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Does liquidity drive stock market returns? The role of investor risk aversion

Author

Listed:
  • Qingjing Zhang

    (University of Southampton)

  • Taufiq Choudhry

    (University of Southampton)

  • Jing-Ming Kuo

    (University of Birmingham)

  • Xiaoquan Liu

    (University of Nottingham Business School China, University of Nottingham)

Abstract

In this paper, we explore the relations between liquidity, stock returns, and investor risk aversion as captured by the variance risk premium (VRP). This is motivated by theoretical and empirical evidence in the literature which suggests that investor risk aversion negatively correlates with asset liquidity, and ample empirical evidence documenting liquidity risk premium. We use monthly US data from January 1999 to December 2018 and show that innovations in the VRP Granger-cause stock returns, which in turn drive liquidity. Our findings are consistent with predictions of prior theories and highlight the predictability of the VRP. They also contribute to the on-going debate on the causal relation between stock returns and liquidity. Finally, we explore the channels through which the VRP impacts liquidity and find that the VRP influences market and momentum factors, and that movements in these factors lead to changes in liquidity.

Suggested Citation

  • Qingjing Zhang & Taufiq Choudhry & Jing-Ming Kuo & Xiaoquan Liu, 2021. "Does liquidity drive stock market returns? The role of investor risk aversion," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 929-958, October.
    • Handle: RePEc:kap:rqfnac:v:57:y:2021:i:3:d:10.1007_s11156-021-00966-5
    DOI: 10.1007/s11156-021-00966-5
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    More about this item

    Keywords

    Systematic factors; Toda-Yamamoto Granger non-causality test; Investor risk aversion; Liquidity;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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