Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach
This article carries out an asset‐pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross‐sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tend...
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Veröffentlicht in: | Real estate economics 2006-12, Vol.34 (4), p.519-552 |
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description | This article carries out an asset‐pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross‐sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross‐sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset‐pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return‐volatility‐price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner‐occupied housing, gross rent and population density. |
doi_str_mv | 10.1111/j.1540-6229.2006.00177.x |
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We use ZIP code–level housing data to study the cross‐sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross‐sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset‐pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. 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Miller, Norman G. ; Pandher, Gurupdesh S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5767-6e57dddb93c0ae02219d73d2c61df1da5844a378a35fe4360ac93adb530247c23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Capital assets</topic><topic>Correlation analysis</topic><topic>Dwellings</topic><topic>Economic aspects</topic><topic>Employment</topic><topic>Evaluation</topic><topic>Family income</topic><topic>Households</topic><topic>Housing</topic><topic>Housing prices</topic><topic>Influence</topic><topic>Investments</topic><topic>Metropolitan areas</topic><topic>Neighborhoods</topic><topic>Population density</topic><topic>Postal codes</topic><topic>Price levels</topic><topic>Prices</topic><topic>Property values</topic><topic>Rate of return</topic><topic>Rates of return</topic><topic>Real estate</topic><topic>Risk</topic><topic>Risk assessment</topic><topic>Securities markets</topic><topic>Stock exchanges</topic><topic>Studies</topic><topic>Volatility</topic><topic>Volatility (Finance)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cannon, Susanne</creatorcontrib><creatorcontrib>Miller, Norman G.</creatorcontrib><creatorcontrib>Pandher, Gurupdesh S.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Research Library</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Research Library China</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Real estate economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cannon, Susanne</au><au>Miller, Norman G.</au><au>Pandher, Gurupdesh S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach</atitle><jtitle>Real estate economics</jtitle><date>2006-12-01</date><risdate>2006</risdate><volume>34</volume><issue>4</issue><spage>519</spage><epage>552</epage><pages>519-552</pages><issn>1080-8620</issn><eissn>1540-6229</eissn><abstract>This article carries out an asset‐pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross‐sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross‐sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset‐pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return‐volatility‐price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner‐occupied housing, gross rent and population density.</abstract><cop>Malden, USA</cop><pub>Blackwell Publishing Inc</pub><doi>10.1111/j.1540-6229.2006.00177.x</doi><tpages>34</tpages></addata></record> |
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subjects | Capital assets Correlation analysis Dwellings Economic aspects Employment Evaluation Family income Households Housing Housing prices Influence Investments Metropolitan areas Neighborhoods Population density Postal codes Price levels Prices Property values Rate of return Rates of return Real estate Risk Risk assessment Securities markets Stock exchanges Studies Volatility Volatility (Finance) |
title | Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach |
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