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\hypersetup{pdftitle={Does the Sales Comparison Approach Actually Work? A Large-Scale Point-in-Time Validation of Comparable Selection, Price Adjustments, and Value Reconciliation}, pdfauthor={Simon-Pierre Boucher}}

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\newcommand{\WPnumber}{16}
\newcommand{\WPtitle}{Does the Sales Comparison Approach Actually Work? A Large-Scale Point-in-Time Validation of Comparable Selection, Price Adjustments, and Value Reconciliation}
\newcommand{\WPsubtitle}{Evidence from 391,000 Single-Family Transactions in Quebec, 2021--2026}
\newcommand{\WPdate}{October 2026}
\newcommand{\WPversion}{1.0}
\newcommand{\WPabstract}{%
  The sales comparison approach is the dominant method of residential valuation, yet its operating rules---how many comparables to use, how far and how far back to search, which adjustments to apply, how to weight and reconcile---rest largely on professional convention. We subject these rules to a large-scale, point-in-time backtest on \nSalesClean{} arm's-length single-family transactions in Quebec (2021--2026) matched to the municipal assessment roll. For each of \nTargetsAll{} target sales in 2024--2026, the price is masked and \nConfigs{} configurations of the approach---together with hedonic, gradient-boosting, assessment-ratio and hybrid benchmarks---are applied using only information available on the valuation date; configurations are selected on 2024 and evaluated out of sample on 2025--2026. Adjustments dominate: the median absolute error of the five nearest sales falls from \mdapeMtwo{} with a time adjustment only to \mdapeMseven{} with a hedonic adjustment grid, and a stylized conventional grid captures most of that gain. Selecting physically similar rather than merely nearby comparables delivers a comparable gain without any adjustment. The optimal number of comparables is well above the conventional three---around twenty once a grid is applied, with no penalty up to fifty---and short time windows are dominated; the search radius matters far less than the number and similarity of the sales retained. Weighting and reconciliation rules matter little. The best transparent configuration chosen in 2024 reaches \mdapeMzero{} out of sample, against \mdapeMelevenB{} for a quarterly-retrained gradient-boosting model that uses the assessed value and \mdapeMtwelve{} for a hybrid; the cost of transparency is small and narrows in homogeneous submarkets. Accuracy is governed primarily by submarket liquidity; a wide-net rule that retains the most similar sales is self-adapting, and stratum-specific rules do not improve on it. The results turn a convention-based method into a set of empirically validated, reproducible rules.
}
\newcommand{\WPkeywords}{sales comparison approach, comparable selection, adjustment grid, automated valuation models, hedonic pricing, backtesting, residential real estate, Quebec}
\newcommand{\WPjel}{R31, R32, C52, C53, G12}

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\newcommand{\WPauthor}{Simon-Pierre Boucher}
\newcommand{\WPaffiliation}{%
  Département des sciences administratives\\
  Université du Québec en Outaouais%
}
\newcommand{\WPemail}{simon-pierre.boucher@uqo.ca}
\newcommand{\WPaddress}{%
  Gatineau -- Pavillon Alexandre-Taché\\
  283, boulevard Alexandre-Taché\\
  Gatineau, Québec, Canada J9A 1L8%
}

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