Pub Date : 2018-01-01DOI: 10.1080/10835547.2018.12090013
Mohsen Bahmani‐Oskooee, Tsung-Pao Wu
Executive Summary We apply a bootstrap panel Granger causality test to examine the causal relation between the housing market and the stock market across 18 OECD countries for the period from 1993:Q1 to 2015:Q4, which accounts for both dependency and heterogeneity across regions. The results provide evidence for the credit-price effect in Belgium and Japan. The wealth effect is supported in Australia, Canada, France, Greece, Portugal, South Korea, Spain, Sweden, and the United Kingdom. A feedback effect was found in Ireland, Italy, Netherlands, and the United States and finally, the neutrality effect was supported in Denmark, Finland, and Germany.
{"title":"On The Relation Between Housing and Stock Markets in 18 OECD Countries: A Bootstrap Panel Causality Test","authors":"Mohsen Bahmani‐Oskooee, Tsung-Pao Wu","doi":"10.1080/10835547.2018.12090013","DOIUrl":"https://doi.org/10.1080/10835547.2018.12090013","url":null,"abstract":"Executive Summary We apply a bootstrap panel Granger causality test to examine the causal relation between the housing market and the stock market across 18 OECD countries for the period from 1993:Q1 to 2015:Q4, which accounts for both dependency and heterogeneity across regions. The results provide evidence for the credit-price effect in Belgium and Japan. The wealth effect is supported in Australia, Canada, France, Greece, Portugal, South Korea, Spain, Sweden, and the United Kingdom. A feedback effect was found in Ireland, Italy, Netherlands, and the United States and finally, the neutrality effect was supported in Denmark, Finland, and Germany.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"45 1","pages":"121-133"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84960909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.1080/10835547.2018.12090016
Nina Rogers, M. Tieslau, I. Karafiath
Executive Summary Real estate returns recurrently show heteroscedasticity. Using Jensen's alpha as a measure of risk-adjusted returns, we compare test statistic sensitivity to alternative estimates of the standard errors. Utilizing several robust estimators, we find the wild bootstrap consistently provides the most conservative result in real estate mutual funds and REITs. Surprisingly, the Newey-West standard error increases the percentage of REITs exhibiting significant alphas. Sensitivity to specification error in the model is examined. Explanatory variables failed to systematically attenuate significant alphas. When using the wild boot-strapped HC3 standard errors, significant alphas in REITs are no greater than random chance. Our results suggest appropriate adjustment for heteroscedasticity in real estate returns would minimize the potential for erroneous interpretation.
{"title":"Significant Alphas in Real Estate Funds: An Empirical Comparison of Alternative Estimators","authors":"Nina Rogers, M. Tieslau, I. Karafiath","doi":"10.1080/10835547.2018.12090016","DOIUrl":"https://doi.org/10.1080/10835547.2018.12090016","url":null,"abstract":"Executive Summary Real estate returns recurrently show heteroscedasticity. Using Jensen's alpha as a measure of risk-adjusted returns, we compare test statistic sensitivity to alternative estimates of the standard errors. Utilizing several robust estimators, we find the wild bootstrap consistently provides the most conservative result in real estate mutual funds and REITs. Surprisingly, the Newey-West standard error increases the percentage of REITs exhibiting significant alphas. Sensitivity to specification error in the model is examined. Explanatory variables failed to systematically attenuate significant alphas. When using the wild boot-strapped HC3 standard errors, significant alphas in REITs are no greater than random chance. Our results suggest appropriate adjustment for heteroscedasticity in real estate returns would minimize the potential for erroneous interpretation.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"17 1","pages":"167-179"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80299645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.1080/10835547.2018.12090018
Randall S. Guttery, S. L. Poe
Executive Summary The cannabis industry is growing rapidly, with a majority of states having passed legislation allowing the use of marijuana in some capacity. Significant challenges exist for those seeking to invest in this industry. An alternative source of financing could be a real estate investment trust (REIT). The investment risk can be spread among many investors, who can offer longer-term and lower interest rate loans than traditional financing. The major downsides to REIT investing are risks related to the fact that marijuana is still illegal under federal law. As REITs must distribute at least 90% of taxable income as shareholder dividends, this leaves minimal capital for expansion and growth.
