Asset Pricing Restrictions on Predictability

U.S. stock portfolios sorted on size, momentum, transaction costs, M/B, I/A and ROA ratios, and industry classication show considerable levels and variation of return predictability, inconsistent with asset pricing models. This means that a predictable risk premium is not equal to compensation for systematic risk as implied by asset pricing theory (Kirby 1998). We show that introducing market frictions relaxes these asset pricing moments from a strict equality to a range. Empirically, it is not short sales constraints but transaction costs (below 35 basis points) that help to reconcile the observed predictability with the Fama-French-Carhart four- factor model and the Chen-Novy-Marx-Zhang three factor model, and partly with the Durable Consumption model. Across the sorts, predictability in industry returns can be reconciled with all models considered with only 25 basis points transaction costs, whereas for momentum and ROA portfolios up to 115 basis points are needed

Evaluating Style Analysis

In this paper we evaluate applications of (return based) style analysis. The portfolio and positivity constraints imposed by style analysis are useful in constructing mimicking portfolios without short positions. Such mimicking portfolios can be used e.g. to construct efficient portfolios of mutual funds with desired factor loadings if the factor loadings in the underlying factor model are positively weighted portfolios. Under these conditions style analysis may also be used to determine a benchmark portfolio for performance measurement. Attribution of the returns on portfolios of which the actual composition is unobserved to specific asset classes on the basis of return based style analysis is attractive if moreover there are no additional cross exposures between the asset classes and if fund managers hold securities that on average have a beta of one relative to their own asset class. If such restrictions are not met, and in particular if the factor loadings do not generate a positively weighted portfolio, the restrictions inherent in return based style analysis distort the outcomes of standard regression approaches rather than that the analysis is improved. The size of the distortions is illustrated by considering empirical results on style analysis of US mutual funds

Currency Hedging for International Stock Portfolios

This paper tests whether hedging currency risk improves the performance of international stock portfolios. We use a generalized performance measure which allows for investor-dependencies such as different utility functions and the presence of nontraded risks. In addition we show that an auxiliary regression, similar to the Jensen regression, provides a wealth of information about the optimal portfolio holdings for investors for the non mean-variance case. This is analogous to the information provided by the Jensen regression about optimal portfolio holdings for the mean-variance case. Our empirical results show that static hedging with currency forwards does not lead to improvements in portfolio performance for a US investor that holds a stock portfolio from the G5 countries. On the other hand, hedges that are conditional on the current interest rate spread do lead to significant performance improvements. Also, when an investor has a substantial exogenous exposure to one of the currencies, currency hedging clearly improves his portfolio performance. While these results hold for investors with power utility as well as with mean-variance utility functions, the optimal hedge ratios for these investors are different

The Price of Commodity Risk in Stock and Futures Markets

We find that commodity risk is priced in the cross-section of US stock returns. Following the financialization of commodities, investors hedge commodity price risk directly in the futures market, primarily via commodity index investments, whereas before they gained commodity exposure mainly via the stock market. As a result, we find that the annualized average returns of high-minus-low commodity beta stocks change from -8% pre-financialization to 11% post-financialization. As stock market investors increasingly participate in commodity futures markets, stock market risk is also priced in the cross-section of commodity futures returns