: 92 percent of hedge funds in the TASS database exhibit significantly skewed returns. The alphas the managers of these funds earn are difficult to estimate accurately with OLS, especially in times of crisis. An alternative, the Residual Augmented Least Squares (RALS) estimator, is robust with respect to skewness. We demonstrate that the OLS performance assessment error relative to RALS depends systematically upon the sign of skewness in a fund’s returns and is economically significant. Furthermore, portfolios formed on RALS alphas persist more than those formed on OLS alphas and the performance persistence is concentrated in crisis periods.
{"title":"Which Hedge Fund Managers Deliver in a Crisis? Assessing Performance When Returns are Skewed","authors":"Andrea Heuson","doi":"10.2139/ssrn.1929107","DOIUrl":"https://doi.org/10.2139/ssrn.1929107","url":null,"abstract":": 92 percent of hedge funds in the TASS database exhibit significantly skewed returns. The alphas the managers of these funds earn are difficult to estimate accurately with OLS, especially in times of crisis. An alternative, the Residual Augmented Least Squares (RALS) estimator, is robust with respect to skewness. We demonstrate that the OLS performance assessment error relative to RALS depends systematically upon the sign of skewness in a fund’s returns and is economically significant. Furthermore, portfolios formed on RALS alphas persist more than those formed on OLS alphas and the performance persistence is concentrated in crisis periods.","PeriodicalId":202253,"journal":{"name":"University of Miami Herbert Business School Research Paper Series","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129319058","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 paper shows that the diversification choices of individual investors influence stock returns. A zero-cost portfolio that takes a long (short) position in stocks with the least (most) diversified individual investor clientele generates an annual, risk-adjusted return of 5-9%. This spread reflects the combined effects of sentiment induced mispricing, narrow risk framing, and asymmetric information, where the sentiment effect is the strongest. Furthermore, the influence on returns is stronger among smaller, low institutionally owned, and hard-to-arbitrage stocks. These results are robust to concerns about relatively short sample size, improper factor model specification, slow information diffusion, and high transaction costs.
{"title":"Do the Diversification Choices of Individual Investors Influence Stock Returns?","authors":"Alok Kumar","doi":"10.2139/ssrn.664044","DOIUrl":"https://doi.org/10.2139/ssrn.664044","url":null,"abstract":"This paper shows that the diversification choices of individual investors influence stock returns. A zero-cost portfolio that takes a long (short) position in stocks with the least (most) diversified individual investor clientele generates an annual, risk-adjusted return of 5-9%. This spread reflects the combined effects of sentiment induced mispricing, narrow risk framing, and asymmetric information, where the sentiment effect is the strongest. Furthermore, the influence on returns is stronger among smaller, low institutionally owned, and hard-to-arbitrage stocks. These results are robust to concerns about relatively short sample size, improper factor model specification, slow information diffusion, and high transaction costs.","PeriodicalId":202253,"journal":{"name":"University of Miami Herbert Business School Research Paper Series","volume":"90 11-12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134363279","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}
We investigate the empirical implications of the investment-based model of asset pricing for the Hansen-Jagannathan and Kozak-Nagel-Santosh discount factors in the linear span of equity returns. We find that the stochastic discount factors satisfying the Euler equation for equity returns cannot satisfy the Euler equation for investment returns because returns on corporate investment covary inversely with the sources of equity risk relative to returns on equity. As a result, the model fails to replicate the level of the risk premium. Our results suggest that joint restrictions on the optimality of investment and consumption pose stringent conditions for candidate production models.
{"title":"Do Investment-Based Models Explain Equity Returns? Evidence from Euler Equations","authors":"Stefanos Delikouras, Robert F. Dittmar","doi":"10.2139/ssrn.1786620","DOIUrl":"https://doi.org/10.2139/ssrn.1786620","url":null,"abstract":"\u0000 We investigate the empirical implications of the investment-based model of asset pricing for the Hansen-Jagannathan and Kozak-Nagel-Santosh discount factors in the linear span of equity returns. We find that the stochastic discount factors satisfying the Euler equation for equity returns cannot satisfy the Euler equation for investment returns because returns on corporate investment covary inversely with the sources of equity risk relative to returns on equity. As a result, the model fails to replicate the level of the risk premium. Our results suggest that joint restrictions on the optimality of investment and consumption pose stringent conditions for candidate production models.","PeriodicalId":202253,"journal":{"name":"University of Miami Herbert Business School Research Paper Series","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125090898","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}
A long history of economic theory suggests that industry membership plays an important role in explaining a firm's financial performance. In this paper we investigate the usefulness of industry benchmarks and industry level analysis for predicting a firm's future profitability and growth. Specifically we investigate whether incorporating the industry performance metric provides incremental information over the firm specific metric for explaining performance one-year-ahead. We also investigate the usefulness of performing industry level analysis relative to an analysis of all firms pooled across the economy. We find little or no incremental explanatory power from incorporating industry information for predicting future profitability, defined either as return on equity or return on net operating assets. Nor do we find industry information incrementally informative for predicting growth in net operating assets. We do, however, find significant improvement from incorporating industry information for predicting growth in sales. These general results hold for one-, three-, and five-year windows, and are robust to alternative industry classification schemes.
