Asset Pricing with Conditioning Information: A New Test

This paper presents a new test of conditional versions of the Sharpe-Lintner CAPM, the Jagannathan and Wang (1996) extension of the CAPM, and the Fama and French (1993) three-factor model. The test is based on a general nonparametric methodology that avoids functional form misspecification of betas, risk premia, and the stochastic discount factor. Our results provide a novel view of empirical performance of these models. In particular, we find that a nonparametric version of the Fama and French model performs well, even when challenged by momentum portfolios.     

Event studies with a contaminated estimation period

Event studies are an important tool for empirical research in Finance. Since the seminal contribution of Fama et al. [Fama, E., Fisher, L., Jensen, M., Roll, R., 1969. The adjustment of stock prices to new information. International Economic Review 10, 1–21], there have been many enhancements to the classical test methodology. Somewhat surprisingly, the estimation period has attracted less interest. It is usually routinely determined as a fixed window prior to the event announcement day. In this study, we propose a test that reduces the impact of potentially unrelated events during the estimation period. Our proposition is based on a two-state version of the classical market model as a return-generating process. We present standard specification and power analyses. The results highlight the importance of explicitly controlling for unrelated events occurring during the estimation window, especially in the presence of event-induced increase in return volatility.     

DISTRIBUTIONS OF FINANCIAL RATIOS IN THE COMMERCIAL BANKING INDUSTRY

Much research in banking assumes that the data are normally distributed. There has been little empirical confirmation of this assumption. In this paper, the normality assumption is subjected to an extensive test using data for virtually all U.S. commercial banks for several years. The statistical characteristics of 11 common financial ratios are investigated. The findings reject any broad assumption of population normality.     

Volatility Risk Premium,Risk Aversion,and the Cross‐Section of Stock Returns

We test if innovations in investor risk aversion are a priced factor in the stock market. Using 25 portfolios sorted on book‐to‐market and size as test assets, our new factor together with the market factor explains 64% of the variation in average returns compared to 60% for the Fama‐French model. The new factor is generally significant with an estimated risk premium close to its time series mean also when industry portfolios and portfolios sorted on previous returns are augmented to the test assets.     

CAPM and Option Pricing With Elliptically Contoured Distributions

This article offers an alternative proof of the capital asset pricing model (CAPM) when asset returns follow a multivariate elliptical distribution. Empirical studies continue to demonstrate the inappropriateness of the normality assumption for modeling asset returns. The class of elliptically contoured distributions, which includes the more familiar Normal distribution, provides flexibility in modeling the thickness of tails associated with the possibility that asset returns take extreme values with nonnegligible probabilities. As summarized in this article, this class preserves several properties of the Normal distribution. Within this framework, we prove a new version of Stein's lemma for this class of distributions and use this result to derive the CAPM when returns are elliptical. Furthermore, using the probability distortion function approach based on the dual utility theory of choice under uncertainty, we also derive an explicit form solution to call option prices when the underlying is log‐elliptically distributed. The Black–Scholes call option price is a special case of this general result when the underlying is log‐normally distributed.     

A conditional multifactor analysis of return momentum

Although the Fama–French three-factor model captures most CAPM anomalies, it still fails to explain return momentum. This paper shows that the incorporation of conditioning information into an asset-pricing model is one way to capture return momentum. Results from the conditional regression with linear exposures in the instruments show clear evidence that both small minus big (SMB) and high minus low (HML) risks are time varying and that momentum and reversal return patterns have different time-varying risk characteristics. The conditional Fama–French regression model seems, however, to remain misspecified. Conversely, when the linearity assumption is relaxed and cross-sectional restrictions are imposed, the conditional pricing model appears to capture both short-term momentum and long-term reversal.     

The Conditional Relationship Between Beta and Returns: A Reassessment

Abstract:  Several recent empirical tests of the Capital Asset Pricing Model have been based on the conditional relationship between betas and market returns. This paper shows that this method needs reconsideration. An adjusted version of this test is presented. It is then demonstrated that the adjusted technique has similar, or lower, power to the more easily implemented CAPM test of Fama and MacBeth (1973) if returns are normally distributed.     

