This article analyzes the factor investment landscape in China A-shares and explores a feasible solution to construct an adaptive multifactor model for stock selection aiming at stable outperformance over the benchmark CSI 300 Index. A diversified factor database, with more than 60 factors across five factor groups, is constructed for factor behavioral study and model preparation. After analyzing and extracting common time-series and cross-sectional factor predictive power characteristics, a dynamic model with monthly factor selection and tilting based on factor predictive power momentum, persistency, and crowdedness measures is proposed and backtested. From January 2013–March 2020, the proposed model has an information ratio of 1.1152 net of transaction costs—a strong outperformance versus the static models and the simple dynamic model using solely factor momentum. This research offers directional insights into multifactor model applications in the A-shares market.
{"title":"Study of Dynamic Multifactor Model Application In China A-Shares","authors":"Ying-hua Lan","doi":"10.3905/joi.2022.1.223","DOIUrl":"https://doi.org/10.3905/joi.2022.1.223","url":null,"abstract":"This article analyzes the factor investment landscape in China A-shares and explores a feasible solution to construct an adaptive multifactor model for stock selection aiming at stable outperformance over the benchmark CSI 300 Index. A diversified factor database, with more than 60 factors across five factor groups, is constructed for factor behavioral study and model preparation. After analyzing and extracting common time-series and cross-sectional factor predictive power characteristics, a dynamic model with monthly factor selection and tilting based on factor predictive power momentum, persistency, and crowdedness measures is proposed and backtested. From January 2013–March 2020, the proposed model has an information ratio of 1.1152 net of transaction costs—a strong outperformance versus the static models and the simple dynamic model using solely factor momentum. This research offers directional insights into multifactor model applications in the A-shares market.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41725023","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 : 2022-01-31DOI: 10.3905/joi.2022.31.2.001
Brian R. Bruce
{"title":"Editor’s Letter","authors":"Brian R. Bruce","doi":"10.3905/joi.2022.31.2.001","DOIUrl":"https://doi.org/10.3905/joi.2022.31.2.001","url":null,"abstract":"","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47345424","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}
This article explores the relation between interest rates, REITs valuation, and future returns. Using a dataset on mortgage and equity REITs that spans the 1993–2019 time period, we investigate whether and to what extend nominal and real interest rates, as well as interest rate quality and term spreads, are related to the valuation of REITs, measured by different metrics, and REITs returns in the medium run. The results of our analysis show that interest rates are related to REITs absolute and relative valuation measures, but the sensitivity of REITs valuation to interest rates depends on their original valuation level. Moreover, we provide evidence that lower nominal interest rates and wide quality interest spreads are positively related to future REITs returns in the medium term.
{"title":"The Effect of Interest Rates on REITs Valuation and Future Returns","authors":"Randy I. Anderson, Eli Beracha, Spencer Propper","doi":"10.3905/joi.2022.1.222","DOIUrl":"https://doi.org/10.3905/joi.2022.1.222","url":null,"abstract":"This article explores the relation between interest rates, REITs valuation, and future returns. Using a dataset on mortgage and equity REITs that spans the 1993–2019 time period, we investigate whether and to what extend nominal and real interest rates, as well as interest rate quality and term spreads, are related to the valuation of REITs, measured by different metrics, and REITs returns in the medium run. The results of our analysis show that interest rates are related to REITs absolute and relative valuation measures, but the sensitivity of REITs valuation to interest rates depends on their original valuation level. Moreover, we provide evidence that lower nominal interest rates and wide quality interest spreads are positively related to future REITs returns in the medium term.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44631607","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}
Despite efforts to diversify internationally, public pension funds in the US have a significant, latent home-equity bias. The home bias takes on added importance in light of the extraordinary valuation level of the US stock market. All in all, public funds are betting heavily on the home market and paying up to do so. Caveat!
