Stochastic Discount Factor Bounds with Conditioning Information

Hansen and Jagannathan (HJ, 1991) describe restrictions on the volatility of stochastic discount factors (SDFs) that price a given set of asset returns. This paper compares the sampling properties of different versions of HJ bounds that use conditioning information in the form of a given set of lagged instruments. HJ describe one way to use conditioning information. Their approach is to multiply the original returns by the lagged variables, and much of the asset pricing literature to date has followed this ihmultiplicativel. approach. We also study two versions of optimized HJ bounds with conditioning information. One is from Gallant, Hansen and Tauchen (1990) and the second is based on the unconditionally-efficient portfolios derived in Ferson and Siegel (2000). We document finite-sample biases in the HJ bounds, where the biased bounds reject asset-pricing models too often. We provide useful correction factors for the bias. We also evaluate the asymptotic standard errors for the HJ bounds, from Hansen, Heaton and Luttmer (1995).

Conditioning Variables and the Cross-Section of Stock Returns

Previous studies have identified predetermined variables that have some power to explain the time series of stock and bond returns. This paper shows that loadings on the same variables also provide significant cross-sectional explanatory power for stock portfolio returns. These loadings are important, over and the above the variables advocated by Fama and French (1993) in their three factor model,' and also the four factors of Elton, Gruber and Blake (1995). The explanatory power of the loadings on lagged variables is robust to various portfolio grouping procedures and other considerations. The lagged variables reveal information about the cross-section of expected returns that is not captured by popular asset pricing factors. These results carry implications for risk analysis, performance measurement, cost-of-capital calculations and other applications.

An Exploratory Investigation of the Fundamental Determinants of National Equity Market Returns

This paper studies average and conditional expected returns in national equity markets, and their relation to a number of fundamental country attributes. The attributes are organized into three groups. The first is relative valuation ratios, such as price-to-book-value, cash-flow, earnings and dividends. The second group measures relative economic performance and the third measures industry structure. We find that average returns across countries are related to the volatility of their price-to-book ratios. Predictable variation in returns is also related to relative gross domestic product, interest rate levels and dividend-price ratios. We explore the hypothesis that cross-sectional variation in the country attributes proxy for variation in the sensitivity of national markets to global measures of economic risks. We test single-factor and two-factor models in which countries' conditional betas are assumed to be functions of the more important fundamental attributes.

Sources of Risk and Expected Returns in Global Equity Markets

This paper empirically examines multifactor asset pricing models for the returns and expected returns on eighteen national equity markets. The factors are chosen to measure global economic risks. Although previous studies do not reject the unconditional mean- variance efficiency of a world market portfolio, our evidence indicates that the tests are low in power, and the world market betas do not provide a good explanation of cross-sectional differences in average returns. Multiple beta models provide an improved explanation of the equity returns.

Testing Portfolio Efficiency with Conditioning Information

We develop asset pricing models' implications for portfolio efficiency when there is conditioning information in the form of a set of lagged instruments. A model of expected returns identifies a portfolio that should be minimum variance efficient with respect to the conditioning information. Our tests refine previous tests of portfolio efficiency, using the conditioning information optimally. We reject the efficiency of all static or time-varying combinations of the three Fama-French (1996) factors with respect to the conditioning information and also the conditional efficiency of time-varying combinations of the factors, given standard lagged instruments.

Tests of Multifactor Pricing Models, Volatility Bounds and Portfolio Performance

Three concepts: stochastic discount factors, multi-beta pricing and mean variance efficiency, are at the core of modern empirical asset pricing. This paper reviews these paradigms and the relations among them, concentrating on conditional asset pricing models where lagged variables serve as instruments for publicly available information. The different paradigms are associated with different empirical methods. We review the variance bounds of Hansen and Jagannathan (1991), concentrating on extensions for conditioning information. Hansen's (1982) Generalized Method of Moments (GMM) is briefly reviewed as an organizing principle. Then, cross-sectional regression approaches as developed by Fama and MacBeth (1973) are reviewed and used to interpret empirical factors, such as those advocated by Fama and French (1993, 1996). Finally, we review the multivariate regression approach, popularized in the finance literature by Gibbons (1982) and others. A regression approach, with a beta pricing formulation, and a GMM approach with a stochastic discount factor formulation, may be considered competing paradigms for empirical work in asset pricing. This discussion clarifies the relations between the various approaches. Finally, we bring the models and methods together, with a review of the recent conditional performance evaluation literature, concentrating on mutual funds and pension funds.

Spurious Regressions in Financial Economics?

Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of Yule (1926) and Granger and Newbold (1974). Data mining for predictor variables interacts with spurious regression bias. The two effects reinforce each other, because more highly persistent series are more likely to be found significant in the search for predictor variables. Our simulations suggest that many of the regressions in the literature, based on individual predictor variables, may be spurious

Weak and Semi-Strong Form Stock Return Predictability Revisited

This paper makes indirect inference about the time-variation in expected stock returns by comparing unconditional sample variances to estimates of expected conditional variances. The evidence reveals more predictability as more information is used, and no evidence that predictability has diminished in recent years. Semi-strong form evidence suggests that time-variation in expected returns remains economically important.

Weak and Semi-Strong Form Stock Return Predictability, Revisited

This paper makes indirect inference about the time-variation in expected stock returns by comparing unconditional sample variances to estimates of expected conditional variances. The evidence reveals more predictability as more information is used, and no evidence that predictability has diminished in recent years. Semi-strong form evidence suggests that time-variation in expected returns remains economically important.

Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression

This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become baised. Previous studies overstate the significance of time-varying alphas.