Some Empirical Tests of the Theory of Arbitrage Pricing

We estimate the parameters of Ross's Arbitrage Pricing Theory (APT). Using daily return data during the 1963–78 period, we compare the evidence on the APT and the Capital Asset Pricing Model (CAPM) as implemented by market indices and find that the APT performs well. The theory is further supported in that estimated expected returns depend on estimated factor loadings, and variables such as own variance and firm size do not contribute additional explanatory power to that of the factor loadings.     

Aggregate Jump and Volatility Risk in the Cross‐Section of Stock Returns

We examine the pricing of both aggregate jump and volatility risk in the cross‐section of stock returns by constructing investable option trading strategies that load on one factor but are orthogonal to the other. Both aggregate jump and volatility risk help explain variation in expected returns. Consistent with theory, stocks with high sensitivities to jump and volatility risk have low expected returns. Both can be measured separately and are important economically, with a two‐standard‐deviation increase in jump (volatility) factor loadings associated with a 3.5% to 5.1% (2.7% to 2.9%) drop in expected annual stock returns.     

Arbitrage pricing with information

The Arbitrage Pricing Theory is extended to a setting where investors possess information about future asset returns. A no-arbitrage pricing restriction is obtained with arbitrage conditioned on an investor's information. The pricing restriction contains unconditional factor loadings and either conditional or unconditional expected returns. Thus, tests of the theory can be based solely on time-series estimates of unconditional moments. Additional tests based on conditional expected returns are also appropriate.     

Volatility risk and the value premium: Evidence from the French stock market

This paper documents that systematic volatility risk is an important factor that drives the value premium observed in the French stock market. Using returns on at-the-money straddles written on the CAC 40 index as a proxy for systematic volatility risk, I document significant differences between volatility factor loadings of value and growth stocks. Furthermore, when markets are classified into expected booms and recessions, volatility factor loadings are also time-varying. When expected market risk premium is above its average, i.e. during expected recessions, value stocks are seen riskier than their growth counterparts. This implies in bad times, investors shift their preferences away from value firms. Instead they use growth stocks as hedges against deteriorations in their wealth during those times. The findings are in line with the predictions of rational asset pricing theory and support a “flight-to-quality” explanation.     

Return generating process and the determinants of term premiums

This paper examines asset pricing theories for treasury bonds using longer maturities than previous studies and employing a simple multi-factor model. We allow bond factor loadings to vary over time according to term structure variables. The model examines not only the time variation in the expected returns of bonds but also their unexpected returns. This allows us to explicitly test some asset pricing restrictions which are difficult to study under existing frameworks. We confirm that the pure expectation theory of the term structure of interest rates is rejected by the data. Our empirical study of a two-factor model finds substantial evidence of time-varying term-premiums and factor loadings. The fact that factor loadings vary with long-term interest rates and yield spreads suggest that bond return volatilities are sensitive to interest rate levels.     

A Labor Capital Asset Pricing Model

We show that labor search frictions are an important determinant of the cross‐section of equity returns. Empirically, we find that firms with low loadings on labor market tightness outperform firms with high loadings by 6% annually. We propose a partial equilibrium labor market model in which heterogeneous firms make dynamic employment decisions under labor search frictions. In the model, loadings on labor market tightness proxy for priced time‐variation in the efficiency of the aggregate matching technology. Firms with low loadings are more exposed to adverse matching efficiency shocks and require higher expected stock returns.     

Modeling Corporate Bond Returns

We propose a conditional factor model for corporate bond returns with five factors and time-varying factor loadings. We have three main empirical findings. First, our factor model excels in describing the risks and returns of corporate bonds, improving over previously proposed models in the literature by a large margin. Second, our model recommends a systematic bond investment portfolio whose high out-of-sample Sharpe ratio suggests that the credit risk premium is notably larger than previously estimated. Third, we find closer integration between debt and equity markets than found in prior literature.     