{"title":"Does Industry-Level Analysis Improve Profitability and Growth Forecasts?","authors":"P. M. Fairfield, Sundaresh Ramnath, T. Yohn","doi":"10.2139/ssrn.589361","DOIUrl":"https://doi.org/10.2139/ssrn.589361","url":null,"abstract":"A long history of economic theory suggests that industry membership plays an important role in explaining a firm's financial performance. In this paper we investigate the usefulness of industry benchmarks and industry level analysis for predicting a firm's future profitability and growth. Specifically we investigate whether incorporating the industry performance metric provides incremental information over the firm specific metric for explaining performance one-year-ahead. We also investigate the usefulness of performing industry level analysis relative to an analysis of all firms pooled across the economy. We find little or no incremental explanatory power from incorporating industry information for predicting future profitability, defined either as return on equity or return on net operating assets. Nor do we find industry information incrementally informative for predicting growth in net operating assets. We do, however, find significant improvement from incorporating industry information for predicting growth in sales. These general results hold for one-, three-, and five-year windows, and are robust to alternative industry classification schemes.","PeriodicalId":202253,"journal":{"name":"University of Miami Herbert Business School Research Paper Series","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128334898","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 dynamic principal-agent relationships, unless a principal can precommit to a multiperiod contract, incentives are affected by a problem known as the ratchet effect. We present a two period agency model to show that the use of more aggregate performance measures and greater consolidation of responsibility helps mitigate the ratchet effect. For example, an aggregate measure may be preferred to a set of disaggregate measures to avoid aggravating the ratchet effect. Similarly, it may be preferable to consolidate responsibility for two activities in the hands of one agent despite the potential loss of performance evaluation information implied by consolidation.
{"title":"Dynamic Incentives and Responsibility Accounting","authors":"Raffi Indjejikian, D. Nanda","doi":"10.2139/ssrn.74368","DOIUrl":"https://doi.org/10.2139/ssrn.74368","url":null,"abstract":"In dynamic principal-agent relationships, unless a principal can precommit to a multiperiod contract, incentives are affected by a problem known as the ratchet effect. We present a two period agency model to show that the use of more aggregate performance measures and greater consolidation of responsibility helps mitigate the ratchet effect. For example, an aggregate measure may be preferred to a set of disaggregate measures to avoid aggravating the ratchet effect. Similarly, it may be preferable to consolidate responsibility for two activities in the hands of one agent despite the potential loss of performance evaluation information implied by consolidation.","PeriodicalId":202253,"journal":{"name":"University of Miami Herbert Business School Research Paper Series","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131390007","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}
Alfred Cowles' (1934) test of the Dow Theory apparently provided strong evidence against the ability of Wall Street's most famous chartist to forecast the stock market. In this paper, we review Cowles' evidence and find that it supports the contrary conclusion -- that the Dow Theory, as applied by its major practitioner, William Peter Hamilton over the period 1902 to 1929, yielded positive risk-adjusted returns. A re-analysis of the Hamilton editorials suggests that his timing strategies yield high Sharpe ratios and positive alphas. Neural net modeling to replicate Hamilton's market calls provides interesting insight into the nature and content of the Dow Theory. This allows us to examine the properties of the Dow Theory itself out-of-sample.
{"title":"The Dow Theory: William Peter Hamilton's Track Record Re-Considered","authors":"Stephen J. Brown, W. Goetzmann, Alok Kumar","doi":"10.2139/ssrn.58690","DOIUrl":"https://doi.org/10.2139/ssrn.58690","url":null,"abstract":"Alfred Cowles' (1934) test of the Dow Theory apparently provided strong evidence against the ability of Wall Street's most famous chartist to forecast the stock market. In this paper, we review Cowles' evidence and find that it supports the contrary conclusion -- that the Dow Theory, as applied by its major practitioner, William Peter Hamilton over the period 1902 to 1929, yielded positive risk-adjusted returns. A re-analysis of the Hamilton editorials suggests that his timing strategies yield high Sharpe ratios and positive alphas. Neural net modeling to replicate Hamilton's market calls provides interesting insight into the nature and content of the Dow Theory. This allows us to examine the properties of the Dow Theory itself out-of-sample.","PeriodicalId":202253,"journal":{"name":"University of Miami Herbert Business School Research Paper Series","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130563877","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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