Resolving the Presidential Puzzle

Many financial economists are puzzled by the fact that stock returns are higher under Democratic than Republican presidencies. In this paper, we test whether this return differential is explained by risk using a conditional version of the Fama and French (1993) model that allows risk to vary across political cycles. We find that the presidential puzzle can be explained when risk is properly taken into account. Much of the return differential can be attributed to the fact that Democratic presidencies are associated with higher market and default risk premiums than their Republican counterparts.     

Conditional beta pricing models: A nonparametric approach

We propose a two-stage procedure to estimate conditional beta pricing models that allows for flexibility in the dynamics of asset betas and market prices of risk (MPR). First, conditional betas are estimated nonparametrically for each asset and period using the time-series of previous data. Then, time-varying MPR are estimated from the cross-section of returns and betas. We prove the consistency and asymptotic normality of the estimators. We also perform Monte Carlo simulations for the conditional version of the three-factor model of Fama and French (1993) and show that nonparametrically estimated betas outperform rolling betas under different specifications of beta dynamics. Using return data on the 25 size and book-to-market sorted portfolios, we find that the nonparametric procedure produces a better fit of the three-factor model to the data, less biased estimates of MPR and lower pricing errors than the Fama–MacBeth procedure with betas estimated under several alternative parametric specifications.     

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.     

A Dynamic Model of Firm Valuation

We propose a dynamic version of the dividend discount model, solve it in closed form, and assess its empirical validity. The valuation method is tractable and can be easily implemented. We find that our model produces equity value forecasts that are very close to market prices, and explains a large proportion of the observed variation in share prices. Moreover, we show that a simple portfolio strategy based on the difference between market and estimated values earns considerably positive returns. These returns cannot be simply explained either by the Fama‐French three‐factor model (even after adding a momentum factor) or the Fama‐French five‐factor model.     

Asset-pricing Tests under Alternative Distributions

Given the normality assumption, we reject the mean-variance efficiency of the Center for Research in Security Prices value-weighted stock index for three of the six consecutive ten-year subperiods from 1926 to 1986. However, the normality assumption is strongly rejected by the data. Under plausible alternative distributional assumptions of the elliptical class, the efficiency can no longer be rejected. When the normality assumption is violated but the ellipticity assumption is maintained, many tests tend to be biased toward overrejection and both the accuracy of estimated beta and $R^2$ are usually overstated.     

Macroeconomic risk and the cross-section of stock returns

We develop a conditional version of the consumption capital asset pricing model (CCAPM) using the conditioning variable from the cointegrating relation among macroeconomic variables (dividend yield, term spread, default spread, and short-term interest rate). Our conditioning variable has a strong power to predict market excess returns in the presence of competing predictive variables. In addition, our conditional CCAPM performs approximately as well as Fama and French’s (1993) three-factor model in explaining the cross-section of the Fama and French 25 size and book-to-market sorted portfolios. Our specification shows that value stocks are riskier than growth stocks in bad times, supporting the risk-based story.     

Asset Pricing and the Illiquidity Premium

In this paper, we examine the asset‐pricing role of liquidity (as proxied by share turnover) in the context of the Fama and French (1993) three‐factor model. Our analysis employs monthly Australian data, covering the sample period from 1990 to 1998. The key finding of our research is that the main test is unable to reject the test of over‐identifying restrictions, thus supporting the overall favorability of the liquidity‐augmented Fama–French model. In addition, we find that the asset‐pricing performance of the liquidity factor is generally very robust to a wide range of sensitivity checks.     

