Are factor characteristics more informative when compared with the entire investment universe or a relevant subset of peers? Motivated by a belief that the answer is dependent on the identity of the peer groups used, this article provides a novel perspective on this longstanding question by using clusters derived from stock returns in place of the industrial and geographical peer groups typically used by investors. The author presents empirical results in support of the use of return-derived clusters, with a key finding being that the optimal set of peer groups varies by investment universe and period and that standard classification taxonomies that fail to account for these nuances are, on average, inferior to a simple data-driven approach that does take them into account.
{"title":"Peer Group Identification in Factor Portfolios: A Data-Driven Approach","authors":"Ross French","doi":"10.3905/jpm.2023.1.566","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.566","url":null,"abstract":"Are factor characteristics more informative when compared with the entire investment universe or a relevant subset of peers? Motivated by a belief that the answer is dependent on the identity of the peer groups used, this article provides a novel perspective on this longstanding question by using clusters derived from stock returns in place of the industrial and geographical peer groups typically used by investors. The author presents empirical results in support of the use of return-derived clusters, with a key finding being that the optimal set of peer groups varies by investment universe and period and that standard classification taxonomies that fail to account for these nuances are, on average, inferior to a simple data-driven approach that does take them into account.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"244 ","pages":"149 - 173"},"PeriodicalIF":1.4,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139203290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fixed income markets present unique considerations that many believe make the space prohibitive to factor investing. Examples include high transaction costs, limitations on shorting instruments, and the highly diverse set of constraints credit portfolio managers often consider during construction—potentially “washing out” any factor exposures. Despite these challenges, the authors document significant performance for style factors created using simple construction rules applied across US investment grade, US high yield, and emerging market bonds. The authors conclude with two case studies that investigate the level of factor exposure for active fixed income funds to demonstrate a success story and highlight opportunities for funds that lack factor exposure.
{"title":"Fixed Income Factors: Theory and Practice","authors":"Benton Chambers, Reed McDonnell, Nancy Razzouk, Noelle Corum","doi":"10.3905/jpm.2023.1.564","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.564","url":null,"abstract":"Fixed income markets present unique considerations that many believe make the space prohibitive to factor investing. Examples include high transaction costs, limitations on shorting instruments, and the highly diverse set of constraints credit portfolio managers often consider during construction—potentially “washing out” any factor exposures. Despite these challenges, the authors document significant performance for style factors created using simple construction rules applied across US investment grade, US high yield, and emerging market bonds. The authors conclude with two case studies that investigate the level of factor exposure for active fixed income funds to demonstrate a success story and highlight opportunities for funds that lack factor exposure.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"58 7 1","pages":"41 - 54"},"PeriodicalIF":1.4,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139198851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article sets forth a practical framework for incorporating tax management into long-only factor investing and assessing the impact on tax efficiency and pre-tax returns. The framework premise is that investor views on the factor risk premium are represented by a tax-oblivious model portfolio. The model portfolio is then implemented in a separately managed account (SMA) by utilizing optimized, tax-efficient trading. The authors rigorously evaluate the impact of tax-managed model implementation on expected excess returns and risk on a both a pre-tax and after-tax basis. In particular, they extend the standard framework for covariance-based risk attribution to incorporate expected factor alphas and tax impacts. They find that tax-managed model implementation provides a boost to after-tax returns, more than fully mitigating model portfolio tax drag in most cases. Importantly, they also find that tax-managed model implementation does not degrade the capture of the factor premium, neither eroding the factor alpha nor meaningfully increasing risk of pre-tax underperformance relative to the benchmark.
