Pub Date : 2016-01-01DOI: 10.1080/10835547.2016.12089989
Jocelyn D. Evans, T. Jones, G. Mitchener
Executive Summary. In this paper, we present a mathematical simulation of a secondary equity offer (SEO) decision that captures the payoffs for investors with either low (e.g., actively managed funds) or high (e.g., passive index investors) monitoring costs. The calibrated solutions are consistent with overvalued SEOs being issued when institutions with high monitoring costs are present. Institutions with low monitoring costs either incentivize management to issue fairly priced SEOs or lead to greater ex post discipline of the CEO for value decreasing issuances. The existence of institutions with business relationships creates uncertainty regarding the value of SEOs. Ownership network alliances are beneficial.
{"title":"An Ownership Framework for Managers' Accelerated Seo Decisions: The Importance of Connected Institutional Investors in the Reit Industry","authors":"Jocelyn D. Evans, T. Jones, G. Mitchener","doi":"10.1080/10835547.2016.12089989","DOIUrl":"https://doi.org/10.1080/10835547.2016.12089989","url":null,"abstract":"Executive Summary. In this paper, we present a mathematical simulation of a secondary equity offer (SEO) decision that captures the payoffs for investors with either low (e.g., actively managed funds) or high (e.g., passive index investors) monitoring costs. The calibrated solutions are consistent with overvalued SEOs being issued when institutions with high monitoring costs are present. Institutions with low monitoring costs either incentivize management to issue fairly priced SEOs or lead to greater ex post discipline of the CEO for value decreasing issuances. The existence of institutions with business relationships creates uncertainty regarding the value of SEOs. Ownership network alliances are beneficial.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73047769","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 : 2016-01-01DOI: 10.1080/10835547.2016.12089991
R. D. Evans, Andrew G. Mueller
Executive Summary. Relatively low-level Markov chain methods and widely available information allow this extension of real estate cycle risk analysis to office portfolios across cities initially in different cycle conditions. Examples include evaluation of cycle conditions at the end of a holding period and for cash flows from operations across a span of quarters. Standard spreadsheet functions serve to provide examples of changes in real estate cycle prospects, including before/after changes in portfolio weights, applying mean-variance dominance, mean-semivariance dominance, and stochastic dominance analysis.
{"title":"Forecasting Real Estate Cycle Risks in Portfolios of Office Properties Across Cities","authors":"R. D. Evans, Andrew G. Mueller","doi":"10.1080/10835547.2016.12089991","DOIUrl":"https://doi.org/10.1080/10835547.2016.12089991","url":null,"abstract":"Executive Summary. Relatively low-level Markov chain methods and widely available information allow this extension of real estate cycle risk analysis to office portfolios across cities initially in different cycle conditions. Examples include evaluation of cycle conditions at the end of a holding period and for cash flows from operations across a span of quarters. Standard spreadsheet functions serve to provide examples of changes in real estate cycle prospects, including before/after changes in portfolio weights, applying mean-variance dominance, mean-semivariance dominance, and stochastic dominance analysis.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88172371","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 : 2016-01-01DOI: 10.1080/10835547.2016.12089981
R. D. Evans, Andrew G. Mueller
Executive Summary Adding a stochastic element to a well-understood real estate cycle model offers opportunities like those seen in earlier such syntheses of real estate analysis and statistics. The discrete real estate cycle points in the model require a discrete probability model, here a first order Markov chain. Many statistical applications flow from the combined model. Three Markov chain count variables have obvious real estate cycle appeal. Staying time, first recurrence time, and first passage time already exist in the Markov chain literature but only staying time is in the real estate cycle literature. The most fundamental innovation is in probabilistic forecasting. Being able to describe real estate cycle risk, cycle point by cycle point many quarters ahead, could improve evaluation of prospects for property disposal. It is also a simple spreadsheet application to describe real estate cycle risks that influence cash flows from operations across four-quarter spans.