On Testing the Arbitrage Pricing Theory: Inter-Battery Factor Analysis

This paper tests the Arbitrage Pricing Theory (APT) by estimating the factor loadings that are consistent between two industry groups of securities. One of the pitfalls in the study by Roll and Ross is that the factors estimated in one group may not be the same with the factors estimated in another group. This raises some concerns on the acceptability of their conclusions. For our study, we employ inter-battery factor analysis which enables us to estimate factor loadings by constraining the factors to be the same between two different groups. Our results show that there seem to be five or six inter-group common factors that generate daily returns for two industry groups of securities, and these inter-group common factors do not seem to depend on the size of groups. Also, based on our cross-sectional tests on the risk premia, we conclude that the APT should not be rejected.     

Exchange risk and universal returns: A test of international arbitrage pricing theory

According to the international arbitrage pricing theory (IAPT) posited by Solnik (1983), currency movements affect assets' factor loadings and associated risk premiums. Based on a novel universal return decomposition, we propose an empirical model to test this proposition and perform tests using U.S. stock returns in the period 1975–2008. Our results confirm that currency movements significantly affect the market betas of a large proportion of stocks. Further cross-sectional tests indicate that currency movements affecting the market factor are significantly priced in stock returns. Based on these and other findings, we conclude that Solnik's IAPT is supported. An important implication of our findings is that exchange rate risk can broadly affect stock returns through both factor loading and residual factor channels.     

Exchange risk and universal returns: A test of international arbitrage pricing theory

According to the international arbitrage pricing theory (IAPT) posited by Solnik (1983), currency movements affect assets' factor loadings and associated risk premiums. Based on a novel universal return decomposition, we propose an empirical model to test this proposition and perform tests using U.S. stock returns in the period 1975–2008. Our results confirm that currency movements significantly affect the market betas of a large proportion of stocks. Further cross-sectional tests indicate that currency movements affecting the market factor are significantly priced in stock returns. Based on these and other findings, we conclude that Solnik's IAPT is supported. An important implication of our findings is that exchange rate risk can broadly affect stock returns through both factor loading and residual factor channels.     

Government Bond Returns,Measurement of Interest Rate Risk,and the Arbitrage Pricing Theory

Empirical tests are reported for Ross' arbitrage pricing theory using monthly data for U.S. Treasury securities during the 1960–1979 period. We find that mean returns on bond portfolios are linearly related to at least two factor loadings. Multivariate test results, however, are not consistent with the APT. Our sample data in the U.S. Treasury securities market are also not consistent with either version of the CAPM. One-month-ahead forecasts of excess returns using factor-generating models are compared with corresponding naive predictions or predictions using the “market model” with various market portfolios.     

Expected Option Returns

This paper examines expected option returns in the context of mainstream asset-pricing theory. Under mild assumptions, expected call returns exceed those of the underlying security and increase with the strike price. Likewise, expected put returns are below the risk-free rate and increase with the strike price. S&P index option returns consistently exhibit these characteristics. Under stronger assumptions, expected option returns vary linearly with option betas. However, zero-beta, at-the-money straddle positions produce average losses of approximately three percent per week. This suggests that some additional factor, such as systematic stochastic volatility, is priced in option returns.     

Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns

Consistent with the post-1962 US evidence by Ang et al. [Ang, A., Hodrick, R., Xing Y., Zhang, X., 2006. The cross-section of volatility and expected returns. Journal of Finance 51, 259–299], we find that stocks with high idiosyncratic variance (IV) have low CAPM-adjusted expected returns in both pre-1962 US and modern G7 data. We also test in three ways the conjecture that IV is a proxy of systematic risk. First, the return difference between low and high IV stocks – that we dub as IVF – is a priced factor in the cross-section of stock returns. Second, loadings on lagged market variance and lagged average IV account for a significant portion of variation in average returns on portfolios sorted by IV. Third, the variance of IVF correlates closely with average IV, and the two variables have similar explanatory power for the time-series and cross-sectional stock returns.     

