Industry Costs of Equity: Incorporating Prior Information

I examine whether incorporating economically motivated prior information yields more accurate forecasts of industry costs of equity. I find that incorporating the long‐run mean of the Capital Asset Pricing Model (CAPM) parameters and the industry characteristics in the cross section produces more accurate parameter estimates, which subsequently translate into more accurate out‐of‐sample forecasts of industry costs of equity. The outperformance of this method over rolling‐window estimates becomes larger as the forecast horizon extends into the future. These findings provide evidence that the CAPM parameters have a long‐run mean‐reversion property and correlate with the industry characteristics in a systematic way.     

Beta and firm age

We document a robust pattern of beta declining over the age of a firm. We find that changes in systematic risk via firm characteristics and life-cycle stages are insufficient to explain this pattern. Moreover, standard proxies for the quantity and quality of information also explain this pattern only partially. To fully explain this pattern we rely on the increasingly important role of familiarity in financial decision making: familiarity is a determinant of beta and firm age is a proxy for the degree of familiarity that investors feel toward individual stocks. To illustrate the implication of our findings, we document that when we control for firm age there is support for the CAPM and its use as an input for the cost of equity capital calculation.     

资本市场的实验经济学方法论研究

随着金融市场理论研究和实践检验的不断发展，资本市场的许多基础理论受到了极大的挑战，与现有理论相悖的异象不断涌现。新近兴起的实验经济学为人们研究资本市场提供了一条更为有效的途径。本文分析了实验方法在资本市场研究中的利与弊，介绍了部分资本市场实验的设计过程，并应用该方法分析了风险与收益、资本市场的效率、市场泡沫的产生和破灭、CAPM理论，以及交易制度等。文章指出，在资本市场中运用实验方法进行研究，具有可控性、可比性以及可重复性等优点，为我们对于资本市场诸多理论进行检验提供了可能。在资本市场实验的设计中，我们不但需要考虑实验的各种交易制度，还需要考虑到被试人员的选择、交易资产的确定以及市场信息的设计等很多问题，只有对这些问题进行全面地考虑，才能保证实验结果的可信度，进而为我们对于各种金融理论的检验提供可能。     

Monotonicity in asset returns: New tests with applications to the term structure,the CAPM,and portfolio sorts

Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times to maturity; the Capital Asset Pricing Model (CAPM) implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.     

An Examination of Alternative Factor Models in UK Stock Returns

This paper examines the mean-variance efficiency of a number offactor models in UK stock returns. The paper also explores, using theapproach of MacKinlay (1995), whether missing risk factors ornonrisk-based explanations best explain the pricing errors of thedifferent factor models. The evidence in the paper suggests that themean-variance efficiency of each factor model is rejected and missing riskfactors are unable to explain the pricing errors of any of the models.Some nonrisk-based explanations, which posit a wide spread in abnormalreturns, may be a more plausible source of explaining the pricing errorsof the factor models.     

The role of co-skewness in the pricing of real estate

The current study investigates whether systematic skewness offers an alternative perspective as to why the risk-adjusted returns on real estate should be similar to that for stocks. This is not a trivial issue since an affirmative finding implies that we might be incorrectly measuring real estate risk from both a pricing and a portfolio allocation perspective. A multivariate test of the Kraus-Litzenberger model is used to investigate this skewness proposition with the K-L CAPM tested against several alternative versions of the CAPM. The study finds that the Kraus-Litzenberger model offers additional insights into the measurement of real estate risk. Evidence is also found that both the zero beta and the consumption-oriented CAPM hold, which is consistent with the recent literature in real estate.     

Market Power,Efficiency and the Dispersion of Systematic Risk

A number of studies have used the Capital Asset Pricing Model (CAPM) to integrate product market and financial theories of the firm. We reexamine the relationship between product market structure and systematic risk at the firm and industry level. We show that theory yields no testable implications at the firm level. We show, however, that there is a relationship between the intraindustry dispersion of systematic risk and industry concentration which depends on the causes and consequences of concentration. Estimates of the relationship between the intraindustry variance of and concentration for a 1987 cross-section of U.S. industries suggest that concentration allows larger firms to exercise market power.     

An Intertemporal CAPM Approach to Evaluate Mutual Fund Performance

Merton (1973) and Campbell (1993) have demonstrated that if an investor anticipates information shifts, he will adjust his portfolio choice today in an attempt to hedge these shifts. Exploiting these insights, we construct a new performance measure to evaluate fund managers' hedging ability. This new measure is different from two widely adopted performance evaluation measures: securities selectivity and market timing. Moreover, an econometric methodology is developed to simultaneously estimate the magnitudes of these three portfolio performance evaluation measures. The results show that mutual fund managers are on average with positive security selection and negative market timing ability. Furthermore, the mutual funds with investment style classified as Asset Allocation generally have positive hedging timing ability.     

Financial Sector Risk and the Stock Returns: Evidence from Tokyo Stock Exchange Firms

We investigate whether the activity of financial firms creates value and/or risk to the economy within the asset pricing framework. We use stock return data from nonfinancial firms listed in the first section of the Tokyo Stock Exchange. The value-weighted index that is solely composed of nonfinancial firms is augmented with the index of the firms from the financial sector, and we estimate multivariate asset pricing model with these two indices. We note that our procedure can simultaneously take into account the cross-holding phenomena among Japanese firms, especially between the financial sector and the nonfinancial sector. Our augmented index model performs well both with cross-sectional Fama and MacBeth regression test and GMM test. Our two index model with additional Fama and French's HML factor can capture cross-sectional variations of the returns of sample portfolios better than the original Fama and French model can, when measured by Hansen and Jagannathan distance measure. We find that this additional new sector variable can be a substitute for Fama and French's size factor, but not related to the bond index return. This variable has similar factor characteristic as money supply growth or the term structure, but the latter variables contain more information than the former. Morever, our financial sector model helps explain the return and risk structure of Japanese firms during the so-called bubble period.     

Aggregate volatility expectations and threshold CAPM

We propose a volatility-based capital asset pricing model (V-CAPM) in which asset betas change discretely with respect to changes in investors’ expectations regarding near-term aggregate volatility. Using a novel measure to proxy uncertainty about expected changes in aggregate volatility, i.e. monthly range of the VIX index (RVIX), we find that portfolio betas change significantly when uncertainty about aggregate volatility expectations is beyond a certain threshold level. Due to changes in their market betas, small and value stocks are perceived as riskier than their big and growth counterparts in bad times, when uncertainty about aggregate volatility expectations is high. The proposed model yields a positive and significant market risk premium during periods when investors do not expect significant uncertainty in near-term aggregate volatility. Our findings support a volatility-based time-varying risk explanation.