{"title":"Industrial Real Estate Cycles: Markov Chain Applications","authors":"R. D. Evans, Andrew G. Mueller","doi":"10.1080/10835547.2016.12089981","DOIUrl":"https://doi.org/10.1080/10835547.2016.12089981","url":null,"abstract":"Executive Summary Adding a stochastic element to a well-understood real estate cycle model offers opportunities like those seen in earlier such syntheses of real estate analysis and statistics. The discrete real estate cycle points in the model require a discrete probability model, here a first order Markov chain. Many statistical applications flow from the combined model. Three Markov chain count variables have obvious real estate cycle appeal. Staying time, first recurrence time, and first passage time already exist in the Markov chain literature but only staying time is in the real estate cycle literature. The most fundamental innovation is in probabilistic forecasting. Being able to describe real estate cycle risk, cycle point by cycle point many quarters ahead, could improve evaluation of prospects for property disposal. It is also a simple spreadsheet application to describe real estate cycle risks that influence cash flows from operations across four-quarter spans.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89814395","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 : 2015-10-20DOI: 10.1080/10835547.2015.12089968
B. Case
Executive Summary NCREIF has published performance data covering a 25-year historical period for institutional investments following core, value-add, and opportunistic strategies in private equity real estate assets. In this paper, I summarize salient observations regarding capital appreciation, income, fees and expenses, the income share of total return, the effects of cash reserves and leverage, net total returns, systematic risk, and risk-adjusted performance during five informative market periods: two severe real estate market downturns, one complete real estate bull market, and two incomplete bull market periods. The available data challenge several points of conventional wisdom regarding private equity real estate returns.
{"title":"What Have 25 Years of Performance Data Taught Us About Private Equity Real Estate","authors":"B. Case","doi":"10.1080/10835547.2015.12089968","DOIUrl":"https://doi.org/10.1080/10835547.2015.12089968","url":null,"abstract":"Executive Summary NCREIF has published performance data covering a 25-year historical period for institutional investments following core, value-add, and opportunistic strategies in private equity real estate assets. In this paper, I summarize salient observations regarding capital appreciation, income, fees and expenses, the income share of total return, the effects of cash reserves and leverage, net total returns, systematic risk, and risk-adjusted performance during five informative market periods: two severe real estate market downturns, one complete real estate bull market, and two incomplete bull market periods. The available data challenge several points of conventional wisdom regarding private equity real estate returns.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84682966","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 : 2015-02-28DOI: 10.5555/1083-5547-21.1.53
N. Antonakakis, Rangan Gupta, C. André
We examine dynamic correlations between housing market returns and economic policy uncertainty in the United States. Our findings suggest that correlations are time-varying and sensitive to economic fundamentals and US recessions.
{"title":"Dynamic co-movements between economic policy uncertainty and housing market returns","authors":"N. Antonakakis, Rangan Gupta, C. André","doi":"10.5555/1083-5547-21.1.53","DOIUrl":"https://doi.org/10.5555/1083-5547-21.1.53","url":null,"abstract":"We examine dynamic correlations between housing market returns and economic policy uncertainty in the United States. Our findings suggest that correlations are time-varying and sensitive to economic fundamentals and US recessions.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89568590","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 : 2015-01-01DOI: 10.1080/10835547.2015.12089972
B. Mei
Executive Summary Based on asset values of different business segments, I derive a pure-play timberland return index using monthly data of public timber firms for the 2010–2014 period. Returns on public timber firms are first unleveraged and then regressed on the holding percentages of each firm' assets in timber and non-timberland business segments. The regression provides pure-play portfolios with specified long and short positions in those public timber firms, with a minimum idiosyncratic volatility, that have pure exposure to the timberland business segment and eliminate all exposure to non-timberland segments. Results reveal that this pure-play index better depicts returns on securitized timberland assets and differs significantly from various NCREIF timberland indices in mean and variance, and that returns of public-market vehicles of timberland investments tend to lead private ones for about one quarter.