{"title":"Richard Ennis’s Insights: Overexposed? Public Pension Funds Have a Lot Riding on the US Stock Market, Possibly Even More than They Realize","authors":"Richard M. Ennis","doi":"10.3905/joi.2022.1.221","DOIUrl":"https://doi.org/10.3905/joi.2022.1.221","url":null,"abstract":"Despite efforts to diversify internationally, public pension funds in the US have a significant, latent home-equity bias. The home bias takes on added importance in light of the extraordinary valuation level of the US stock market. All in all, public funds are betting heavily on the home market and paying up to do so. Caveat!","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45429254","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}
There are two types of supervised machine learning (SML): regression and classification. In this study, the authors propose classification-based machine learning algorithms for factor investing with artificial neural networks in which the cross section of stock returns is grouped into five categories: strong buy, buy, neutral, sell, and strong sell. Their empirical out-of-sample results demonstrate some advantages of classification-based machine learning relative to regression-based learning in which the actual stock returns denote the response variable. The classification-based models also deliver slight outperformance relative to the ordinary least squares model, although the outperformance is not statistically significant. Furthermore, the out-of-sample results show that “deep” learning with multilayers of neuron layers cannot outperform a less sophisticated “shallow” learning for both classification-based and regression-based SML algorithms. Their findings suggest that market noise, common in the financial markets, during the training process overwhelms the nonlinear association uncovered in the machine learning process; and the classification of the cross section of stock returns may have reduced some of the noise.
{"title":"Factor Investing with Classification-Based Supervised Machine Learning","authors":"Edward N. W. Aw, Joshua Jiang, John Q. Jiang","doi":"10.3905/joi.2022.1.220","DOIUrl":"https://doi.org/10.3905/joi.2022.1.220","url":null,"abstract":"There are two types of supervised machine learning (SML): regression and classification. In this study, the authors propose classification-based machine learning algorithms for factor investing with artificial neural networks in which the cross section of stock returns is grouped into five categories: strong buy, buy, neutral, sell, and strong sell. Their empirical out-of-sample results demonstrate some advantages of classification-based machine learning relative to regression-based learning in which the actual stock returns denote the response variable. The classification-based models also deliver slight outperformance relative to the ordinary least squares model, although the outperformance is not statistically significant. Furthermore, the out-of-sample results show that “deep” learning with multilayers of neuron layers cannot outperform a less sophisticated “shallow” learning for both classification-based and regression-based SML algorithms. Their findings suggest that market noise, common in the financial markets, during the training process overwhelms the nonlinear association uncovered in the machine learning process; and the classification of the cross section of stock returns may have reduced some of the noise.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44418834","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}
Riley M. L. Perkins, Michael D. Phillips, D. Nyonna
Extant literature suggests that many student-managed investment funds (SMIFs) restrict membership to a few knowledgeable students, develop skills unevenly across participants, and lack formal organization and/or execution. The reality is that most individuals and many financial advisors recommend investing through mutual funds for retirement, yet most SMIFs are designed for investing in individual securities rather than in mutual funds. This article fills this void by providing a detailed framework of goals, processes, and solutions for establishing a SMIF focused exclusively on mutual fund investments that is appropriate for all undergraduate business majors. The design here is appropriate for an audience without prior investment expertise and leads to competency in mutual fund analysis, selection, and asset allocation decisions.
{"title":"Creating and Managing a SMIF Club That Invests Exclusively in Mutual Funds","authors":"Riley M. L. Perkins, Michael D. Phillips, D. Nyonna","doi":"10.3905/joi.2021.1.219","DOIUrl":"https://doi.org/10.3905/joi.2021.1.219","url":null,"abstract":"Extant literature suggests that many student-managed investment funds (SMIFs) restrict membership to a few knowledgeable students, develop skills unevenly across participants, and lack formal organization and/or execution. The reality is that most individuals and many financial advisors recommend investing through mutual funds for retirement, yet most SMIFs are designed for investing in individual securities rather than in mutual funds. This article fills this void by providing a detailed framework of goals, processes, and solutions for establishing a SMIF focused exclusively on mutual fund investments that is appropriate for all undergraduate business majors. The design here is appropriate for an audience without prior investment expertise and leads to competency in mutual fund analysis, selection, and asset allocation decisions.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91315815","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}
Institutional investors use myriad and often ambiguous asset class descriptions that obscure portfolio market exposures for anyone on the outside. This obfuscation makes it difficult to understand risk characteristics and complicates performance evaluation. Fortunately, analytical techniques exist to cut through the fog of asset class labeling.
