The author applies cointegration methods to separate desirable segmented equity markets from redundant cointegrated ones. The cointegration framework is robust to the intertemporal correlation instability that plagues modern portfolio theory (MPT)–based portfolios and identifies segmented market portfolios that consistently outperform both MPT and cointegrated counterparts over the 1995–2014 test period, based on 23 developed countries. The author proposes a new allocation strategy that more heavily weights countries with smaller likelihood ratios and that captures the degree of market segmentation for each country. This cointegration-based portfolio has fewer risks and performs better, particularly in declining market conditions, when diversification is most needed. This article provides a novel global portfolio management framework for country selection and allocation.
{"title":"A New Global Portfolio Weighting Strategy Based on Cointegration Methods","authors":"Ying Zhang","doi":"10.3905/joi.2023.1.299","DOIUrl":"https://doi.org/10.3905/joi.2023.1.299","url":null,"abstract":"The author applies cointegration methods to separate desirable segmented equity markets from redundant cointegrated ones. The cointegration framework is robust to the intertemporal correlation instability that plagues modern portfolio theory (MPT)–based portfolios and identifies segmented market portfolios that consistently outperform both MPT and cointegrated counterparts over the 1995–2014 test period, based on 23 developed countries. The author proposes a new allocation strategy that more heavily weights countries with smaller likelihood ratios and that captures the degree of market segmentation for each country. This cointegration-based portfolio has fewer risks and performs better, particularly in declining market conditions, when diversification is most needed. This article provides a novel global portfolio management framework for country selection and allocation.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139168690","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}
Backtests often are discounted based on the expected failure between live and simulated (theoretical) trading. These failures are associated with the modeling assumptions that address market conditions. Deviations between live trading and strategy model performance will be biased downward by poor backtesting methodologies that do not account for model uncertainty and trading cost assumptions. However, model reality can be improved through explicitly accounting for all trading costs, endogenizing costs as part of the overall backtesting methodology, and forming systematic backtesting methodologies that account for sources of randomness. This article presents a framework for assessing backtested performance that can be employed by both investors and managers as a checklist for improving model reality, reducing trading cost biases, and accounting for uncertainty.
{"title":"“I Have Never Seen a Bad Backtest”: Modeling Reality in Quantitative Investing","authors":"Mark S. Rzepczynski, Andrew Brunner, Peter Wild","doi":"10.3905/joi.2023.1.291","DOIUrl":"https://doi.org/10.3905/joi.2023.1.291","url":null,"abstract":"Backtests often are discounted based on the expected failure between live and simulated (theoretical) trading. These failures are associated with the modeling assumptions that address market conditions. Deviations between live trading and strategy model performance will be biased downward by poor backtesting methodologies that do not account for model uncertainty and trading cost assumptions. However, model reality can be improved through explicitly accounting for all trading costs, endogenizing costs as part of the overall backtesting methodology, and forming systematic backtesting methodologies that account for sources of randomness. This article presents a framework for assessing backtested performance that can be employed by both investors and managers as a checklist for improving model reality, reducing trading cost biases, and accounting for uncertainty.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139260229","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}
Several studies have supported predictability of stock market returns, but others have questioned the evidence. Some researchers have indicated that returns predictability reflects risk aversion fluctuating with business cycles. This study investigates whether historical patterns in market risk premiums, which indicate variations in risk aversion, can predict risk premiums. Eight forecasting methods are used to identify optimal monthly forecasts of US market risk premiums for 70 years, with 95 years of data. Double moving averages of historical market risk premiums, reflecting nonseasonal data with trend, consistently provide optimal forecasts. The forecasts match the distribution of risk premiums more closely than historical averages and, unlike historical averages, they have significant predictive power for risk premiums. Years with higher forecasts provide higher risk premiums and the forecasts produce substantial utility gains in recessions and in months with negative forecasts. Four performance measures show that two investment strategies using the forecasts outperform a passive stock market investment, by enhancing risk premiums and reducing both systematic and total risk.
