Tracking down distress risk

This paper shows that exposure to aggregate distress risk is the underlying source of the premiums for the Fama-French size (SMB) and value (HML) factors. Using a unique data set of aggregate business failures of both private and public firms from 1926 to 1997, I build portfolios that track news about future firm failures. These tracking portfolios optimally hedge aggregate distress risk and earn a Capital Asset Pricing Model (CAPM) alpha of approximately −4% a year. Both HML and SMB predict changes in future failure rates. Small stocks have lower returns than large stocks and value stocks have lower returns than growth stocks when the market expects an increase in future failure rates. Finally, a two-factor model with the market and the tracking portfolio for aggregate distress as factors does as well as the Fama-French three-factor model in pricing the 25 size and book-to-market sorted portfolios.     

Investing in equity mutual funds

We construct optimal portfolios of equity funds by combining historical returns on funds and passive indexes with prior views about asset pricing and skill. By including both benchmark and nonbenchmark indexes, we distinguish pricing-model inaccuracy from managerial skill. Modest confidence in a pricing model helps construct portfolios with high Sharpe ratios. Investing in active mutual funds can be optimal even for investors who believe managers cannot outperform passive indexes. Optimal portfolios exclude hot-hand funds even for investors who believe momentum is priced. Our large universe of funds offers no close substitutes for the Fama-French and momentum benchmarks.     

An alternative measure of the “world market portfolio”: Determinants, efficiency, and information content

The world market portfolio plays an important role in international asset pricing, but is unobservable in practice. We first propose a framework for constructing a market proxy that corresponds to the “market portfolio” of financial theory. We then construct this proxy, analyze its determinants and test its efficiency and explanatory power over the period 1975-2007 with respect to the return generating processes of a broad asset universe. We show that its major determinants are traded assets and that it is not efficient. However, it is significant for explaining individual asset returns over an asset universe that includes stocks, bonds, money markets and commodities. The explanatory information is incremental to what is available in traded asset prices and the significance of this information is robust with respect to diversified portfolios generated by factor analysis and to characteristic-sorted portfolios as well as to various model specifications, including the single-index model, the Fama-French (1992) three factor model for stocks, and various specifications of multi-index models hedged and unhedged for foreign currency risk.     

Testing conditional factor models: A nonparametric approach

Some recent studies of conditional factor models do not specify conditioning information but use data from small windows to estimate the time series of conditional alphas and betas. In this paper, we propose a nonparametric method using an optimal window to estimate time-varying coefficients. In addition, we offer two empirical tests of a conditional factor model. Using our new method, we examine the performance of the conditional CAPM and the conditional Fama-French three-factor model in explaining the return variations of portfolios sorted by size, book-to-market ratios, and past returns, for which recent literature has generated controversial results. We find that, although in general the conditional FF model outperforms the conditional CAPM, both models fail to explain well-known asset-pricing anomalies. Moreover, for both models, the failure is more pronounced for the equally-weighted portfolios than for the value-weighted ones.     

Predicting stock returns

This paper studies whether incorporating business cycle predictors benefits a real time optimizing investor who must allocate funds across 3,123 NYSE-AMEX stocks and cash. Realized returns are positive when adjusted by the Fama-French and momentum factors as well as by the size, book-to-market, and past return characteristics. The investor optimally holds small-cap, growth, and momentum stocks and loads less (more) heavily on momentum (small-cap) stocks during recessions. Returns on individual stocks are predictable out-of-sample due to alpha variation, whereas the equity premium predictability, the major focus of previous work, is questionable.     

Macroeconomic risks and characteristic-based factor models

We show that book-to-market, size, and momentum capture cross-sectional variation in exposures to a broad set of macroeconomic factors identified in the prior literature as potentially important for pricing equities. The factors considered include innovations in economic growth expectations, inflation, the aggregate survival probability, the term structure of interest rates, and the exchange rate. Factor mimicking portfolios constructed on the basis of book-to-market, size, and momentum therefore, serve as proxy composite macroeconomic risk factors. Conditional and unconditional cross-sectional asset pricing tests indicate that most of the macroeconomic factors considered are priced. The performance of an asset pricing model based on the macroeconomic factors is comparable to the performance of the Fama and French (1993) model. However, the momentum factor is found to contain incremental information for asset pricing.     

Style investing,comovement and return predictability

Barberis and Shleifer (2003) argue that style investing generates momentum and reversals in style and individual asset returns, as well as comovement between individual assets and their styles. Consistent with these predictions, in some specifications, past style returns help explain future stock returns after controlling for size, book-to-market and past stock returns. We also use comovement to identify style investing and assess its impact on momentum. High comovement momentum portfolios have significantly higher future returns than low comovement momentum portfolios. Overall, our results suggest that style investing plays a role in the predictability of asset returns.     

