Long-term reversal and value effects: the role of liquidity risk

ABSTRACT

This paper demonstrates that liquidity risk helps explain the return patterns of stocks with high book-to-market ratios and low intangible returns. We document empirical evidence that (1) liquidity shocks, the unexpected variation in liquidity factors that are orthogonal to the firm’s past accounting performance, predict stock returns, (2) stocks with higher book-to-market ratios or lower intangible returns have higher exposure to aggregate capital constraint measures (i.e. these stocks possess higher liquidity risk) and (3) the returns of long-term contrarian strategies based on liquidity shocks, book-to-market ratios and intangible returns are highly correlated and serve as proxies for returns from liquidity provision. Moreover, liquidity-providing returns are stronger in declining markets as well as when the market volatility is high, indicating that liquidity providers are capital-constrained in providing liquidity under such conditions.

KEYWORDS:

• Funding liquidity risk
• liquidity shocks
• long-term reversal and value effects
• capital constraints
• liquidity-providing returns

JEL CLASSIFICATION:

• G11
• G12

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ Returns from short-term reversal strategies. This strategy was first applied by Jegadeesh (1990) and Lehmann (1990), who argue that stocks that perform well over the past few days (weeks) earn higher future returns over the coming days (weeks).

² The original definition proposed by Roll (1984) had the form of $2\cdot \sqrt{-Cov\left(R_{i,t},R_{i,t-1}\right)}$, and was used as a proxy for the effective bid-ask spread. However, this measure is not well defined when the autocovariance is greater than 0. To resolve this issue, Corwin and Schultz (2012) and Saleemi (2020) equate all “outliers” to 0. Alternatively, Lesmond (2005) and Kim and Lee (2014) treat the positive autocovariance as a negative value. However, their approach may be imperfect, since a positive autocovariance contains important information when conducting a cross-sectional analysis and, thus, does not consider the fact that it can distort results. Bao, Pan, and Wang (2011) as well as Guo et al. (2017) include the data sample containing positive autocovariances in their analysis by removing the square root. We apply the approach of the latter and define price reversal as negative autocovariance of returns.

³ In Table A1 of the Appendix, we explore the impact of firm performance (i.e. accounting-based performance, market performance, or intangible performance) on liquidity, and the evidence suggests that stocks with poor performance are more illiquid relative to stocks at the opposite end.

⁴ Gutierrez and Prinsky (2007) demonstrate that institutions chase cross-sectional return winners, which tend to be stocks with low book-to-market ratios. In general, institutional funds that hold stocks with poor performance may face more outflows, and force managers to prematurely liquidate some of their holdings. In addition, institutional investors may avoid adding losing stocks to their portfolios for the sake of window-dressing (Ritter and Chopra 1989; Asness, Liew, and Stevens 1997). In collateral-based model, when stock prices decline, the intermediaries hit margin constraints and are forced to liquidate(Garleanu and Pedersen 2007; Brunnermeier and Pedersen 2009; Hameed, Kang, and Viswanathan 2010).

⁵ The analysis and results are available upon request from the authors.

⁶ The primary dealer Repo positions are calculated based on data downloaded from the Federal Reserve Bank of New York website: https://www.newyorkfed.org/markets/gsds/search#.

⁷ The monthly data on the aggregate ICR are obtained from Zhiguo He’s website: https://voices.uchicago.edu/zhiguohe/data-and-empirical-patterns/intermediary-capital-ratio-and-risk-factor/.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (71873088) and the National Social Science Fund of China (20BJY190).