{"title":"Factor Investing for Taxable Investors","authors":"Ben Davis, Tianchuan Li, Vassilii Nemtchinov","doi":"10.3905/jpm.2023.1.559","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.559","url":null,"abstract":"This article sets forth a practical framework for incorporating tax management into long-only factor investing and assessing the impact on tax efficiency and pre-tax returns. The framework premise is that investor views on the factor risk premium are represented by a tax-oblivious model portfolio. The model portfolio is then implemented in a separately managed account (SMA) by utilizing optimized, tax-efficient trading. The authors rigorously evaluate the impact of tax-managed model implementation on expected excess returns and risk on a both a pre-tax and after-tax basis. In particular, they extend the standard framework for covariance-based risk attribution to incorporate expected factor alphas and tax impacts. They find that tax-managed model implementation provides a boost to after-tax returns, more than fully mitigating model portfolio tax drag in most cases. Importantly, they also find that tax-managed model implementation does not degrade the capture of the factor premium, neither eroding the factor alpha nor meaningfully increasing risk of pre-tax underperformance relative to the benchmark.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"5 1","pages":"55 - 73"},"PeriodicalIF":1.4,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139266548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study analyzes the return–risk metrics of real estate security tokens as digital representatives of fractional ownership in physical properties. The author uses approximately 40,000 pricing data points for 180 tokenized properties in the United States between 2019 and 2022 to construct a monthly index. This index is used in various analyses to see whether the tokens’ returns follow the performance of the underlying markets for housing, securitized real estate, stock, and cryptocurrency. The token index shows no clear pattern of similarity to other asset classes and has its own return–risk pattern. The principal component analysis shows that debt and macroeconomic factors are the major drivers and that the crypto market and housing market are of minor importance in explaining variation in returns. This absence of a clear linear relationship with other assets makes real estate tokens attractive as diversifiers in a multiasset portfolio. However, investors looking for an alternative investment vehicle for the real estate asset class cannot rely on tokenized real estate.
{"title":"Return–Risk Analysis of Real Estate Tokens: An Asset Class of Its Own","authors":"Bertram I. Steininger","doi":"10.3905/jpm.2023.1.540","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.540","url":null,"abstract":"This study analyzes the return–risk metrics of real estate security tokens as digital representatives of fractional ownership in physical properties. The author uses approximately 40,000 pricing data points for 180 tokenized properties in the United States between 2019 and 2022 to construct a monthly index. This index is used in various analyses to see whether the tokens’ returns follow the performance of the underlying markets for housing, securitized real estate, stock, and cryptocurrency. The token index shows no clear pattern of similarity to other asset classes and has its own return–risk pattern. The principal component analysis shows that debt and macroeconomic factors are the major drivers and that the crypto market and housing market are of minor importance in explaining variation in returns. This absence of a clear linear relationship with other assets makes real estate tokens attractive as diversifiers in a multiasset portfolio. However, investors looking for an alternative investment vehicle for the real estate asset class cannot rely on tokenized real estate.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"49 1","pages":"83 - 102"},"PeriodicalIF":1.4,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48146063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The built environment carries an outsized environmental footprint, and aspects such as energy consumption impact the bottom line of commercial real estate (CRE) investors. A large portion of CRE assets are owned and operated by both private equity real estate (PERE) funds and listed property companies (REITs). Therefore, the extent to which these public and private entities integrate sustainability considerations into their investment and operating decisions may impact both the environmental and financial performance for the organizations as well as the environmental performance of the broader market. We provide a comprehensive analysis comparing the sustainability performance of REIT and PERE firms/funds, as well as an analysis of the relationship between sustainability and the financial performance of REITs. Results indicate that private and public CRE entities now seem on par in their integration of sustainability into firm/fund management and policies. However, the performance aspect of sustainability is stronger for REITs. Examination of REIT financial performance indicates that higher levels of sustainability disclosure are associated with enhanced operating performance and firm valuation, as well as a higher propensity for holding environmentally certified buildings.