Does Focus Really Matter? Specialized vs. Diversified REITs

REITs that limit their holdings to a single property type typically defend their lack of diversification by claiming the management possesses special investment expertise in that particular property type. This paper investigates whether property type specialized REITs outperform diversified REITs thus providing evidence of superior management expertise associated with specialized REITs. We compare the performance of specialized versus diversified REIT portfolios during 1997–2006 by examining abnormal returns using CAPM and the Fama-French three factor model with momentum. We find no evidence of superior performance associated with REITs specializing in a single property type. On the contrary, diversified REITs somewhat outperform specialized REITs, but not by a statistically significant margin. Also, consistent with theory, we find that specialized REITs have higher market risk than diversified REITs.     

Asset pricing with a reference level of consumption: New evidence from the cross-section of stock returns

This paper presents an empirical evaluation of recently proposed asset pricing models which extend the standard preference specification by a reference level of consumption. We motivate an alternative model that accounts for the return on human capital as a determinant of the reference level. Our analysis is based on a broad cross-section of test assets, which provides a level playing field for a comparison to established benchmark models. The reference level model extended by human capital does a good job in explaining size and value premia. Estimated on Fama and French's size and book-to-market sorted portfolios, it outperforms Lettau and Ludvigson's scaled CCAPM and delivers average pricing errors comparable to the Fama-French three-factor model.     

Is the Mean Return of Hotel Real Estate Stocks Apt to Overreact to Past Performance?

This study examines the return patterns of hotel real estate stocks in the U.S. during the period from 1990 to 2007.We find that the magnitude and persistence of future mean returns of hotel real estate stocks can be predicted based on past returns, past earnings surprise, trading volume, firm size, and holding period. The empirical evidence found from this paper confirms that short-horizon contrarian profits can be partially explained by the lead-lag effects, while in the intermediate-term price momentum profits and long-term contrarian profits can be partially attributed to the firms’ overreaction to past price changes. Our results support the contrarian/overreaction hypothesis, and they are inconsistent with the Fama-French risk-based hypothesis or the underreaction hypothesis. The study also confirms the earning underreaction hypothesis and finds the high volume stocks tend to earn high momentum profits in the intermediate-term. The study finds that the earning momentum effect for hotel stocks is more short-lived and smaller in magnitude than the market average. Price momentum portfolios (or contrarian portfolios) of big hotel firms underperform small hotel firms and the hotel price momentum portfolio (or contrarian portfolios) significantly underperform the overall market over the intermediate-term (or the long-term). These findings imply that the U.S. hotel industry, particularly the big hotel firms, have experienced relatively conservative growth in the sample period. It suggests that a conservative hotel growth strategy accompanied by an internal-oriented financing policy is proper in a period of prosperity.     

MOMENTUM: DOES THE DATABASE MAKE A DIFFERENCE?

We examine discrepancies between the Center for Research in Security Prices (CRSP) and Trade and Quote (TAQ) databases by examining the returns of momentum strategies using each database. Momentum portfolios constructed from CRSP prices earn significant profits whereas similar portfolios using TAQ prices show losses. Adjusting TAQ prices with the TAQ dividends file or with the cumulative distribution factor provided by CRSP does not eliminate all differences. There are significant discrepancies in the way CRSP and TAQ record newly listed and delisted stocks. We document the residual (after all filters) price differences between the two databases and provide filters to adjust TAQ data for long sample periods and large sample sizes. Our filtering procedures allow for the possibility of examining intraday patterns in momentum profits.     

Momentum strategies in commodity futures markets

The article tests for the presence of short-term continuation and long-term reversal in commodity futures prices. While contrarian strategies do not work, the article identifies 13 profitable momentum strategies that generate 9.38% average return a year. A closer analysis of the constituents of the long–short portfolios reveals that the momentum strategies buy backwardated contracts and sell contangoed contracts. The correlation between the momentum returns and the returns of traditional asset classes is also found to be low, making the commodity-based relative-strength portfolios excellent candidates for inclusion in well-diversified portfolios.     

Momentum strategies based on reward–risk stock selection criteria

In this paper, we analyze momentum strategies that are based on reward–risk stock selection criteria in contrast to ordinary momentum strategies based on a cumulative return criterion. Reward–risk stock selection criteria include the standard Sharpe ratio with variance as a risk measure, and alternative reward–risk ratios with the expected shortfall as a risk measure. We investigate momentum strategies using 517 stocks in the S&P 500 universe in the period 1996–2003. Although the cumulative return criterion provides the highest average monthly momentum profits of 1.3% compared to the monthly profit of 0.86% for the best alternative criterion, the alternative ratios provide better risk-adjusted returns measured on an independent risk-adjusted performance measure. We also provide evidence on unique distributional properties of extreme momentum portfolios analyzed within the framework of general non-normal stable Paretian distributions. Specifically, for every stock selection criterion, loser portfolios have the lowest tail index and tail index of winner portfolios is lower than that of middle deciles. The lower tail index is associated with a lower mean strategy. The lowest tail index is obtained for the cumulative return strategy. Given our data-set, these findings indicate that the cumulative return strategy obtains higher profits with the acceptance of higher tail risk, while strategies based on reward–risk criteria obtain better risk-adjusted performance with the acceptance of the lower tail risk.     

