Pub Date : 2021-09-30DOI: 10.3905/joi.2021.30.6.001
Brian R. Bruce
{"title":"Editor’s Letter","authors":"Brian R. Bruce","doi":"10.3905/joi.2021.30.6.001","DOIUrl":"https://doi.org/10.3905/joi.2021.30.6.001","url":null,"abstract":"","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47231603","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}
Many well-known mutual fund companies as well as mutual fund rating services such as Morningstar have recently reported “capture ratios” to help investors evaluate mutual fund performance. These ratios give investors a sense of how a fund has performed in certain market conditions. For example, there is an “upside market capture ratio” that shows a mutual fund’s past performance in up-markets. Similarly, there is a “downside market capture ratio” which provides the fund’s past performance in down-markets. In this article we use mutual fund data from 1990–2019 to analyze these capture ratios and examine how well they predict future fund performance. We find evidence that capture ratios are quite overrated. First, they do not seem to “capture” manager ability but rather just the beta of the portfolio. Second, when we use a measure of manager skill created by combining capture ratios, we find that this measure of skill is actually negatively and significantly related to future fund performance over periods longer than one year. Based on our results, investors should be cautious when using capture ratios to measure or predict performance. Key Findings ▪ This article finds that the relationship between the capture ratios and beta is significantly and strongly positive. This suggests that those using capture ratios as evidence of manager skill may be misattributing performance. ▪ This article also finds that the skill measure, which is the difference between a fund’s upside and downside capture ratios, is significantly and negatively related to three-year and five-year out-of-sample alpha. This suggests that longer-term investors do not benefit from investing in funds with higher skill. ▪ The results presented in this article suggest that mutual fund companies should be cautious when touting their capture ratios as evidence of manager skill, and investors should be cautious not to misinterpret the capture ratios as evidence of manager skill.
{"title":"What Do Capture Ratios Really Capture in Mutual Fund Performance?","authors":"Aron Gottesman, M. Morey","doi":"10.3905/joi.2021.1.191","DOIUrl":"https://doi.org/10.3905/joi.2021.1.191","url":null,"abstract":"Many well-known mutual fund companies as well as mutual fund rating services such as Morningstar have recently reported “capture ratios” to help investors evaluate mutual fund performance. These ratios give investors a sense of how a fund has performed in certain market conditions. For example, there is an “upside market capture ratio” that shows a mutual fund’s past performance in up-markets. Similarly, there is a “downside market capture ratio” which provides the fund’s past performance in down-markets. In this article we use mutual fund data from 1990–2019 to analyze these capture ratios and examine how well they predict future fund performance. We find evidence that capture ratios are quite overrated. First, they do not seem to “capture” manager ability but rather just the beta of the portfolio. Second, when we use a measure of manager skill created by combining capture ratios, we find that this measure of skill is actually negatively and significantly related to future fund performance over periods longer than one year. Based on our results, investors should be cautious when using capture ratios to measure or predict performance. Key Findings ▪ This article finds that the relationship between the capture ratios and beta is significantly and strongly positive. This suggests that those using capture ratios as evidence of manager skill may be misattributing performance. ▪ This article also finds that the skill measure, which is the difference between a fund’s upside and downside capture ratios, is significantly and negatively related to three-year and five-year out-of-sample alpha. This suggests that longer-term investors do not benefit from investing in funds with higher skill. ▪ The results presented in this article suggest that mutual fund companies should be cautious when touting their capture ratios as evidence of manager skill, and investors should be cautious not to misinterpret the capture ratios as evidence of manager skill.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48393203","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}
In this article, the authors show that it is possible to enhance traditional Black and Litterman strategic asset allocation (SAA) models with a behavioral approach based on news sentiment. In an out-of-sample backtest over 10 years, the news sentiment–based SAA outperforms the benchmark SAA by 0.5% a year with less risk and a 20% higher Sharpe ratio. The news sentiment data are also statistically different from price momentum measures.