{"title":"Sustainability Disclosure and Financial Performance: The Case of Private and Public Real Estate","authors":"Avis Devine, N. Kok, Chongyu Wang","doi":"10.3905/jpm.2023.1.534","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.534","url":null,"abstract":"The built environment carries an outsized environmental footprint, and aspects such as energy consumption impact the bottom line of commercial real estate (CRE) investors. A large portion of CRE assets are owned and operated by both private equity real estate (PERE) funds and listed property companies (REITs). Therefore, the extent to which these public and private entities integrate sustainability considerations into their investment and operating decisions may impact both the environmental and financial performance for the organizations as well as the environmental performance of the broader market. We provide a comprehensive analysis comparing the sustainability performance of REIT and PERE firms/funds, as well as an analysis of the relationship between sustainability and the financial performance of REITs. Results indicate that private and public CRE entities now seem on par in their integration of sustainability into firm/fund management and policies. However, the performance aspect of sustainability is stronger for REITs. Examination of REIT financial performance indicates that higher levels of sustainability disclosure are associated with enhanced operating performance and firm valuation, as well as a higher propensity for holding environmentally certified buildings.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"49 1","pages":"119 - 133"},"PeriodicalIF":1.4,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42173969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lionel Foster, Jacques N. Gordon, Greg Mackinnon, Rachel Mavrothalasitis
The social aspect of environmental, social, and governance issues—the S of ESG—is the least well understood due to common misunderstandings, a lack of clarity in terminology, and the complexity and multidimensional nature of social factors. Nevertheless, all real estate investments are affected by social factors and also, in turn, affect society. Many investors would benefit from incorporating social considerations in their investment strategy, whether or not they consider themselves impact investors. Developing social awareness within the real estate investment process does not need to sacrifice financial returns and can, in some cases, enhance risk–return performance. Because of their complexity, however, any approach to incorporating social factors into investment decisions must be bespoke to the specific investor; there is no off-the-shelf approach that will work for all. Despite the idiosyncratic nature of social considerations, there are certain commonalities that all investors should consider before building a portfolio or program that includes awareness of social implications.
{"title":"Social Awareness in Real Estate Investment: What Should Investors Do about the “S” in ESG?","authors":"Lionel Foster, Jacques N. Gordon, Greg Mackinnon, Rachel Mavrothalasitis","doi":"10.3905/jpm.2023.1.533","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.533","url":null,"abstract":"The social aspect of environmental, social, and governance issues—the S of ESG—is the least well understood due to common misunderstandings, a lack of clarity in terminology, and the complexity and multidimensional nature of social factors. Nevertheless, all real estate investments are affected by social factors and also, in turn, affect society. Many investors would benefit from incorporating social considerations in their investment strategy, whether or not they consider themselves impact investors. Developing social awareness within the real estate investment process does not need to sacrifice financial returns and can, in some cases, enhance risk–return performance. Because of their complexity, however, any approach to incorporating social factors into investment decisions must be bespoke to the specific investor; there is no off-the-shelf approach that will work for all. Despite the idiosyncratic nature of social considerations, there are certain commonalities that all investors should consider before building a portfolio or program that includes awareness of social implications.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"49 1","pages":"24 - 38"},"PeriodicalIF":1.4,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46635513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thomas R. Arnold, Jim Clayton, Frank J. Fabozzi, S. Giliberto, Jacques N. Gordon, Youguo Liang, Greg Mackinnon, Asieh Mansour
The articles contained in the special real estate issue are discussed within the context of three broad trends that are likely to affect the real estate investment industry over the next 20 years: the rise of data science and artificial intelligence, the increasing importance of environmental and social issues to real estate investment, and a broadening of investors’ interest in real estate both geographically and by property sector. Each of these trends has reinforcing effects on the others. Together, these trends appear likely to impact how investment decisions are made, what typical institutional real estate portfolios look like, and how the industry itself is structured. Although it is likely that these forces will have significant impacts, the most impactful trends over the next 20 years might be forces that that no one is even thinking about today.
{"title":"Twenty Years of the Real Estate Special Issue: What Might the Next Twenty Years Bring?","authors":"Thomas R. Arnold, Jim Clayton, Frank J. Fabozzi, S. Giliberto, Jacques N. Gordon, Youguo Liang, Greg Mackinnon, Asieh Mansour","doi":"10.3905/jpm.2023.1.532","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.532","url":null,"abstract":"The articles contained in the special real estate issue are discussed within the context of three broad trends that are likely to affect the real estate investment industry over the next 20 years: the rise of data science and artificial intelligence, the increasing importance of environmental and social issues to real estate investment, and a broadening of investors’ interest in real estate both geographically and by property sector. Each of these trends has reinforcing effects on the others. Together, these trends appear likely to impact how investment decisions are made, what typical institutional real estate portfolios look like, and how the industry itself is structured. Although it is likely that these forces will have significant impacts, the most impactful trends over the next 20 years might be forces that that no one is even thinking about today.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"49 1","pages":"11 - 23"},"PeriodicalIF":1.4,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46769252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editor’s Introduction for 2023 Special Issue on Quantitative Tools for Asset Management","authors":"Frank J. Fabozzi","doi":"10.3905/jpm.2023.1.531","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.531","url":null,"abstract":"","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":" ","pages":"1 - 4"},"PeriodicalIF":1.4,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44499472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The authors propose a new real estate investment class, moderate income rental housing (MIRH). Drawing on multifamily total return performance data from the National Council of Real Estate Fiduciaries (NCREIF), they classify multifamily properties as MIRH or above-MIRH according to whether they offer housing costs affordable to tenants earning less than 80% of median income. MIRH assets are found to offer comparable and favorable return and risk characteristics relative to above-MIRH assets and other investment alternatives. This basic finding is robust nationally, across 11 metros that provide sufficient data coverage, and across three vintage-year cohorts beginning in 2005, 2010, and 2015. Counterintuitively, MIRH assets typically exhibit slightly lower occupancy levels but higher capital expenditures and higher earnings yields over the analysis period (2005 to 2021). A new MIRH asset class aligns with rising interest in ESG investment, as it has posted compelling performance metrics while also providing an affordable rent.