{"title":"Using a Cannabis Real Estate Investment Trust to Capitalize a Marijuana Business","authors":"Randall S. Guttery, S. L. Poe","doi":"10.1080/10835547.2018.12090018","DOIUrl":"https://doi.org/10.1080/10835547.2018.12090018","url":null,"abstract":"Executive Summary The cannabis industry is growing rapidly, with a majority of states having passed legislation allowing the use of marijuana in some capacity. Significant challenges exist for those seeking to invest in this industry. An alternative source of financing could be a real estate investment trust (REIT). The investment risk can be spread among many investors, who can offer longer-term and lower interest rate loans than traditional financing. The major downsides to REIT investing are risks related to the fact that marijuana is still illegal under federal law. As REITs must distribute at least 90% of taxable income as shareholder dividends, this leaves minimal capital for expansion and growth.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"23 1","pages":"201-206"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87257647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.1080/10835547.2018.12090017
C. Dodd, M. Hill
Executive Summary This study examines the determinants of credit ratings for real estate investment trusts (REITs). Probit and ordered probit results generally suggest reduced ratings (S&P and Fitch) for REITs with greater financial constraints. Higher rated REITs are larger with greater dividends, lower cash holdings, and less volatile dividends. The significance of leverage is conditional on econometric methodology and operating performance measure. Unlike for Fitch, operating performance influences S&P's rating assignments through earnings and not FFO. The latter challenges the credibility of S&P in the effective monitoring of REITs and highlights differences in financial characteristics accounted for by rating agencies.
{"title":"Determinants of REIT Credit Ratings","authors":"C. Dodd, M. Hill","doi":"10.1080/10835547.2018.12090017","DOIUrl":"https://doi.org/10.1080/10835547.2018.12090017","url":null,"abstract":"Executive Summary This study examines the determinants of credit ratings for real estate investment trusts (REITs). Probit and ordered probit results generally suggest reduced ratings (S&P and Fitch) for REITs with greater financial constraints. Higher rated REITs are larger with greater dividends, lower cash holdings, and less volatile dividends. The significance of leverage is conditional on econometric methodology and operating performance measure. Unlike for Fitch, operating performance influences S&P's rating assignments through earnings and not FFO. The latter challenges the credibility of S&P in the effective monitoring of REITs and highlights differences in financial characteristics accounted for by rating agencies.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"19 1","pages":"181-199"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84236900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.1080/10835547.2018.12090008
Steven P. Rich, John T. Rose, Charles J. Delaney
Executive Summary While the finance discipline focuses on the added value of a capital investment project to the firm's assets (NPVA), the real estate discipline typically looks at the impact on the firm's equity investors (NPVE). The two approaches will generate the same value provided that the project and the firm are equally leveraged. However, if the project's capital structure differs from that of the firm, NPVE will differ from NPVA. This study explores the effect of different capital structures for the project and the firm in three scenarios—a single-year project, a project generating a single cash flow multiple years into the future, and a project generating multi-year cash flows— and the resultant discrepancy between NPVE and NPVA. Using two adjustment routes, we show that NPVE can be recalculated to equal NPVA in each scenario, although the adjustment process is complicated, particularly in the more complex scenarios.