{"title":"Predicting Market Risk Premiums with Historical Patterns","authors":"Sandip Mukherji","doi":"10.3905/joi.2023.1.283","DOIUrl":"https://doi.org/10.3905/joi.2023.1.283","url":null,"abstract":"Several studies have supported predictability of stock market returns, but others have questioned the evidence. Some researchers have indicated that returns predictability reflects risk aversion fluctuating with business cycles. This study investigates whether historical patterns in market risk premiums, which indicate variations in risk aversion, can predict risk premiums. Eight forecasting methods are used to identify optimal monthly forecasts of US market risk premiums for 70 years, with 95 years of data. Double moving averages of historical market risk premiums, reflecting nonseasonal data with trend, consistently provide optimal forecasts. The forecasts match the distribution of risk premiums more closely than historical averages and, unlike historical averages, they have significant predictive power for risk premiums. Years with higher forecasts provide higher risk premiums and the forecasts produce substantial utility gains in recessions and in months with negative forecasts. Four performance measures show that two investment strategies using the forecasts outperform a passive stock market investment, by enhancing risk premiums and reducing both systematic and total risk.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45117173","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}
Edward N. W. Aw, Cristina Carroll, Delia Setola, Hong Xie
Many studies have disputed the widely accepted notion that a well-diversified portfolio of randomly chosen stocks must include at least 30 stocks. Furthermore, active managers generally do not select securities randomly, requiring a further examination of the notion to provide a more applicable portfolio construction framework. We find that an active manager’s conviction on the selected securities is a decreasing function of the number of securities held in a portfolio. Thus, a decision to determine the total numbers of portfolio holdings embodies an active risk budgeting exercise. We conclude that the active managers should establish a tracking error risk budget while considering the expected level of excess returns versus a benchmark using a target level of information ratio. Finally, based on the tracking error risk budget, active managers should then determine the number of securities needed in their portfolio.
{"title":"How Many Securities Should an Active Manager hold?","authors":"Edward N. W. Aw, Cristina Carroll, Delia Setola, Hong Xie","doi":"10.3905/joi.2023.1.282","DOIUrl":"https://doi.org/10.3905/joi.2023.1.282","url":null,"abstract":"Many studies have disputed the widely accepted notion that a well-diversified portfolio of randomly chosen stocks must include at least 30 stocks. Furthermore, active managers generally do not select securities randomly, requiring a further examination of the notion to provide a more applicable portfolio construction framework. We find that an active manager’s conviction on the selected securities is a decreasing function of the number of securities held in a portfolio. Thus, a decision to determine the total numbers of portfolio holdings embodies an active risk budgeting exercise. We conclude that the active managers should establish a tracking error risk budget while considering the expected level of excess returns versus a benchmark using a target level of information ratio. Finally, based on the tracking error risk budget, active managers should then determine the number of securities needed in their portfolio.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42689625","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 dollar-cost averaging (DCA) strategy is an enigma. Proven suboptimal from a risk-adjusted performance time and again since the late 1970s, it is nevertheless more popular today than ever. Our empirical analysis makes no exception. The DCA strategy does almost systematically show a lower level of volatility than the so-called lump sum investing (LSI) strategy, but there is no free lunch. The price to pay is a significantly lower level of return, leading more often than not to lower Sharpe ratios. Yet, the DCA strategy has its merit. It prevents investors from giving free reins to their “animal spirits” and paves the way of least resistance to build up an estate. This being said, recent developments shed a new light on the DCA strategy, and suggest that the liquidity profile of its order flow could very well be the key driving factor of its success today. The collateral effect is that retail investors looking for an efficient way to securely build up positions in risky assets could finally end up with more risks than they think/feel, and possibly than they can really stand. Caveat emptor.
