Benjamin McMillan, Joshua Myers, A. Nguyen, Don Robinson, Mark Kennard
Institutional interest in bitcoin has grown significantly since its “bubble highs” in 2017; and given its lack of traditional fundamentals, investor sentiment is likely to drive price discovery. As social media has grown, Reddit has evolved to host significant conversations regarding bitcoin (‘r/bitcoin’) and general investing (‘r/investing’). We focus on these two channels using four distinct natural language processing algorithms to create an ensemble sentiment score and measure the relationship of the score to the change in bitcoin’s price.
{"title":"Analysis and Comparison of Natural Language Processing Algorithms as Applied to Bitcoin Conversations on Social Media","authors":"Benjamin McMillan, Joshua Myers, A. Nguyen, Don Robinson, Mark Kennard","doi":"10.3905/joi.2021.1.213","DOIUrl":"https://doi.org/10.3905/joi.2021.1.213","url":null,"abstract":"Institutional interest in bitcoin has grown significantly since its “bubble highs” in 2017; and given its lack of traditional fundamentals, investor sentiment is likely to drive price discovery. As social media has grown, Reddit has evolved to host significant conversations regarding bitcoin (‘r/bitcoin’) and general investing (‘r/investing’). We focus on these two channels using four distinct natural language processing algorithms to create an ensemble sentiment score and measure the relationship of the score to the change in bitcoin’s price.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42974956","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 study examines the risk-adjusted performance of actively managed mutual funds versus passively managed mutual funds between 1991 and 2019 and finds that there is no statistically significant difference in performance between the two types of funds when the passively managed funds are compared to competitively priced actively managed funds. The practical implication of this study is that, setting tax considerations aside, as long as investors are cost-conscious in their fund selection process, investing in passively managed funds does not meaningfully improve investor outcomes.
{"title":"The Historical Record on Active versus Passive Mutual Fund Performance","authors":"David Nanigian","doi":"10.3905/joi.2021.1.212","DOIUrl":"https://doi.org/10.3905/joi.2021.1.212","url":null,"abstract":"This study examines the risk-adjusted performance of actively managed mutual funds versus passively managed mutual funds between 1991 and 2019 and finds that there is no statistically significant difference in performance between the two types of funds when the passively managed funds are compared to competitively priced actively managed funds. The practical implication of this study is that, setting tax considerations aside, as long as investors are cost-conscious in their fund selection process, investing in passively managed funds does not meaningfully improve investor outcomes.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47321397","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 : 2021-11-30DOI: 10.3905/joi.2021.31.1.001
Brian R. Bruce
{"title":"Editor’s Letter","authors":"Brian R. Bruce","doi":"10.3905/joi.2021.31.1.001","DOIUrl":"https://doi.org/10.3905/joi.2021.31.1.001","url":null,"abstract":"","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47667792","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 apply economic value added (EVA) style analysis to four corporate actions: acquisitions, share repurchases, stock splits, and dividend announcements. Firms acquiring public targets provide significant shorting opportunities on value-destroying growth and “wise” restructurers. Acquiring firms with private targets provide longing opportunities on underinvesting and wise restructurers. For share repurchases, the authors find consistent alpha opportunities on repurchasing firms by longing their stocks, with the highest alpha on the wise restructurers. The post-announcement returns for stock splits were negative for value destroyers and positive for restructurers. For dividend increases, post-announcement effects are small except for positive alpha on the wise restructurers. For dividend decreases, negative abnormal returns continue for the value destroyers and restructurers. The best longing opportunity is on the stocks of share-repurchasing companies in a wise restructurer position, while the best shorting opportunity is on the stocks of dividend-decreasing companies in a value-destroyer position. For active investors, EVA style analysis illuminates the naiveté of a “one size fits all” trading strategy on corporate actions.
{"title":"Trading Applications Using EVA Style Analysis","authors":"A. Chakraborty, J. Grant, E. Trahan, B. Varma","doi":"10.3905/joi.2021.1.210","DOIUrl":"https://doi.org/10.3905/joi.2021.1.210","url":null,"abstract":"The authors apply economic value added (EVA) style analysis to four corporate actions: acquisitions, share repurchases, stock splits, and dividend announcements. Firms acquiring public targets provide significant shorting opportunities on value-destroying growth and “wise” restructurers. Acquiring firms with private targets provide longing opportunities on underinvesting and wise restructurers. For share repurchases, the authors find consistent alpha opportunities on repurchasing firms by longing their stocks, with the highest alpha on the wise restructurers. The post-announcement returns for stock splits were negative for value destroyers and positive for restructurers. For dividend increases, post-announcement effects are small except for positive alpha on the wise restructurers. For dividend decreases, negative abnormal returns continue for the value destroyers and restructurers. The best longing opportunity is on the stocks of share-repurchasing companies in a wise restructurer position, while the best shorting opportunity is on the stocks of dividend-decreasing companies in a value-destroyer position. For active investors, EVA style analysis illuminates the naiveté of a “one size fits all” trading strategy on corporate actions.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41289617","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}
Eugene Podkaminer, Wylie Tollette, Laurence B. Siegel
Inflation is a perennial threat to the real value of portfolios, even though current inflation rates are low. To protect portfolios against inflation, cash, inflation-indexed bonds, equities, real estate, and commodities are the usual candidates. We examine each, plus other assets and, importantly, various kinds of liabilities, to examine their historical and prospective responses to expected and unexpected inflation. Our article is integrative, bringing together ideas and data from many different sources in one place.