{"title":"Net Present Value Analysis in Finance and Real Estate: A Clash of Methodologies","authors":"Steven P. Rich, John T. Rose, Charles J. Delaney","doi":"10.1080/10835547.2018.12090008","DOIUrl":"https://doi.org/10.1080/10835547.2018.12090008","url":null,"abstract":"Executive Summary While the finance discipline focuses on the added value of a capital investment project to the firm's assets (NPVA), the real estate discipline typically looks at the impact on the firm's equity investors (NPVE). The two approaches will generate the same value provided that the project and the firm are equally leveraged. However, if the project's capital structure differs from that of the firm, NPVE will differ from NPVA. This study explores the effect of different capital structures for the project and the firm in three scenarios—a single-year project, a project generating a single cash flow multiple years into the future, and a project generating multi-year cash flows— and the resultant discrepancy between NPVE and NPVA. Using two adjustment routes, we show that NPVE can be recalculated to equal NPVA in each scenario, although the adjustment process is complicated, particularly in the more complex scenarios.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"15 1","pages":"83-94"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75484452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.1080/10835547.2018.12090006
M. Drew, Adam N. Walk, J. West
We investigate the per- formance of allocations to public and private real estate using dynamic retirement portfolio strate- gies. Our approach frames asset allocation decisions to real estate with the primary objective of maxi- mizing retirement outcomes. The main innovation in this paper is that allocations to listed and un- listed real estate are formally incorporated into a dynamic framework that can be implemented by defined contribution (DC) retirement plans. We demonstrate that the time-variant characteristics of real estate as an asset class can be systematically exploited to improve the risk-return trade-offs in retirement portfolios through the lifecycle of a DC plan member.
{"title":"Time Variation in the Allocation to Real Estate Assets through the Life Cycle","authors":"M. Drew, Adam N. Walk, J. West","doi":"10.1080/10835547.2018.12090006","DOIUrl":"https://doi.org/10.1080/10835547.2018.12090006","url":null,"abstract":"We investigate the per- formance of allocations to public and private real estate using dynamic retirement portfolio strate- gies. Our approach frames asset allocation decisions to real estate with the primary objective of maxi- mizing retirement outcomes. The main innovation in this paper is that allocations to listed and un- listed real estate are formally incorporated into a dynamic framework that can be implemented by defined contribution (DC) retirement plans. We demonstrate that the time-variant characteristics of real estate as an asset class can be systematically exploited to improve the risk-return trade-offs in retirement portfolios through the lifecycle of a DC plan member.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"106 1","pages":"51-64"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77884742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-04DOI: 10.1080/10835547.2017.12089994
Stephen Lee
Executive Summary. Portfolio diversification is a fundamental tenet of modern portfolio theory. Statman and Scheid (2008), however, argue that while correlation is the common indicator of diversifi...
{"title":"Mind the Gap in REITs","authors":"Stephen Lee","doi":"10.1080/10835547.2017.12089994","DOIUrl":"https://doi.org/10.1080/10835547.2017.12089994","url":null,"abstract":"Executive Summary. Portfolio diversification is a fundamental tenet of modern portfolio theory. Statman and Scheid (2008), however, argue that while correlation is the common indicator of diversifi...","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"30 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89565498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-04DOI: 10.1080/10835547.2017.12089997
W. Miles
Executive Summary. Although both housing and stock values have been studied for their impacts on consumer spending, as well as their effects on financial institutions, capital spending, and the macroeconomy, there have been few studies on how the two assets co-move. In this study, I apply the dynamic conditional correlation (DCC) generalized autoregressive conditional heteroscedasticity (GARCH) model to housing and stock values in the G-7 countries (except Japan, where time series properties inhibit parameter convergence). I find that correlations increased sharply after the 2007 crisis, and that co-movement spiked during the recessions of the 1980s. This indicates that the financial turmoil of a contraction pushes returns on the two assets closer together (and down). Real estate investors and other financial institutions with exposure to both markets will want to prepare and set capital and liquidity standards with the potential for such a “double hit” in mind.