{"title":"What Makes the Dollar Cost Averaging Strategy So Popular Today? A Critical Review of the Benefits and Risks of a Controversial Investment Scheme","authors":"François Marchessaux, Mathieu Vaissié","doi":"10.3905/joi.2023.1.281","DOIUrl":"https://doi.org/10.3905/joi.2023.1.281","url":null,"abstract":"The dollar-cost averaging (DCA) strategy is an enigma. Proven suboptimal from a risk-adjusted performance time and again since the late 1970s, it is nevertheless more popular today than ever. Our empirical analysis makes no exception. The DCA strategy does almost systematically show a lower level of volatility than the so-called lump sum investing (LSI) strategy, but there is no free lunch. The price to pay is a significantly lower level of return, leading more often than not to lower Sharpe ratios. Yet, the DCA strategy has its merit. It prevents investors from giving free reins to their “animal spirits” and paves the way of least resistance to build up an estate. This being said, recent developments shed a new light on the DCA strategy, and suggest that the liquidity profile of its order flow could very well be the key driving factor of its success today. The collateral effect is that retail investors looking for an efficient way to securely build up positions in risky assets could finally end up with more risks than they think/feel, and possibly than they can really stand. Caveat emptor.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42306767","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 investigates the relationship between R&D investment and excess returns. R&D-intensive portfolios generate higher returns than less R&D-oriented portfolios. This is despite these portfolios having lower valuation ratios. We establish that the R&D premium is a robust phenomenon with its own cyclical regularity. In particular, excess returns of R&D-intensive portfolios concentrate around the “tech bubble” period. Further, we explore the complementary relationship between intangible and tangible assets of firms, as well as the interaction between the R&D premium and value premium. We simulate a set of investing strategies integrating R&D with value; all of them perform well with improved and more stable returns than portfolios without an R&D factor.
{"title":"R&D Premium: The Intangible Side of Value","authors":"L. Cai, Ricky Cooper, Dielin He","doi":"10.3905/joi.2023.1.280","DOIUrl":"https://doi.org/10.3905/joi.2023.1.280","url":null,"abstract":"This article investigates the relationship between R&D investment and excess returns. R&D-intensive portfolios generate higher returns than less R&D-oriented portfolios. This is despite these portfolios having lower valuation ratios. We establish that the R&D premium is a robust phenomenon with its own cyclical regularity. In particular, excess returns of R&D-intensive portfolios concentrate around the “tech bubble” period. Further, we explore the complementary relationship between intangible and tangible assets of firms, as well as the interaction between the R&D premium and value premium. We simulate a set of investing strategies integrating R&D with value; all of them perform well with improved and more stable returns than portfolios without an R&D factor.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44048274","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 : 2023-07-31DOI: 10.3905/joi.2023.32.5.001
Brian R. Bruce
{"title":"Editor’s Letter","authors":"Brian R. Bruce","doi":"10.3905/joi.2023.32.5.001","DOIUrl":"https://doi.org/10.3905/joi.2023.32.5.001","url":null,"abstract":"","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48955589","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 have failed to apprehend the difference between investment policy and investment strategy. Most trustees, CIOs, and consultants don’t appear to know where one leaves off and the other begins. Trustees should concern themselves with institutional investment policy, the principal focus of which is controlling risk and ensuring liquidity. In practice, however, trustees have allowed their deliberations to encompass elements of active investment strategy. Consequently, performance accountability has become clouded. This article discusses how trustees can fix the problem.
{"title":"COMMENTARY: Disentangling Investment Policy and Investment Strategy for Better Governance","authors":"Richard M. Ennis","doi":"10.3905/joi.2023.1.279","DOIUrl":"https://doi.org/10.3905/joi.2023.1.279","url":null,"abstract":"Institutional investors have failed to apprehend the difference between investment policy and investment strategy. Most trustees, CIOs, and consultants don’t appear to know where one leaves off and the other begins. Trustees should concern themselves with institutional investment policy, the principal focus of which is controlling risk and ensuring liquidity. In practice, however, trustees have allowed their deliberations to encompass elements of active investment strategy. Consequently, performance accountability has become clouded. This article discusses how trustees can fix the problem.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41402861","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}
Inflation hit 9.1% year-over-year, spurring significant concern on the part of both institutional and retail investors. Examining the behavior of a 60/40 stock/bond portfolio over the 108.4 years ending 2/28/2023 one finds that it returned an inflation-adjusted return of 8.44% during the 75% of the months during which inflationary surprise was at its lowest. But it lost –5.18% per annum during the 25% of the months when inflationary surprise was at its highest. These data suggest that investor attention to this topic is well placed. Investors, investment managers, advisors, and strategists often discuss gold, TIPS bonds, and diversified commodities as effective, useful mitigants. But are they? This article considers 29 mitigants over the time period spanning 1914 through today and identifies those mitigants that are effective and those that are not. It presents results that strongly support the conclusion that both gold and TIPS are remarkably poor mitigants. This result is not surprising, given that gold is driven, in large measure, by its use as an event-risk mitigant, both domestic and international. Moreover, gold lacks any significant industrial use. In a similar fashion, TIPS bonds carry significant interest rate risk, which serves to disrupt their use as an inflationary surprise mitigant. The largest TIPS ETF (“TIP”) carries an effective interest rate duration of seven years. This article shows that the most effective mitigant is a 50/50 blend of broadly diversified commodities and wheat. The inclusion of wheat may be an indirect way of reducing the overall weighting to fossil fuels. Perhaps fossil fuels are playing a reduced role and agricultural foodstuffs an expanded role, as the global economy becomes less energy-intensive and the middle class grows. Finally, it is shown that the benefits of inflationary surprise mitigation rely, in large measure, on the frequency with which the mitigant is applied (not too often, but still often enough) and the dosage size. Moreover, although correct timing is highly beneficial, the benefits of mitigation still accrue to those who arrive surprisingly late to the party.
