indicate that the MCA demonstrates enhanced effectiveness when applied to a carefully curated selection of comparables based on specific criteria, as evidenced by minimal discrepancies between adjusted prices and reduced forecasting error margins.Additionally, the analysis shows a notable decline in the model’s accuracy as the dataset size increases, attributed to the inclusion of less suitable comparable properties in the valuation process.

Keywords