Rationalizing Momentum Interactions

Momentum profitability concentrates in high information uncertainty and high credit risk firms and is virtually nonexistent otherwise. This paper rationalizes such momentum interactions in equilibrium asset pricing. In our paradigm, dividend growth is mean reverting, expected dividend growth is stochastic and highly persistent, the representative agent is endowed with stochastic differential utility of Duffie and Epstein (1992), and leverage, which proxies for credit risk, is modeled based on the Abel's (1999) formulation. Using reasonable risk aversion levels we produce the observational momentum effects. In particular, momentum profitability is especially high in the interaction between high levered and risky cash flow firms. It rapidly deteriorates and ultimately disappears as leverage or cash flow risk diminishes

Hedge Funds, Managerial Skill, and Macroeconomic Variables

BNP Paribas Hedge Fund Centre at the Singapore Management Universit

Investing in Hedge Funds when Returns are Predictable

This paper evaluates hedge fund performance through portfolio strategies that incorporate predictability in managerial skills, fund risk loadings, and benchmark returns. Incorporating predictability substantially improves performance for the entire universe of hedge funds as well as various subsets based on investment styles. Such outperformance is strongest during market downturns when the marginal utility of consumption is relatively high. Moreover, the major source of investment profitability is predictability in managerial skills. In particular, long-only strategies that incorporate predictable skills outperform their Fung and Hsieh (2004) benchmarks by over 15 percent per year. The economic value of predictability obtains for various rebalancing horizons and is robust to style adjustments as well as adjustments for backfill bias, incubation bias, illiquidity-induced serial correlation, fees, closed funds and alterative benchmark models

Stock -return predictability and model uncertainty

We investigate the implications of uncertainty about the return-forecasting model for the investment opportunity set. Asset allocations are computed through various approaches that differ in their treatment of model uncertainty. The optimal portfolio choices can differ to economically significant degrees, especially for short-horizon high risk-tolerance investors. We decompose the variance of predicted stock returns into several components, including model uncertainty and parameter uncertainty. The model-uncertainty component can be significantly higher than the parameter-uncertainty component, especially when predictive variables, such as dividend yield and book-to-market, are at their recently observed levels, and there is substantial prior uncertainty about whether returns are predictable

Asset Pricing Models and Financial Market Anomalies

This article develops a framework that applies to single securities to test whether asset pricing models can explain the size, value, and momentum anomalies. Stock level beta is allowed to vary with firm-level size and book-to-market as well as with macroeconomic variables. With constant beta, none of the models examined capture any of the market anomalies. When beta is allowed to vary, the size and value effects are often explained, but the explanatory power of past return remains robust. The past return effect is captured by model mispricing that varies with macroeconomic variables. Copyright 2006, Oxford University Press.