{"title":"Inflation Hedging Tools—What Works and What Doesn’t","authors":"Rob Brown","doi":"10.3905/joi.2023.1.278","DOIUrl":"https://doi.org/10.3905/joi.2023.1.278","url":null,"abstract":"Inflation hit 9.1% year-over-year, spurring significant concern on the part of both institutional and retail investors. Examining the behavior of a 60/40 stock/bond portfolio over the 108.4 years ending 2/28/2023 one finds that it returned an inflation-adjusted return of 8.44% during the 75% of the months during which inflationary surprise was at its lowest. But it lost –5.18% per annum during the 25% of the months when inflationary surprise was at its highest. These data suggest that investor attention to this topic is well placed. Investors, investment managers, advisors, and strategists often discuss gold, TIPS bonds, and diversified commodities as effective, useful mitigants. But are they? This article considers 29 mitigants over the time period spanning 1914 through today and identifies those mitigants that are effective and those that are not. It presents results that strongly support the conclusion that both gold and TIPS are remarkably poor mitigants. This result is not surprising, given that gold is driven, in large measure, by its use as an event-risk mitigant, both domestic and international. Moreover, gold lacks any significant industrial use. In a similar fashion, TIPS bonds carry significant interest rate risk, which serves to disrupt their use as an inflationary surprise mitigant. The largest TIPS ETF (“TIP”) carries an effective interest rate duration of seven years. This article shows that the most effective mitigant is a 50/50 blend of broadly diversified commodities and wheat. The inclusion of wheat may be an indirect way of reducing the overall weighting to fossil fuels. Perhaps fossil fuels are playing a reduced role and agricultural foodstuffs an expanded role, as the global economy becomes less energy-intensive and the middle class grows. Finally, it is shown that the benefits of inflationary surprise mitigation rely, in large measure, on the frequency with which the mitigant is applied (not too often, but still often enough) and the dosage size. Moreover, although correct timing is highly beneficial, the benefits of mitigation still accrue to those who arrive surprisingly late to the party.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47153361","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}
Crowding risk is a major concern in factor investing in general, and in momentum strategies in particular. This article contributes to the discussion on the implications of crowding risk in the stock market by focusing on the dynamic of momentum crowdedness and the subsequent alterations in the related risk premium. Understanding these implications is key for the design of more resilient momentum strategies. Our analysis shows that the five-factor risk profile of momentum and the structure of the related risk premium mutate with crowdedness regime switches. It suggests that actively managing this risk in momentum strategies leads to a material improvement of their risk-adjusted performance.
{"title":"Dragging Momentum out of the Crowd","authors":"Hamza Bahaji, Edouard Van Yen","doi":"10.3905/joi.2023.1.277","DOIUrl":"https://doi.org/10.3905/joi.2023.1.277","url":null,"abstract":"Crowding risk is a major concern in factor investing in general, and in momentum strategies in particular. This article contributes to the discussion on the implications of crowding risk in the stock market by focusing on the dynamic of momentum crowdedness and the subsequent alterations in the related risk premium. Understanding these implications is key for the design of more resilient momentum strategies. Our analysis shows that the five-factor risk profile of momentum and the structure of the related risk premium mutate with crowdedness regime switches. It suggests that actively managing this risk in momentum strategies leads to a material improvement of their risk-adjusted performance.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47407125","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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