{"title":"Richard Ennis’s Insights: Cutting through the Fog of Asset Class Labels","authors":"Richard M. Ennis","doi":"10.3905/joi.2021.1.218","DOIUrl":"https://doi.org/10.3905/joi.2021.1.218","url":null,"abstract":"Institutional investors use myriad and often ambiguous asset class descriptions that obscure portfolio market exposures for anyone on the outside. This obfuscation makes it difficult to understand risk characteristics and complicates performance evaluation. Fortunately, analytical techniques exist to cut through the fog of asset class labeling.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43186019","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}
This article examines ETF creations and redemptions around price deviations and finds that the expected arbitrage trades are relatively rare in a broad sample of equity index ETFs. In the absence of these trades, price deviations persist much longer. Creation and redemption activity appears to be constrained when exchange conditions would lead to a costlier arbitrage trade, and the size of the price deviations mainly impact the likelihood rather than the amount of trading. The authors also find some evidence that creations and redemptions are less likely to trade on price deviations when they would be required to trade the underlying stocks against broad market movements. Their results suggest that several factors may discourage the built-in ETF arbitrage mechanism and that investors may receive poorer trade execution in these conditions as a result.
{"title":"ETF Arbitrage and Daily Cash Flow","authors":"Jon A. Fulkerson, S. Jordan, Denver H. Travis","doi":"10.3905/joi.2021.1.216","DOIUrl":"https://doi.org/10.3905/joi.2021.1.216","url":null,"abstract":"This article examines ETF creations and redemptions around price deviations and finds that the expected arbitrage trades are relatively rare in a broad sample of equity index ETFs. In the absence of these trades, price deviations persist much longer. Creation and redemption activity appears to be constrained when exchange conditions would lead to a costlier arbitrage trade, and the size of the price deviations mainly impact the likelihood rather than the amount of trading. The authors also find some evidence that creations and redemptions are less likely to trade on price deviations when they would be required to trade the underlying stocks against broad market movements. Their results suggest that several factors may discourage the built-in ETF arbitrage mechanism and that investors may receive poorer trade execution in these conditions as a result.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47393607","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}
The authors construct ESG strategies that have been shown to outperform in popular articles. They assess performance benefits to investors when accounting for sector and factor exposures. They find that most of the outperformance of these strategies can be explained by their exposure to equity style factors that are mechanically constructed from balance sheet information. This result is robust across different multifactor models. Furthermore, the ESG strategies tested show large sector biases. Removing these biases also removes outperformance. They conclude that claims on ESG outperformance in popular articles are not valid.
{"title":"“Honey, I Shrunk the ESG Alpha”: Risk-Adjusting ESG Portfolio Returns","authors":"G. Bruno, Mikheil Esakia, Felix Goltz","doi":"10.3905/joi.2021.1.215","DOIUrl":"https://doi.org/10.3905/joi.2021.1.215","url":null,"abstract":"The authors construct ESG strategies that have been shown to outperform in popular articles. They assess performance benefits to investors when accounting for sector and factor exposures. They find that most of the outperformance of these strategies can be explained by their exposure to equity style factors that are mechanically constructed from balance sheet information. This result is robust across different multifactor models. Furthermore, the ESG strategies tested show large sector biases. Removing these biases also removes outperformance. They conclude that claims on ESG outperformance in popular articles are not valid.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42087534","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}
{"title":"COMMENTARY: Last Page","authors":"G. Frankfurter","doi":"10.3905/joi.2021.1.214","DOIUrl":"https://doi.org/10.3905/joi.2021.1.214","url":null,"abstract":"","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42374164","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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