# 13-156/IV/DSF64 (2013-10-08)

Dennis Karstanje, Erasmus University Rotterdam; Elvira Sojli, Erasmus University Rotterdam; Wing Wah Tham, Erasmus University Rotterdam; Michel van der Wel, Erasmus University Rotterdam
Liquidity, forecasting, expected returns, economic valuation
JEL codes:
G11, G12, G17

This discussion paper resulted in a publication in the 'Journal of Banking and Finance' (2013). Vol. 37, issue 12, pages 5073-5087.

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, Ogden, and Trzcinka, 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.