Information based trade,the PIN variable,and portfolio style differences: Evidence from Tokyo stock exchange firms

We investigate whether the variables related to information based trade proposed by Easley et al. [Easley, D., Kiefer, N.M., O'Hara, M., Paperman, J.B., 1996. Liquidity, information, and infrequently traded stocks. Journal of Finance 51, 1405–1436.] help explain the daily price discovery process in an electronically order-driven market of the Tokyo Stock Exchange using the microstructure tick data. We find strong evidence that the value firms show higher probability of bad news occurrences than the growth firms. We also find that the PIN is higher for smaller firms as is the case in the U.S. With the portfolio ranking tests and the Fama and MacBeth test we find that the alpha variable, which represents the information event occurrence rate, is systematically related to required returns, while the evidence related to the PIN is weaker. In the final Fama and MacBeth test, in which the PIN or alpha variable is used as an additional explanatory variable to the benchmark Fama and French three factor model, we find that the sign of the alpha variable supports our hypothesis that the arrival of new information reduces the risk of the stock, though not significantly. We also find that the higher PIN value increases the risk of the stock, at the same time it can marginally improve the explanatory power of the multifactor model. We conclude that the PIN variable cannot be a substitutable proxy variable for the book-to-market factor unlike in the U.S., and that it is strongly related to the size variable.     

Conditional coskewness and asset pricing

We explore the empirical usefulness of conditional coskewness to explain the cross-section of equity returns. We find that coskewness is an important determinant of the returns to equity, and that the pricing relationship varies through time. In particular we find that when the conditional market skewness is positive investors are willing to sacrifice 7.87% annually per unit of gamma (a standardized measure of coskewness risk) while they only demand a premium of 1.80% when the market is negatively skewed. A similar picture emerges from the coskewness factor of Harvey and Siddique (Harvey, C., Siddique, A., 2000a. Conditional skewness in asset pricing models tests. Journal of Finance 65, 1263–1295.) (a portfolio that is long stocks with small coskewness with the market and short high coskewness stocks) which earns 5.00% annually when the market is positively skewed but only 2.81% when the market is negatively skewed. The conditional two-moment CAPM and a conditional Fama and French (Fama, E., French, K., 1992. The cross-section of expected returns. Journal of Finance 47,427465.) three-factor model are rejected, but a model which includes coskewness is not rejected by the data. The model also passes a structural break test which many existing asset pricing models fail.     

Kernel-type estimators for the distortion risk premiums of heavy-tailed distributions

A new kernel-type estimator for the distortion risk premiums of heavy-tailed losses is introduced. Using a least-squares approach, a bias-reduced version of this estimator is proposed. Under suitable assumptions, the asymptotic normality of the given estimators is established. A small simulation study, to illustrate the performance of our method, is carried out.     

Security factors as linear combinations of economic variables

A new framework is proposed to find the best linear combinations of economic variables that optimally forecast security factors. In particular, we obtain such combinations from Chen et al. (Journal of Business 59, 383–403, 1986) five economic variables, and obtain a new GMM test for the APT which is more robust than existing tests. In addition, by using Fama and French's (1993) five factors, we test whether fewer factors are sufficient to explain the average returns on 25 stock portfolios formed on size and book-to-market. While inconclusive in-sample, a three-factor model appears to perform better out-of-sample than both four- and five-factor models.     

On the distribution of government bond returns: evidence from the EMU

This paper assesses the statistical distribution of daily EMU bond returns for the period 1999–2012. The normality assumption is tested and clearly rejected for all European countries and maturities. Although skewness plays a minor role in this departure from normality, it is mainly due to the excess kurtosis of bond returns. Therefore, we test the Student’s t, skewed Student’s t, and stable distribution that exhibit this feature. The financial crisis leads to a structural break in the time series. We account for this and retest the alternative distributions. A value-at-risk application underlines the importance of our findings for investors. In sum, excess kurtosis in bond returns is essential for risk management, and the stable distribution captures this feature best.     

MULTI-PERIOD CAPITAL ASSET PRICING MODELS - A REVIEW OF DEVELOPMENT

This paper considers the single-period Capital Asset Pricing Model and its shortcomings for corporate investment decisions. The conditions under which a multi-period version of the model can be developed are discussed. Previous notable attempts at developing such a model by a number of writers including Stapleton, Brennan, Bogue and Roll, Myers and Turnbull, and Fama are reviewed.