Testing the Economic Value of Asset Return Predictability

2012 ◽  
Author(s):  
Michael W. McCracken ◽  
Giorgio Valente
Keyword(s):  
Economic Value ◽  
Return Predictability ◽  
Asset Return

scholarly journals The Optimal Use of Return Predictability: An Empirical Study

2012 ◽  
Vol 47 (5) ◽  
pp. 973-1001 ◽  
Author(s):  
Abhay Abhyankar ◽  
Devraj Basu ◽  
Alexander Stremme
Keyword(s):  
Statistical Significance ◽  
Economic Value ◽  
Return Predictability ◽  
Credit Spread ◽  
Asset Return ◽  
Term Spread ◽  
Predictive Variables ◽  
Economic Interpretation ◽  
Wide Range ◽  
Out Of Sample

AbstractIn 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 dynamic, unconditionally efficient strategies, first studied by Hansen and Richard (1987) and Ferson and Siegel (2001), using a test that has both an intuitive economic interpretation and known statistical properties. We find that using the lagged term spread, credit spread, and inflation significantly improves the risk-return trade-off. Our strategies consistently outperform efficient buy-and-hold strategies, both in and out of sample, and they also incur lower transactions costs than traditional conditionally efficient strategies.

scholarly journals Is Human Capital the Sixth Factor? Evidence from US Data

2019 ◽  
Vol 8 (1) ◽  
pp. 21-55 ◽  
Author(s):  
Rahul Roy ◽  
Santhakumar Shijin
Keyword(s):  
Human Capital ◽  
Asset Pricing ◽  
Factor Model ◽  
Generalized Method Of Moments ◽  
Common Factors ◽  
Return Predictability ◽  
Pricing Model ◽  
Gmm Estimation ◽  
Asset Return ◽  
Asset Pricing Model

Problem/Relevance: Measuring the risk of an asset and the economic forces driving the price of the risk is a challengingtask that preoccupied the asset pricing literature for decades. However, there exists no consensus on the integrated asset pricing framework among the financial economists in the contemporaneous asset pricing literature. Thus, we consider and study this research problem that has greater relevance in pricing the risks of an asset. In this backdrop, we develop an integrated equilibrium asset pricing model in an intertemporal (ICAPM) framework. Research Objective/Questions: Broadly we have two research objectives. First, we examine the joint dynamics of the human capital component and common factors in approximating the variation in asset return predictability. Second, we test whether the human capital component is the unaccounted and the sixth pricing factor of FF five-factor asset pricing model. Additionally, we assess the economic and statistical significance of the equilibrium six-factor asset pricing model. Methodology: The human capital component, market portfolio, size, value, profitability, and investment are the pricing factors of the equilibrium six-factor asset pricing model. We use Fama-French (FF) portfolios of 2  3, 5  5, 10  10 sorts, 2  4  4 sorts, and the Industry portfolios to examine the equilibrium six-factor asset pricing model. The Generalized method of moments (GMM) estimation is used to estimate the parameters of variant asset pricing models and Gibbons-Ross-Shanken test is employed to evaluate the performance of the variant asset pricing frameworks. Major Findings: Our approaches led to three conclusions. First, the GMM estimation result infers that the human capital component of the six-factor asset pricing model significantly priced the variation in excess return on FF portfolios of variant sorts and the Industry portfolios. Further, the sensitivity to human capital component priced separately in the presence of the market portfolios and the common factors. Second, the six-factor asset pricing model outperforms the CAPM, FF three-factor model, and FF five-factor model, which indicates that the human capital component is a significant pricing factor in asset return predictability. Third, we argue that the human capital component is the unaccounted asset pricing factor and equally the sixth-factor of the FF five-factor asset pricing model. The additional robustness test result confirms that the parameter estimation of the six-factor asset pricing model is robust to the alternative definitions of the human capital component. Implications: The empirical results and findings equally pose the more significant effects for the decision-making process of the rational investor, institutional managers, portfolio managers, and fund managers in formulating the better investment strategies, which can help in diversifying the aggregate risks.

scholarly journals Time-varying stock return predictability: the Eurozone case

2015 ◽  
pp. 28-38
Author(s):  
Nuno Silva
Keyword(s):  
Statistical Tests ◽  
Economic Value ◽  
Return Predictability ◽  
Time Varying ◽  
Stock Return Predictability ◽  
Varying Coefficients ◽  
Time Varying Parameters ◽  
Constant Coefficients ◽  
Time Varying Coefficients ◽  
Better Than

In this paper, we test the existence of predictability in eleven Eurozone stock markets, using both regressions with constant coefficients and with time-varying coefficients. Our results show that there is statistical evidence of predictability in some countries. The economic value of the forecasting models is much stronger than what could be inferred, based on the statistical tests. A meanvariance investor could have obtained substantial utility gains in most countries. Overall, models with time-varying parameters perform slightly better than models with constant coefficients.http://dx.doi.org/10.14195/2183‑203X_41_4

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