{"title":"Applying News Sentiment for Optimizing Strategic Asset Allocations","authors":"P. Rohner, Matthias W. Uhl","doi":"10.3905/joi.2021.1.203","DOIUrl":"https://doi.org/10.3905/joi.2021.1.203","url":null,"abstract":"In this article, the authors show that it is possible to enhance traditional Black and Litterman strategic asset allocation (SAA) models with a behavioral approach based on news sentiment. In an out-of-sample backtest over 10 years, the news sentiment–based SAA outperforms the benchmark SAA by 0.5% a year with less risk and a 20% higher Sharpe ratio. The news sentiment data are also statistically different from price momentum measures.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44430675","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 introduces an intuitive, earnings-based sentiment indicator that is useful for forecasting overall market direction. The indicator aggregates the difference between the mean and the low forecasts on individual stocks, with the rationale being that the indicator captures for the entire market what dispersion captures for a single stock. The basic results are that when the aggregate low forecast is considerably lower than the aggregate mean forecast, subsequent forecast revisions tend to be more negative and future index returns tend to be lower and more volatile. However, when the aggregate low forecast is extremely low compared with the aggregate mean forecast, investor and analyst sentiments tend to be overly pessimistic, and the market thus tends to perform strongly.
{"title":"The Information in Low Forecasts","authors":"Haim A. Mozes","doi":"10.3905/joi.2021.1.202","DOIUrl":"https://doi.org/10.3905/joi.2021.1.202","url":null,"abstract":"This article introduces an intuitive, earnings-based sentiment indicator that is useful for forecasting overall market direction. The indicator aggregates the difference between the mean and the low forecasts on individual stocks, with the rationale being that the indicator captures for the entire market what dispersion captures for a single stock. The basic results are that when the aggregate low forecast is considerably lower than the aggregate mean forecast, subsequent forecast revisions tend to be more negative and future index returns tend to be lower and more volatile. However, when the aggregate low forecast is extremely low compared with the aggregate mean forecast, investor and analyst sentiments tend to be overly pessimistic, and the market thus tends to perform strongly.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48427606","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}
Federal income tax legislative reforms impact both investors and companies. It is prudent to understand these legislative effects before the next round of tax legislation. This article examines whether announcements regarding the passage of the Tax Cuts and Jobs Act of 2017 (TCJA) affected the value of publicly traded companies. The authors use a multiple-date event study methodology to analyze whether abnormal returns were present for companies in the S&P 500 Index after various announcements of the TCJA’s passage by the US Congress. Results on many of the event dates provide support that the TCJA had a positive impact on company value. They also analyze differences among companies based on dividend practices, multinationality, revenue growth, and effective tax rates. Their findings provide valuable insight as US companies and investors prepare for the possibility of corporate tax changes from the Biden administration.
{"title":"Tax Reform, Company Value, and Biden Proposals","authors":"Robin L. Walker, John R. Wingender, T. J. Purcell","doi":"10.3905/joi.2021.1.200","DOIUrl":"https://doi.org/10.3905/joi.2021.1.200","url":null,"abstract":"Federal income tax legislative reforms impact both investors and companies. It is prudent to understand these legislative effects before the next round of tax legislation. This article examines whether announcements regarding the passage of the Tax Cuts and Jobs Act of 2017 (TCJA) affected the value of publicly traded companies. The authors use a multiple-date event study methodology to analyze whether abnormal returns were present for companies in the S&P 500 Index after various announcements of the TCJA’s passage by the US Congress. Results on many of the event dates provide support that the TCJA had a positive impact on company value. They also analyze differences among companies based on dividend practices, multinationality, revenue growth, and effective tax rates. Their findings provide valuable insight as US companies and investors prepare for the possibility of corporate tax changes from the Biden administration.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42818265","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}
Value stocks have endured a period of severe underperformance until recently. This article shows that the value spreads between valuations of value stocks and their most expensive peers expanded in all regions and sectors during this period of underperformance, reaching the same extreme high levels last seen at the peak of the tech bubble in 2000. Investors have rerated expensive stocks relative to their value peers, thus reflecting an expanding difference in their respective earnings growth forecasts. There are signs this trend may now have changed. Value spreads may have started a new period of compression at the end of 2020, led by shrinking differences in earnings growth forecasts. A compression in value spreads would be favorable for value stocks, small-capitalization stocks, and multifactor strategies.