Predictive Systems: Living with Imperfect Predictors

We develop a framework for estimating expected returns—a  predictive system —that allows predictors to be imperfectly correlated with the conditional expected return. When predictors are imperfect, the estimated expected return depends on past returns in a manner that hinges on the correlation between unexpected returns and innovations in expected returns. We find empirically that prior beliefs about this correlation, which is most likely negative, substantially affect estimates of expected returns as well as various inferences about predictability, including assessments of a predictor's usefulness. Compared to standard predictive regressions, predictive systems deliver different expected returns with higher estimated precision.     

An empirical examination of the implications of arbitrage pricing theory

This paper presents a comprehensive set of tests of the implications of the Arbitrage Pricing Theory. We find, unlike previously reported results, a very limited relationship between the expected returns and the covariance (factor loadings) measures of risk. Furthermore, unique variance measures of risk, while generally making only small contributions to the explanation of asset returns, turn out to be significant about as frequently as the coveriance measures of risk — which is inconsistent with the Arbitrage Pricing Theory model. The intercept tests are more mixed but provide only limited support to the model.     

The equity premium and market integration: Evidence from international data

This paper examines the equity premium puzzle by looking at stock market data from 39 countries. For each of these countries, average total return as well as excess returns was estimated for the past 20–30 years. I find that emerging markets have higher excess returns than developed markets, but when adjusted for risk developed markets have higher returns. I test the theory that degree of integration with global markets is a major explanatory factor for differences in excess returns, as the demand for domestic equities may be greater in countries that are less integrated and thus have less access to alternative overseas assets. I find a positive relationship between degree of integration and excess returns, which is evidence in favor of this theory.     

Integrating Factor Models

This paper develops a comprehensive framework to address uncertainty about the correct factor model. Asset pricing inferences draw on a composite model that integrates over competing factor models weighted by posterior probabilities. Evidence shows that unconditional models record near-zero probabilities, while postearnings announcement drift, quality-minus-junk, and intermediary capital are potent factors in conditional asset pricing. Out-of-sample, the integrated model performs well, tilting away from subsequently underperforming factors. Model uncertainty makes equities appear considerably riskier, while model disagreement about expected returns spikes during crash episodes. Disagreement spans all return components involving mispricing, factor loadings, and risk premia.     

Conditional Asset Pricing and Stock Market Anomalies in Europe

This study provides European evidence on the ability of static and dynamic specifications of the Fama‐French (1993) three‐factor model to price 25 size‐B/M portfolios. In contrast to US evidence, we detect a small‐growth premium and find that the size effect is still present in Europe. Furthermore, we document strong time variation in factor risk loadings. Incorporating these risk fluctuations in conditional specifications of the three‐factor model clearly improves its ability to explain time variation in expected returns. However, the model still fails to completely capture cross‐sectional variation in returns as it is unable to explain the momentum effect.     

Fluctuations in the UK equity market: what drives stock returns?

Present value parameters from a state-space model are estimated for the UK FT All-Share Index. The estimated parameters are used to construct a time series of expected future returns and expected future values of dividend growth, both of which are found to be time-varying with persistent components. Variations in the price-dividend ratio appear to be driven primarily by the variance in expected returns. A comparison with the findings from a present value-constrained vector autoregression model indicates that the latter forecasts future realized returns and dividend growth better than the series constructed using a state-space approach. Furthermore, when the model is estimated for monthly and quarterly data, expected dividend growth is found to be more persistent.     

Fear and the Fama‐French Factors

Investors’ expectations of market volatility, captured by the VIX (the Chicago Board Options Exchange's volatility index, also known as the “investor fear gauge”), affects the expected returns of US equities. Changes in the VIX drive variations in the expected returns of the factors included in the Fama and French three‐factor model augmented with a momentum factor. The market risk premium (R_m– R_f) and the value premium (HML) are especially sensitive to changes in the VIX. An increase in expected volatility is associated with flights to quality and increases in estimated required returns.