{"title":"Protecting Portfolios Against Inflation","authors":"Eugene Podkaminer, Wylie Tollette, Laurence B. Siegel","doi":"10.3905/joi.2021.1.207","DOIUrl":"https://doi.org/10.3905/joi.2021.1.207","url":null,"abstract":"Inflation is a perennial threat to the real value of portfolios, even though current inflation rates are low. To protect portfolios against inflation, cash, inflation-indexed bonds, equities, real estate, and commodities are the usual candidates. We examine each, plus other assets and, importantly, various kinds of liabilities, to examine their historical and prospective responses to expected and unexpected inflation. Our article is integrative, bringing together ideas and data from many different sources in one place.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46295892","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}
Although equity index mutual funds (EIMFs) are often viewed as a commodity, we analyze the impact that differences in expenses and other fund characteristics have on both past returns and forward-looking ratings. Morningstar evaluates past performance with their “star” rating and evaluates future fund prospects using analyst ratings (ARs) and quantitative ratings (QRs). Funds with low expense ratios and no loads earn higher returns without adding proportionally higher risk. Morningstar analysts carefully consider fund fees in their evaluations and assign much higher ARs to lower-cost funds. Interestingly, although loads initially appear to negatively impact these ratings, once expense ratios are controlled for, analysts seem to be favorably disposed to funds with loads. Regression analysis further suggests that ARs are also positively influenced by Morningstar ratings and fund size. QRs are positively influenced by past performance, but negatively correlated with loads and expense ratios. EIMF age has little influence on AR and QR levels, though the likelihood of an AR rating increases with time since inception. Similar results occur in both the US and foreign equity markets. Expense ratios, loads, past performance, and size can all be used as fund selection tools that aid in maximizing investor wealth.
{"title":"Enhancing Equity Index Mutual Fund Returns Using Cost and Morningstar Ratings Information","authors":"C. E. Chang, T. Krueger, H. Witte","doi":"10.3905/joi.2021.1.206","DOIUrl":"https://doi.org/10.3905/joi.2021.1.206","url":null,"abstract":"Although equity index mutual funds (EIMFs) are often viewed as a commodity, we analyze the impact that differences in expenses and other fund characteristics have on both past returns and forward-looking ratings. Morningstar evaluates past performance with their “star” rating and evaluates future fund prospects using analyst ratings (ARs) and quantitative ratings (QRs). Funds with low expense ratios and no loads earn higher returns without adding proportionally higher risk. Morningstar analysts carefully consider fund fees in their evaluations and assign much higher ARs to lower-cost funds. Interestingly, although loads initially appear to negatively impact these ratings, once expense ratios are controlled for, analysts seem to be favorably disposed to funds with loads. Regression analysis further suggests that ARs are also positively influenced by Morningstar ratings and fund size. QRs are positively influenced by past performance, but negatively correlated with loads and expense ratios. EIMF age has little influence on AR and QR levels, though the likelihood of an AR rating increases with time since inception. Similar results occur in both the US and foreign equity markets. Expense ratios, loads, past performance, and size can all be used as fund selection tools that aid in maximizing investor wealth.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47004808","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}
Michael Bender, Tino Cestonaro, P. Gomber, Jascha-Alexander Koch
In 2018, the European financial regulation MiFID II introduced research unbundling rules that banned the bundling of research payments with execution costs. The aim of research unbundling is to increase transparency for investors and to avoid agency conflicts. Opponents argue that research unbundling reduces small and medium-sized enterprise (SME) research and, thereby, SMEs’ financing opportunities because this research can no longer be cross-subsidized by research fees paid for larger companies. The outbreak of COVID-19 and its impact on financial markets fueled intense discussions on rebundling for SMEs. Consequently, in February 2021, the European Commission adopted a Capital Markets Recovery Package that allows bundled research for SMEs below a market capitalization of EUR 1 billion. Against this backdrop, the authors conducted a survey among European market participants to investigate changes in research services due to research unbundling and the COVID-19 pandemic. Moreover, they examine market participants’ views on the expected effects and improvements of the option to rebundle SME research as provided by the recovery package.