{"title":"Value versus Glamour Stocks: The Return of Irrational Exuberance?","authors":"B. Bellone, Raul Leote de Carvalho","doi":"10.3905/joi.2021.1.199","DOIUrl":"https://doi.org/10.3905/joi.2021.1.199","url":null,"abstract":"Value stocks have endured a period of severe underperformance until recently. This article shows that the value spreads between valuations of value stocks and their most expensive peers expanded in all regions and sectors during this period of underperformance, reaching the same extreme high levels last seen at the peak of the tech bubble in 2000. Investors have rerated expensive stocks relative to their value peers, thus reflecting an expanding difference in their respective earnings growth forecasts. There are signs this trend may now have changed. Value spreads may have started a new period of compression at the end of 2020, led by shrinking differences in earnings growth forecasts. A compression in value spreads would be favorable for value stocks, small-capitalization stocks, and multifactor strategies.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42904378","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}
Trade disputes and the impact of the COVID-19 pandemic on global supply chains have drawn much attention to the notion of “deglobalization.” The common concern is that the steady trend of globalization and its many benefits may reverse. But the globalization trend is not a monolith. In this article, we show that although trade globalization has stalled since the Global Financial Crisis (GFC), financial globalization has continued to increase. We further show that financial globalization has a much more significant impact on portfolios than trade globalization. The primary mechanism of this impact, US dollar hegemony, impacts portfolios primarily through increased spillover of US monetary policy shocks. The two implications for investors are: (1) global equity markets have become increasingly correlated and are likely to stay that way, and (2) this increased correlation reduces the benefits of portfolio diversification and leads to a more concentrated exposure to US monetary policy shocks. Key Findings ▪ Financial globalization has increased steadily even as trade globalization has stalled over the past decade. ▪ Increased financial globalization amplified by increased US Dollar hegemony raises the correlation of global equity markets, reduces efficacy of geographic diversification, and concentrates exposure to US monetary policy shocks. ▪ Therefore, investors must step beyond the simple equity/fixed income paradigm to consider other opportunities to diversify equity risk such as commodities, currencies, alternatives, or low volatility strategies.
{"title":"Financial Globalization and Its Implications for Diversification of Portfolio Risk","authors":"Ramu Thiagarajan, Jiho Han, Aaron Hurd, Hanbin Im, Gaurav Mallik","doi":"10.3905/joi.2021.1.197","DOIUrl":"https://doi.org/10.3905/joi.2021.1.197","url":null,"abstract":"Trade disputes and the impact of the COVID-19 pandemic on global supply chains have drawn much attention to the notion of “deglobalization.” The common concern is that the steady trend of globalization and its many benefits may reverse. But the globalization trend is not a monolith. In this article, we show that although trade globalization has stalled since the Global Financial Crisis (GFC), financial globalization has continued to increase. We further show that financial globalization has a much more significant impact on portfolios than trade globalization. The primary mechanism of this impact, US dollar hegemony, impacts portfolios primarily through increased spillover of US monetary policy shocks. The two implications for investors are: (1) global equity markets have become increasingly correlated and are likely to stay that way, and (2) this increased correlation reduces the benefits of portfolio diversification and leads to a more concentrated exposure to US monetary policy shocks. Key Findings ▪ Financial globalization has increased steadily even as trade globalization has stalled over the past decade. ▪ Increased financial globalization amplified by increased US Dollar hegemony raises the correlation of global equity markets, reduces efficacy of geographic diversification, and concentrates exposure to US monetary policy shocks. ▪ Therefore, investors must step beyond the simple equity/fixed income paradigm to consider other opportunities to diversify equity risk such as commodities, currencies, alternatives, or low volatility strategies.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44906961","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.2021.1.195","DOIUrl":"https://doi.org/10.3905/joi.2021.1.195","url":null,"abstract":"","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46782827","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}
With a history of empirical success, momentum became widely adopted by investment managers despite a lack of consensus on why it worked. Then in the 2000s, momentum failed, with negative returns and sharp downturns. This article examines behavioral, market friction, and risk-based explanations for why momentum works. The author also pinpoints several circumstances when momentum fails, including post-decimalization, after bear markets, during volatile markets, and when value stocks outperform. He discusses how the three explanations of momentum’s behavior enable us to understand why momentum has failed and applies these conditions to understand momentum’s failure during the 2000s. This article thus provides guidance into when and why momentum works or doesn’t work, which will help investors decide how to proceed going forward. TOPICS: Security analysis and valuation, analysis of individual factors/risk premia, legal/regulatory/public policy, exchanges/markets/clearinghouses, performance measurement Key Findings ▪ The success of momentum can be explained by a variety of behavioral, market friction, and risk considerations. ▪ Under certain conditions, momentum will tend to not work, including post-decimalization, after bear markets, during periods of volatility, and when value stocks outperform. ▪ These conditions were more prevalent in the 2000s, helping to explain momentum’s weak performance in those years and providing investors with guidance going forward.