{"title":"A Pure-Play Timberland Return Index Based On Securitized Timber Firms","authors":"B. Mei","doi":"10.1080/10835547.2015.12089972","DOIUrl":"https://doi.org/10.1080/10835547.2015.12089972","url":null,"abstract":"Executive Summary Based on asset values of different business segments, I derive a pure-play timberland return index using monthly data of public timber firms for the 2010–2014 period. Returns on public timber firms are first unleveraged and then regressed on the holding percentages of each firm' assets in timber and non-timberland business segments. The regression provides pure-play portfolios with specified long and short positions in those public timber firms, with a minimum idiosyncratic volatility, that have pure exposure to the timberland business segment and eliminate all exposure to non-timberland segments. Results reveal that this pure-play index better depicts returns on securitized timberland assets and differs significantly from various NCREIF timberland indices in mean and variance, and that returns of public-market vehicles of timberland investments tend to lead private ones for about one quarter.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89678352","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 : 2015-01-01DOI: 10.5555/1083-5547-21.1.33
W. Miles
Executive Summary Home prices in the United States often exhibit little (and sometimes even negative) correlation across different regions. This reflects segmentation in the national housing market and also provides an apparent opportunity for investors to diversify their exposure to regional downturns by creating residential mortgage-backed securities (RMBSs) out of geographically dispersed home loans. Unfortunately, in a crisis, correlations may rise, and the benefits from geographical diversification may disappear just when investors most desire them. Using a flexible generalized autoregressive conditional heteroscedasticity (GARCH) technique, I find that regional correlations indeed rose dramatically during the latest downturn, in some cases to unprecedented levels. Moreover, this increase in co-movement was clearly financial contagion, and not merely interdependence. Investors in mortgage-backed and other housing securities should thus not rely on house price correlations calculated during “normal” t...
{"title":"Contagion versus Interdependence Across Regional U.S. Housing Markets and Implications for RMBS Geographic Diversification Strategy","authors":"W. Miles","doi":"10.5555/1083-5547-21.1.33","DOIUrl":"https://doi.org/10.5555/1083-5547-21.1.33","url":null,"abstract":"Executive Summary Home prices in the United States often exhibit little (and sometimes even negative) correlation across different regions. This reflects segmentation in the national housing market and also provides an apparent opportunity for investors to diversify their exposure to regional downturns by creating residential mortgage-backed securities (RMBSs) out of geographically dispersed home loans. Unfortunately, in a crisis, correlations may rise, and the benefits from geographical diversification may disappear just when investors most desire them. Using a flexible generalized autoregressive conditional heteroscedasticity (GARCH) technique, I find that regional correlations indeed rose dramatically during the latest downturn, in some cases to unprecedented levels. Moreover, this increase in co-movement was clearly financial contagion, and not merely interdependence. Investors in mortgage-backed and other housing securities should thus not rely on house price correlations calculated during “normal” t...","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79115104","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 : 2015-01-01DOI: 10.1080/10835547.2015.12089973
M. N. Razali, T. Sing
In this paper, we evaluate the systematic risks of Islamic real estate invest- ment trusts (REITs) and conventional REITs in Ma- laysia for the period from August 3, 2005 to De- cember 19, 2014. Our results show that IREITs have lower systematic risks than other conven- tional REITs. The results are consistent when sto- chastic betas are estimated using time-varying co- efficient models. We also find that new IREIT entry creates significant risk reduction effects for the con- ventional REIT markets. When we test the effects of the conversion of Axis REIT from a conventional REIT to an IREIT, we find that the systematic risks of Axis REIT significant reduce between the peri- ods ''before'' and ''after'' the conversion. The find- ings imply that the lower betas of IREITs could pro- tect IREIT investors against stock market volatilities that could not be diversified away.
{"title":"Systematic Risk of Islamic REITs and Conventional REITs in Malaysia","authors":"M. N. Razali, T. Sing","doi":"10.1080/10835547.2015.12089973","DOIUrl":"https://doi.org/10.1080/10835547.2015.12089973","url":null,"abstract":"In this paper, we evaluate the systematic risks of Islamic real estate invest- ment trusts (REITs) and conventional REITs in Ma- laysia for the period from August 3, 2005 to De- cember 19, 2014. Our results show that IREITs have lower systematic risks than other conven- tional REITs. The results are consistent when sto- chastic betas are estimated using time-varying co- efficient models. We also find that new IREIT entry creates significant risk reduction effects for the con- ventional REIT markets. When we test the effects of the conversion of Axis REIT from a conventional REIT to an IREIT, we find that the systematic risks of Axis REIT significant reduce between the peri- ods ''before'' and ''after'' the conversion. The find- ings imply that the lower betas of IREITs could pro- tect IREIT investors against stock market volatilities that could not be diversified away.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75242187","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 : 2014-08-15DOI: 10.1080/10835547.2014.12089961
Pin-te Lin, F. Fuerst
In this study, we apply a Lagrange multiplier (LM) test for the autoregressive conditional heteroscedasticity (ARCH) effects and an exponential generalized autoregressive conditional heteroscedasticity-in-mean (EGARCH-M) model to assess whether regional house prices in Canada exhibit financial characteristics similar to stock indices. Volatility clustering, positive risk-return relationships, and leverage effects are empirically shown to exist in the majority of provincial housing markets of Canada. These volatility behaviors, which reflect regional idiosyncrasies, are further found to differ across provinces. More densely populated provinces exhibit stronger volatility clustering of house prices. The existence of these volatility patterns similar to stock indices has important implications ranging from proper portfolio management to government policy.