{"title":"Research Unbundling and COVID-19: Will Europe’s Capital Markets Recovery Package Help?","authors":"Michael Bender, Tino Cestonaro, P. Gomber, Jascha-Alexander Koch","doi":"10.3905/joi.2021.1.205","DOIUrl":"https://doi.org/10.3905/joi.2021.1.205","url":null,"abstract":"In 2018, the European financial regulation MiFID II introduced research unbundling rules that banned the bundling of research payments with execution costs. The aim of research unbundling is to increase transparency for investors and to avoid agency conflicts. Opponents argue that research unbundling reduces small and medium-sized enterprise (SME) research and, thereby, SMEs’ financing opportunities because this research can no longer be cross-subsidized by research fees paid for larger companies. The outbreak of COVID-19 and its impact on financial markets fueled intense discussions on rebundling for SMEs. Consequently, in February 2021, the European Commission adopted a Capital Markets Recovery Package that allows bundled research for SMEs below a market capitalization of EUR 1 billion. Against this backdrop, the authors conducted a survey among European market participants to investigate changes in research services due to research unbundling and the COVID-19 pandemic. Moreover, they examine market participants’ views on the expected effects and improvements of the option to rebundle SME research as provided by the recovery package.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42383087","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}
Potential severe drawdowns are a central concern of investors and pose a risk often inadequately considered in the risk profiling or portfolio optimization process. In this article, conditional expected drawdowns are extended from a multi-asset perspective by introducing the conditional expected cross-maximum drawdown measure. The dimensions of magnitude and time are combined to describe tail risk dynamics across asset classes. Beyond extending the risk analytics toolbox, approaches are introduced to explicitly and computational efficiently incorporate this perspective in the optimization process. This puts investors in the position to significantly improve the tails of the maximum drawdown distribution of their strategic asset allocation. Key Findings ▪ The understanding of maximum drawdown distributions is extended from a multi-asset perspective to address a central concern of investors. ▪ A framework to estimate and analyze the dynamics across asset classes is established by using the introduced risk measure and bootstrapping simulations. ▪ Applications in portfolio optimization highlight the fact that investors can significantly increase resilience and improve the risk-adjusted returns of their strategic asset allocation.
{"title":"Maximum Drawdown Distributions: The Cross-Asset Dimension","authors":"Peter Warken, Angelina Kostyrina","doi":"10.3905/joi.2021.1.194","DOIUrl":"https://doi.org/10.3905/joi.2021.1.194","url":null,"abstract":"Potential severe drawdowns are a central concern of investors and pose a risk often inadequately considered in the risk profiling or portfolio optimization process. In this article, conditional expected drawdowns are extended from a multi-asset perspective by introducing the conditional expected cross-maximum drawdown measure. The dimensions of magnitude and time are combined to describe tail risk dynamics across asset classes. Beyond extending the risk analytics toolbox, approaches are introduced to explicitly and computational efficiently incorporate this perspective in the optimization process. This puts investors in the position to significantly improve the tails of the maximum drawdown distribution of their strategic asset allocation. Key Findings ▪ The understanding of maximum drawdown distributions is extended from a multi-asset perspective to address a central concern of investors. ▪ A framework to estimate and analyze the dynamics across asset classes is established by using the introduced risk measure and bootstrapping simulations. ▪ Applications in portfolio optimization highlight the fact that investors can significantly increase resilience and improve the risk-adjusted returns of their strategic asset allocation.","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":"47359768","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 current narrative that bonds no longer diversify equities because of low yields and a potential shift in bond-equity correlation fails to consider the relative importance of bond volatility in reducing overall portfolio volatility. Bonds will continue to provide diversification if bond volatility is lower than equity volatility, even if the correlation is positive. While better outcomes can be achieved under negative correlation, this is secondary to the impact of relative volatility. Key Findings ▪ The current narrative that bonds no longer reduce portfolio risk because of low yields and a potential shift in bond-equity correlation fails to consider the relative importance of bond volatility in reducing overall portfolio volatility. ▪ The role of bonds in the portfolio is to provide volatility reduction. Bonds will continue to lower portfolio volatility if bond volatility is lower than equity volatility, even if the correlation is positive. ▪ While better outcomes can be achieved under negative correlation, this is secondary to the impact of relative volatility.
{"title":"Bonds Don’t Need to Be Negatively Correlated with Equities","authors":"L. Ryan","doi":"10.3905/joi.2021.1.192","DOIUrl":"https://doi.org/10.3905/joi.2021.1.192","url":null,"abstract":"The current narrative that bonds no longer diversify equities because of low yields and a potential shift in bond-equity correlation fails to consider the relative importance of bond volatility in reducing overall portfolio volatility. Bonds will continue to provide diversification if bond volatility is lower than equity volatility, even if the correlation is positive. While better outcomes can be achieved under negative correlation, this is secondary to the impact of relative volatility. Key Findings ▪ The current narrative that bonds no longer reduce portfolio risk because of low yields and a potential shift in bond-equity correlation fails to consider the relative importance of bond volatility in reducing overall portfolio volatility. ▪ The role of bonds in the portfolio is to provide volatility reduction. Bonds will continue to lower portfolio volatility if bond volatility is lower than equity volatility, even if the correlation is positive. ▪ While better outcomes can be achieved under negative correlation, this is secondary to the impact of relative volatility.","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":"44494902","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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