{"title":"Real Estate Indices and Unsmoothing Techniques","authors":"Urbi Garay","doi":"10.2139/ssrn.3628823","DOIUrl":null,"url":null,"abstract":"Real estate indices are an increasingly important aspect of real estate investment management. The uses of these indices include the estimation of risks and returns for assisting the asset allocation decision-making process, as well as the specification of benchmarks for performance attribution. Performance attribution provides valuable information both for bottom-up investment management (e.g., in the selection of properties or managers) and for top-down investment management (in the determination of allocation to various categories of real estate investments). The two main approaches to indexation are appraisal-based and transaction-based, each of which has its own potential problems. The chapter compares these approaches and reviews many of the most popular real estate indices, which vary in terms of methodology used. The prevalence of a variety of indexation methodologies highlights the fact that all methodologies have nontrivial problems and that real estate analysts should be aware of the challenges associated with each methodology. The first part of this chapter discusses un-smoothing of a price index or return series — the process of removing the effects of smoothing from a data series. It begins by introducing smoothed pricing and the principles of un-smoothing. The chapter also explains transaction noise, which arises when real estate transaction prices contain errors that make those prices less reliable when compared to prices of more liquid assets. For example, the reported transaction prices result from a negotiation process between buyers and sellers and therefore represent one set of possible values from a range of prices that would have been acceptable to both buyers and sellers. Transaction noise is another important technical issue when dealing with real estate indices. Property values are noisy (in the sense that they reflect random error) because empirical real estate values are imprecise indicators of true value. Finally, the chapter discusses the performance of various appraisal-based and transaction-based real estate indices.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"41 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Microeconometric Studies of Housing Markets (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3628823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Real estate indices are an increasingly important aspect of real estate investment management. The uses of these indices include the estimation of risks and returns for assisting the asset allocation decision-making process, as well as the specification of benchmarks for performance attribution. Performance attribution provides valuable information both for bottom-up investment management (e.g., in the selection of properties or managers) and for top-down investment management (in the determination of allocation to various categories of real estate investments). The two main approaches to indexation are appraisal-based and transaction-based, each of which has its own potential problems. The chapter compares these approaches and reviews many of the most popular real estate indices, which vary in terms of methodology used. The prevalence of a variety of indexation methodologies highlights the fact that all methodologies have nontrivial problems and that real estate analysts should be aware of the challenges associated with each methodology. The first part of this chapter discusses un-smoothing of a price index or return series — the process of removing the effects of smoothing from a data series. It begins by introducing smoothed pricing and the principles of un-smoothing. The chapter also explains transaction noise, which arises when real estate transaction prices contain errors that make those prices less reliable when compared to prices of more liquid assets. For example, the reported transaction prices result from a negotiation process between buyers and sellers and therefore represent one set of possible values from a range of prices that would have been acceptable to both buyers and sellers. Transaction noise is another important technical issue when dealing with real estate indices. Property values are noisy (in the sense that they reflect random error) because empirical real estate values are imprecise indicators of true value. Finally, the chapter discusses the performance of various appraisal-based and transaction-based real estate indices.