{"title":"Home Value and Equity Co-Movement: A Dynamic Approach for G-7 Countries","authors":"W. Miles","doi":"10.1080/10835547.2017.12089997","DOIUrl":"https://doi.org/10.1080/10835547.2017.12089997","url":null,"abstract":"Executive Summary. Although both housing and stock values have been studied for their impacts on consumer spending, as well as their effects on financial institutions, capital spending, and the macroeconomy, there have been few studies on how the two assets co-move. In this study, I apply the dynamic conditional correlation (DCC) generalized autoregressive conditional heteroscedasticity (GARCH) model to housing and stock values in the G-7 countries (except Japan, where time series properties inhibit parameter convergence). I find that correlations increased sharply after the 2007 crisis, and that co-movement spiked during the recessions of the 1980s. This indicates that the financial turmoil of a contraction pushes returns on the two assets closer together (and down). Real estate investors and other financial institutions with exposure to both markets will want to prepare and set capital and liquidity standards with the potential for such a “double hit” in mind.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"2 1","pages":"51-71"},"PeriodicalIF":0.0,"publicationDate":"2017-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78757643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-04DOI: 10.1080/10835547.2017.12089998
Michael Giliberto, David Shulman
Executive Summary. In this study, we evaluate interest rate sensitivity for equity real estate investment trusts (REITs) using a multi-factor asset pricing model estimated with daily data. We utilize yield changes and, as an alternative, bond betas, to measure REITs' sensitivity to interest rate shifts.We find that the degree of interest rate sensitivity varies over time, has switched direction, and that any “pure” effect is often subsumed in equity REITs beta against stocks. Despite recent high sensitivity, we conclude that there is no long-run predictive rule that applies to how equity REIT returns respond to movements in interest rates.
{"title":"On the Interest Rate Sensitivity of REITs: Evidence from Twenty Years of Daily Data","authors":"Michael Giliberto, David Shulman","doi":"10.1080/10835547.2017.12089998","DOIUrl":"https://doi.org/10.1080/10835547.2017.12089998","url":null,"abstract":"Executive Summary. In this study, we evaluate interest rate sensitivity for equity real estate investment trusts (REITs) using a multi-factor asset pricing model estimated with daily data. We utilize yield changes and, as an alternative, bond betas, to measure REITs' sensitivity to interest rate shifts.We find that the degree of interest rate sensitivity varies over time, has switched direction, and that any “pure” effect is often subsumed in equity REITs beta against stocks. Despite recent high sensitivity, we conclude that there is no long-run predictive rule that applies to how equity REIT returns respond to movements in interest rates.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"14 1","pages":"7-20"},"PeriodicalIF":0.0,"publicationDate":"2017-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76781654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-01DOI: 10.1080/10835547.2017.12089995
Hong Zhang, Shuai Gao, Michael J. Seiler
Executive Summary. By way of input-output analysis, we express China's real estate industry position in terms of its industry linkage effect, industry spread effect, and industry clusters division. Using China's 42 sector input-output table, related economic indexes are quantitatively examined. From an industry linkage effect standpoint, the direct driving force from the real estate industry primarily acts on the tertiary industry and is the total driving force behind the secondary industry. Direct pulling power uniformly applies to both the secondary and tertiary industries, and total pulling power mainly acts on the secondary industry. As far as the industry spread effect is concerned, China's real estate industry shows a slight pulling effect and a promotional effect on the national economy. Based on an industry clusters divisional analysis, the real estate industry in China is a final demand and basic industry.
{"title":"Positioning of China's Real Estate Industry Based on Input-Output Analysis","authors":"Hong Zhang, Shuai Gao, Michael J. Seiler","doi":"10.1080/10835547.2017.12089995","DOIUrl":"https://doi.org/10.1080/10835547.2017.12089995","url":null,"abstract":"Executive Summary. By way of input-output analysis, we express China's real estate industry position in terms of its industry linkage effect, industry spread effect, and industry clusters division. Using China's 42 sector input-output table, related economic indexes are quantitatively examined. From an industry linkage effect standpoint, the direct driving force from the real estate industry primarily acts on the tertiary industry and is the total driving force behind the secondary industry. Direct pulling power uniformly applies to both the secondary and tertiary industries, and total pulling power mainly acts on the secondary industry. As far as the industry spread effect is concerned, China's real estate industry shows a slight pulling effect and a promotional effect on the national economy. Based on an industry clusters divisional analysis, the real estate industry in China is a final demand and basic industry.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"18 1","pages":"21-33"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80092342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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