{"title":"ESG Investing: Moderate-Income Rental Housing as a Viable Real Estate Asset Class","authors":"M. Roberts, J. Wegmann","doi":"10.3905/jpm.2023.1.530","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.530","url":null,"abstract":"The authors propose a new real estate investment class, moderate income rental housing (MIRH). Drawing on multifamily total return performance data from the National Council of Real Estate Fiduciaries (NCREIF), they classify multifamily properties as MIRH or above-MIRH according to whether they offer housing costs affordable to tenants earning less than 80% of median income. MIRH assets are found to offer comparable and favorable return and risk characteristics relative to above-MIRH assets and other investment alternatives. This basic finding is robust nationally, across 11 metros that provide sufficient data coverage, and across three vintage-year cohorts beginning in 2005, 2010, and 2015. Counterintuitively, MIRH assets typically exhibit slightly lower occupancy levels but higher capital expenditures and higher earnings yields over the analysis period (2005 to 2021). A new MIRH asset class aligns with rising interest in ESG investment, as it has posted compelling performance metrics while also providing an affordable rent.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"49 1","pages":"103 - 118"},"PeriodicalIF":1.4,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42467141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benedict von Ahlefeldt-Dehn, Juergen Deppner, Eli Beracha, Wolfgang Schaefers
This study proposes a holistic framework for the practical use of automated valuation models (AVMs) in a commercial real estate context that considers both accuracy and interpretability. The authors train a deep neural network (DNN) on a unique sample of more than 400,000 property-quarter observations from the NCREIF Property Index and perform model-agnostic analysis using Shapley Additive exPlanations (SHAP) to provide ex post comprehensibility of the algorithm’s prediction rules. They further assess the extent to which the inner workings of the DNN follow an economic rationale and set out how the proposed methods can add to the understanding of pricing processes in institutional investment markets. By addressing the caveats and illustrating the potential of machine learning in the field of commercial real estate, this article represents another important pillar in the practical use of AVMs.
{"title":"Increasing the Transparency of Pricing Dynamics in the US Commercial Real Estate Market with Interpretable Machine Learning Algorithms","authors":"Benedict von Ahlefeldt-Dehn, Juergen Deppner, Eli Beracha, Wolfgang Schaefers","doi":"10.3905/jpm.2023.1.528","DOIUrl":"https://doi.org/10.3905/jpm.2023.1.528","url":null,"abstract":"This study proposes a holistic framework for the practical use of automated valuation models (AVMs) in a commercial real estate context that considers both accuracy and interpretability. The authors train a deep neural network (DNN) on a unique sample of more than 400,000 property-quarter observations from the NCREIF Property Index and perform model-agnostic analysis using Shapley Additive exPlanations (SHAP) to provide ex post comprehensibility of the algorithm’s prediction rules. They further assess the extent to which the inner workings of the DNN follow an economic rationale and set out how the proposed methods can add to the understanding of pricing processes in institutional investment markets. By addressing the caveats and illustrating the potential of machine learning in the field of commercial real estate, this article represents another important pillar in the practical use of AVMs.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"49 1","pages":"39 - 58"},"PeriodicalIF":1.4,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43403664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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