Reward-risk momentum strategies using classical tempered stable distribution

We implement momentum strategies using reward-risk measures as ranking criteria based on classical tempered stable distribution. Performances and risk characteristics for the alternative portfolios are obtained in various asset classes and markets. The reward-risk momentum strategies with lower volatility levels outperform the traditional momentum strategy regardless of asset class and market. Additionally, the alternative portfolios are not only less riskier in risk measures such as VaR, CVaR and maximum drawdown but also characterized by thinner downside tails. Similar patterns in performance and risk profile are also found at the level of each ranking basket in the reward-risk portfolios. Higher factor-neutral returns achieved by the reward-risk momentum strategies are statistically significant and large portions of the performances are not explained by the Carhart four-factor model.     

The impact of regulation on market risk

While it is crucial to understand the impact of regulatory changes on market risk, the literature does not show how risk responds to expected regulatory changes that are specifically designed to change risk. Our paper fills this gap by providing a detailed study of one such case. Using both a sample of privatized U.K. companies, and U.K. and U.S. control portfolios, between 1993 and 2000, we show (both for the single-factor market model and the three-factor Fama-French model) that the observed changes in market risk are significant and consistent with theory.     

Investing in mutual funds when returns are predictable

This paper forms investment strategies in US domestic equity mutual funds, incorporating predictability in (i) manager skills, (ii) fund risk loadings, and (iii) benchmark returns. We find predictability in manager skills to be the dominant source of investment profitability—long-only strategies that incorporate such predictability outperform their Fama-French and momentum benchmarks by 2 to 4%/year by timing industries over the business cycle, and by an additional 3 to 6%/year by choosing funds that outperform their industry benchmarks. Our findings indicate that active management adds significant value, and that industries are important in locating outperforming mutual funds.     

Are good-news firms riskier than bad-news firms?

This paper examines the relative risk of good-news firms, i.e., those with high standardized unexpected earnings (SUE), and bad-news (low SUE) firms using a stochastic discount factor approach. We find that a stochastic discount factor constructed from a set of basis assets helps explain post-earnings-announcement drift (PEAD). The risk exposures on the pricing kernel increase monotonically from the lowest to highest SUE sorted portfolios. Specifically, good-news firms always have higher risk exposures than bad-news firms in both 10 SUE sorted portfolios and 25 size and SUE sorted portfolios. However, the estimated expected risk premium is too small to explain the observed magnitude of returns on the PEAD strategy. Our risk adjustment can explain only about one-fourth of the total magnitude of the average realized return to the PEAD strategy. As a result, the average risk-adjusted returns of earnings momentum strategies are mostly positive and significant. Overall, our results support the view that at least some portion of the returns to the earnings momentum strategies examined represent compensation for bearing increased risk.     

Characteristic-based mean-variance portfolio choice

We study empirical mean-variance optimization when the portfolio weights are restricted to be direct functions of underlying stock characteristics such as value and momentum. The closed-form solution to the portfolio weights estimator shows that the portfolio problem in this case reduces to a mean-variance analysis of assets with returns given by single-characteristic strategies (e.g., momentum or value). In an empirical application to international stock return indexes, we show that the direct approach to estimating portfolio weights clearly beats a naive regression-based approach that models the conditional mean. However, a portfolio based on equal weights of the single-characteristic strategies performs about as well, and sometimes better, than the direct estimation approach, highlighting again the difficulties in beating the equal-weighted case in mean-variance analysis. The empirical results also highlight the potential for ‘stock-picking’ in international indexes using characteristics such as value and momentum with the characteristic-based portfolios obtaining Sharpe ratios approximately three times larger than the world market.     

An Empirical Investigation of the Campbell-Cochrane Habit Utility Model

Abstract:  This paper tests whether the Campbell and Cochrane (1999) habit utility model generates a valid stochastic discount factor for the 25 Fama-French size/book-to-market and size/momentum sorted portfolios. Campbell and Cochrane (1999) derive a consumption based habit utility asset pricing model and calibrate it to aggregate US stock market data. However, they do not test whether their model is consistent with a larger cross section of asset returns. We test their model using the methodology of Hansen and Jagannathan (1991) and Burnside (1994) . In contrast to previous studies, we find that for reasonable parameter values, the model's stochastic discount factor is inside the Hansen-Jagannathan bounds and therefore satisfies the necessary conditions for a valid stochastic discount factor. We trace the difference between our results and previous studies to the method used to estimate the model's parameters and the parameter values themselves.