This paper conducts a horse-race of different liquidity proxies using dynamic asset allocation strategies to evaluate the short-horizon predictive ability of liquidity on monthly stock returns. We assess the economic value of the out-of-sample power of empirical models based on different liquidity measures and find three key results: liquidity timing leads to tangible economic gains; a risk-averse investor will pay a high performance fee to switch from a dynamic portfolio strategy based on various liquidity measures to one that conditions on the Zeros measure (Lesmond et al., 1999); the Zeros measure outperforms other liquidity measures because of its robustness in extreme market conditions. These findings are stable over time and robust to controlling for existing market return predictors or considering risk-adjusted returns. (C) 2013 Elsevier B.V. All rights reserved.
机构:
Louisiana State Univ, Dept Finance, EJ Ourso Coll Business Adm, Baton Rouge, LA 70803 USALouisiana State Univ, Dept Finance, EJ Ourso Coll Business Adm, Baton Rouge, LA 70803 USA
Lin, Ji-Chai
Wu, YiLin
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机构:
Natl Taiwan Univ, Dept Econ, Coll Social Sci, Taipei 10055, TaiwanLouisiana State Univ, Dept Finance, EJ Ourso Coll Business Adm, Baton Rouge, LA 70803 USA