In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables. We assess the performance of actively managed portfolios strategies which optimally exploit such predictability, both in-sample as well as out-of-sample. Such strategies were first studied by Hansen and Richard (1987) and Ferson and Siegel 2001. Our criterion is to maximize various ex-post performance measures, including maximum Sharpe ratio, utility premia, and transaction costs. We develop a test statistic, based on the difference in maximum Sharpe ratio, that has both an intuitive economic interpretation as well as known statistical properties. We are thus able to assess the statistical significance of the economic gains from predictability. Our analysis allows us to compare and rank different predictor variables and also groups of predictor variables. Overall we find that the optimal use of conditioning information does indeed significantly improve the risk-return tradeoff available to a mean-variance investor, relative to traditional buy-and-hold strategies. These findings are consistent across the different performance measures employed. In addition we also compare the performance of the unconditionally efficient strategies with conditionally efficient strategies from an investment-based perspective. We find that the performance of the two strategies is quite different due to the differing response of the portfolio weights to changes in conditioning information.
本文基于广泛的常用预测变量，研究了资产收益可预测性的经济价值和统计显著性。我们评估积极管理的投资组合策略的表现，这些策略最优地利用了样本内和样本外的可预测性。Hansen and Richard(1987)和Ferson and Siegel(2001)首先对这些策略进行了研究。我们的标准是最大化各种事后绩效指标，包括最大夏普比率、效用溢价和交易成本。基于最大夏普比率的差异，我们开发了一个检验统计量，它既具有直观的经济解释，又具有已知的统计特性。因此，我们能够评估可预测性带来的经济收益的统计意义。我们的分析允许我们比较和排名不同的预测变量和预测变量组。总的来说，我们发现，与传统的买入并持有策略相比，条件反射信息的最佳使用确实显著提高了平均方差投资者的风险回报权衡。这些发现在采用的不同绩效衡量标准中是一致的。此外，我们还从投资的角度比较了无条件有效策略和条件有效策略的绩效。我们发现，由于投资组合权重对条件反射信息变化的响应不同，两种策略的绩效差异很大。
{"title":"The Optimal Use of Return Predictability: An Empirical Analysis","authors":"Abhay Abhyankar, D. Basu, A. Stremme","doi":"10.2139/ssrn.677009","DOIUrl":"https://doi.org/10.2139/ssrn.677009","url":null,"abstract":"In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables. We assess the performance of actively managed portfolios strategies which optimally exploit such predictability, both in-sample as well as out-of-sample. Such strategies were first studied by Hansen and Richard (1987) and Ferson and Siegel 2001. Our criterion is to maximize various ex-post performance measures, including maximum Sharpe ratio, utility premia, and transaction costs. We develop a test statistic, based on the difference in maximum Sharpe ratio, that has both an intuitive economic interpretation as well as known statistical properties. We are thus able to assess the statistical significance of the economic gains from predictability. Our analysis allows us to compare and rank different predictor variables and also groups of predictor variables. \u0000 \u0000Overall we find that the optimal use of conditioning information does indeed significantly improve the risk-return tradeoff available to a mean-variance investor, relative to traditional buy-and-hold strategies. These findings are consistent across the different performance measures employed. \u0000 \u0000In addition we also compare the performance of the unconditionally efficient strategies with conditionally efficient strategies from an investment-based perspective. We find that the performance of the two strategies is quite different due to the differing response of the portfolio weights to changes in conditioning information.","PeriodicalId":107326,"journal":{"name":"Empirical Asset Pricing III","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117132802","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 focuses on two popular predictive variables that are often used to forecast stock market returns: the dividend yield and the price earnings ratio. First, we question the theoretical premise that the dividend yield ought to have predictive power for the aggregate stock market. By referring to the Modigliani and Miller (1961) theorem that dividend policy is irrelevant, but allowing for uncertainty, we show that the dividend yield might not be the appropriate variable to forecast returns on equity. In addition, we show that the dividend yield for stock indexes tends toward the dividend yield of the fastest growing firm in the index, thereby introducing a downward trend in the dividend yield. On the other hand, the earnings yield provides a good proxy for the expected return under mild conditions: if the return on aggregate investment coincides with the expected market return and expected returns form a martingale sequence. Our theoretical findings are confirmed in the S&P 500 data: prices seemingly overreact to dividends, even in the long-run, as suggested by the long-run elasticity of prices with respect to dividends of about 1.5 as first observed by Barsky and DeLong (1993). The long-run elasticity of prices with respect to earnings, however, is insignificantly different from one, suggesting that the focus on dividends alone might be rather misguiding in judging the efficiency of the market. Accounting for these facts, simple tests of market efficiency can be constructed. We find that, in the short-run, the efficient markets hypothesis cannot be rejected.
{"title":"Examining the Statistical Properties of Financial Ratios","authors":"C. Hansen, Bjorn Tuypens","doi":"10.2139/ssrn.676832","DOIUrl":"https://doi.org/10.2139/ssrn.676832","url":null,"abstract":"This paper focuses on two popular predictive variables that are often used to forecast stock market returns: the dividend yield and the price earnings ratio. First, we question the theoretical premise that the dividend yield ought to have predictive power for the aggregate stock market. By referring to the Modigliani and Miller (1961) theorem that dividend policy is irrelevant, but allowing for uncertainty, we show that the dividend yield might not be the appropriate variable to forecast returns on equity. In addition, we show that the dividend yield for stock indexes tends toward the dividend yield of the fastest growing firm in the index, thereby introducing a downward trend in the dividend yield. On the other hand, the earnings yield provides a good proxy for the expected return under mild conditions: if the return on aggregate investment coincides with the expected market return and expected returns form a martingale sequence. Our theoretical findings are confirmed in the S&P 500 data: prices seemingly overreact to dividends, even in the long-run, as suggested by the long-run elasticity of prices with respect to dividends of about 1.5 as first observed by Barsky and DeLong (1993). The long-run elasticity of prices with respect to earnings, however, is insignificantly different from one, suggesting that the focus on dividends alone might be rather misguiding in judging the efficiency of the market. Accounting for these facts, simple tests of market efficiency can be constructed. We find that, in the short-run, the efficient markets hypothesis cannot be rejected.","PeriodicalId":107326,"journal":{"name":"Empirical Asset Pricing III","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126841540","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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