{"title":"Volatility Clustering, Risk-Return Relationship, and Asymmetric Adjustment in the Canadian Housing Market","authors":"Pin-te Lin, F. Fuerst","doi":"10.1080/10835547.2014.12089961","DOIUrl":"https://doi.org/10.1080/10835547.2014.12089961","url":null,"abstract":"In this study, we apply a Lagrange multiplier (LM) test for the autoregressive conditional heteroscedasticity (ARCH) effects and an exponential generalized autoregressive conditional heteroscedasticity-in-mean (EGARCH-M) model to assess whether regional house prices in Canada exhibit financial characteristics similar to stock indices. Volatility clustering, positive risk-return relationships, and leverage effects are empirically shown to exist in the majority of provincial housing markets of Canada. These volatility behaviors, which reflect regional idiosyncrasies, are further found to differ across provinces. More densely populated provinces exhibit stronger volatility clustering of house prices. The existence of these volatility patterns similar to stock indices has important implications ranging from proper portfolio management to government policy.","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89221971","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 : 2014-08-15DOI: 10.1080/10835547.2014.12089964
E. Malizia
This analysis of central business districts (CBDs) and their suburban areas was inspired by the analysis of 24-hour cities by Kelly, Adair, McGreal, and Roulac (2013). The 44 cities are drawn from the 50 largest U.S. metro areas and include 24 of the 26 markets in the Kelly, Adair, McGreal, and Roulac article. Downtowns like the seven 24-hour cities offer live-workplay (LWP) environments that appear to be attracting young talent and tech-oriented companies. LWP places are compact, dense, connected, mixed use, diverse, and walkable with destinations, public spaces, and critical mass. Research conducted for NAIOP defined places with these features as ‘‘vibrant centers.’’ Subsequent work produced an index with nine face-valid measures of vibrancy for 65 cities. This analysis determines the extent to which the vibrancy index values are associated with the area-specific performance of office properties in these 44 large markets. The results indicate that strong associations do exist between downtown vibrancy a...
对中央商务区(cbd)及其郊区的分析受到Kelly、Adair、McGreal和Roulac(2013)对24小时城市的分析的启发。这44个城市是从美国50个最大的都市区中抽取的，包括凯利、阿代尔、麦克格里尔和鲁拉克文章中26个市场中的24个。像7个24小时城市这样的市中心提供了live-work - play (LWP)环境，似乎正在吸引年轻人才和技术型公司。LWP场所紧凑、密集、连接、混合使用、多样化，具有目的地、公共空间和临界质量，适合步行。为NAIOP进行的研究将具有这些特征的地方定义为“充满活力的中心”。随后的工作产生了一个包含65个城市的9个表面有效的活力指标的指数。该分析确定了在这44个大型市场中，活力指数值与办公物业的特定区域性能的关联程度。结果表明，市区活力与城市发展之间存在着强烈的联系。
{"title":"Point of view office property performance in live-work-play places","authors":"E. Malizia","doi":"10.1080/10835547.2014.12089964","DOIUrl":"https://doi.org/10.1080/10835547.2014.12089964","url":null,"abstract":"This analysis of central business districts (CBDs) and their suburban areas was inspired by the analysis of 24-hour cities by Kelly, Adair, McGreal, and Roulac (2013). The 44 cities are drawn from the 50 largest U.S. metro areas and include 24 of the 26 markets in the Kelly, Adair, McGreal, and Roulac article. Downtowns like the seven 24-hour cities offer live-workplay (LWP) environments that appear to be attracting young talent and tech-oriented companies. LWP places are compact, dense, connected, mixed use, diverse, and walkable with destinations, public spaces, and critical mass. Research conducted for NAIOP defined places with these features as ‘‘vibrant centers.’’ Subsequent work produced an index with nine face-valid measures of vibrancy for 65 cities. This analysis determines the extent to which the vibrancy index values are associated with the area-specific performance of office properties in these 44 large markets. The results indicate that strong associations do exist between downtown vibrancy a...","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77758543","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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