{"title":"When and Why Does Momentum Work—and Not Work?","authors":"A. Berkin","doi":"10.3905/joi.2021.1.190","DOIUrl":"https://doi.org/10.3905/joi.2021.1.190","url":null,"abstract":"With a history of empirical success, momentum became widely adopted by investment managers despite a lack of consensus on why it worked. Then in the 2000s, momentum failed, with negative returns and sharp downturns. This article examines behavioral, market friction, and risk-based explanations for why momentum works. The author also pinpoints several circumstances when momentum fails, including post-decimalization, after bear markets, during volatile markets, and when value stocks outperform. He discusses how the three explanations of momentum’s behavior enable us to understand why momentum has failed and applies these conditions to understand momentum’s failure during the 2000s. This article thus provides guidance into when and why momentum works or doesn’t work, which will help investors decide how to proceed going forward. TOPICS: Security analysis and valuation, analysis of individual factors/risk premia, legal/regulatory/public policy, exchanges/markets/clearinghouses, performance measurement Key Findings ▪ The success of momentum can be explained by a variety of behavioral, market friction, and risk considerations. ▪ Under certain conditions, momentum will tend to not work, including post-decimalization, after bear markets, during periods of volatility, and when value stocks outperform. ▪ These conditions were more prevalent in the 2000s, helping to explain momentum’s weak performance in those years and providing investors with guidance going forward.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48792866","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}
Alternative investments long ago ceased to be diversifiers, as their trading markets became more liquid and pricing there came to be more closely aligned with that of public markets. For the same reason, the principal classes of alts ceased to be sources of alpha and became a serious drag on performance. As a result of this market evolution, the endowment model’s signature asset-class diversification scheme now imposes rigidity without benefit: Asset classes have become silos, tantamount to quotas for large-scale investing in pricey alternative investments of uncertain merit. One hundred or more investment managers for an endowment portfolio are way too many: Inefficient diversification abounds. Costs approaching 2% of asset value are implausible on their face. TOPICS: Real assets/alternative investments/private equity, foundations & endowments, portfolio construction, performance measurement Key Findings ▪ Alternative investments have ceased to be diversifiers and have become a serious drag on performance. ▪ Having more than 100 managers for the typical large endowment is a source of inefficient diversification. ▪ An average estimated annual cost of 1.7%, combined with extensive diversification, virtually assures underperformance.
{"title":"COMMENTARY: Problems with the Endowment Model","authors":"Richard M. Ennis","doi":"10.3905/JOI.2021.1.186","DOIUrl":"https://doi.org/10.3905/JOI.2021.1.186","url":null,"abstract":"Alternative investments long ago ceased to be diversifiers, as their trading markets became more liquid and pricing there came to be more closely aligned with that of public markets. For the same reason, the principal classes of alts ceased to be sources of alpha and became a serious drag on performance. As a result of this market evolution, the endowment model’s signature asset-class diversification scheme now imposes rigidity without benefit: Asset classes have become silos, tantamount to quotas for large-scale investing in pricey alternative investments of uncertain merit. One hundred or more investment managers for an endowment portfolio are way too many: Inefficient diversification abounds. Costs approaching 2% of asset value are implausible on their face. TOPICS: Real assets/alternative investments/private equity, foundations & endowments, portfolio construction, performance measurement Key Findings ▪ Alternative investments have ceased to be diversifiers and have become a serious drag on performance. ▪ Having more than 100 managers for the typical large endowment is a source of inefficient diversification. ▪ An average estimated annual cost of 1.7%, combined with extensive diversification, virtually assures underperformance.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48658583","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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