The Role of Liquidity in Stock Returns and Option Pricing

How Liquidity Affects Stock Returns and Option Prices

Author

Nam Nguyen
October 04, 2026 • Estimated Reading Time: 4 minutes

Liquidity is an important factor in financial markets, but it is not always the first consideration in asset pricing, trading, or risk management. In this edition, we examine the importance of liquidity from two different perspectives: its predictive relationship with stock returns and its role in option pricing and hedging.

In this issue:

Latest Posts

  • Correlation, Volatility-of-Volatility, and Sector Implied Volatility (10 min)

  • Reflexivity and the Dynamics of Option Markets (10 min)

  • The Effects of ETF Investing on Financial Markets (10 min)

  • Market Regimes and Changing Market Dynamics (10 min)

  • Making Option Pricing Models More Practical (10 min)

How Liquidity of Stock Affects Its Future Expected Return

The liquidity of a stock is of concern to traders who want to execute a large order at reasonable prices without making a big impact on the market. A stock liquidity level is, however, also a factor influencing the stock's expected return. Along this line, Reference [1] examined how a stock’s liquidity volatility affects its future performance.

Findings

  • The authors find that liquidity volatility negatively predicts subsequent stock returns across global equity markets.

  • The relationship is robust across different liquidity measures, including turnover, the Amihud illiquidity ratio, and the percentage of zero-return days.

  • The negative liquidity-volatility premium persists after controlling for other factors, including idiosyncratic return volatility.

  • The results show an asymmetric relationship between liquidity changes and returns: liquidity decreases have a substantially stronger negative impact than the positive impact associated with comparable liquidity increases.

  • This asymmetry implies that stocks with high liquidity volatility are more exposed to large price declines that are not fully offset by price appreciation following liquidity increases.

  • Further analysis indicates that downside liquidity volatility, rather than upside liquidity volatility, drives the negative liquidity-volatility premium.

  • The stronger effect of liquidity decreases is consistent with the collateral-constraint mechanism proposed in previous research.

In short, the article pointed out that a stock’s liquidity is important not only because of the issues associated with order execution but also because it affects the future performance of the stock. The negative volatility premium is a universal phenomenon that occurs in the majority of global equity markets and across different liquidity measures. Practically speaking, when a stock’s liquidity decreases, it will likely decline in the following months.

Reference

[1] Feng, Frank Yulin and Kang, Wenjin and Zhang, Huiping, Liquidity Shocks and the Negative Premium of Liquidity Volatility Around the World, SSRN 3930591

Incorporating Liquidity into Option Pricing

Liquidity is an overlooked research area, yet it plays a crucial role in financial markets. Trading system developers often use the bid-ask spread as a proxy for liquidity, but this approach is less effective in the options market.

Reference [2] proposes a method for integrating liquidity into the option pricing model. Essentially, it introduces market liquidity as a variable that can change randomly and affects stock prices through a discounting factor and market liquidity levels.

The paper begins by incorporating a stochastic liquidity variable into the SDE for stock price under the P measure. Here, the liquidity process is modeled as an Ornstein-Uhlenbeck process. The SDE is then transformed into the Q measure in which European options are analytically evaluated using a closed-form characteristic function.

Findings

  • The authors develop a European option pricing model that jointly incorporates stochastic volatility, economic cycles, and liquidity risk.

  • The model combines Heston stochastic volatility with regime switching to capture economic cycles, while market liquidity follows a mean-reverting stochastic process.

  • Stock prices are adjusted using a liquidity discounting factor to account for the impact of liquidity risk.

  • A regime-switching Esscher transform is used to obtain risk-neutral dynamics and derive a closed-form European option pricing formula.

  • Numerical experiments and sensitivity analysis demonstrate that stochastic volatility, economic cycles, and liquidity risk all have significant effects on option prices.

  • Empirical results show that incorporating stochastic liquidity significantly improves model performance compared with assuming constant liquidity.

  • The stochastic-liquidity component can also improve hedging responses to liquidity shocks and help mitigate risk.

In short, liquidity is integrated as a discount factor, and the study demonstrates its impact on option prices.

Reference

Closing Thoughts

Together, these studies highlight the importance of considering liquidity in both asset pricing and risk management. The first shows that liquidity volatility contains predictive information about future stock returns, with downside liquidity changes playing a particularly important role. The second demonstrates that incorporating stochastic liquidity into option pricing significantly improves model performance and can enhance hedging against liquidity shocks.

Overall, liquidity is not merely a trading friction but an important source of information and risk that should be explicitly incorporated into quantitative models.

Additional Reading

For further discussion on liquidity, refer to the previous issues:

Educational Video

Measuring Liquidity Risk in the Global Financial System

This roundtable examines liquidity risk from both a banking and system-wide financial-stability perspective. One central argument is that liquidity shortages and bank runs may often be symptoms or accelerants of underlying solvency problems rather than their fundamental cause. Historical evidence from banking crises suggests that failing banks frequently exhibited deteriorating fundamentals well before deposit withdrawals accelerated, while solvent institutions experiencing liquidity pressure could often obtain funding through interbank markets. This distinction has important policy implications: providing additional liquidity cannot resolve an underlying solvency problem, which instead requires recapitalization or resolution. The discussion also highlights that retail depositors appear relatively inattentive to bank fundamentals until conditions become sufficiently severe, whereas other financial institutions may be better able to distinguish liquidity problems from solvency problems.

The discussion then broadens from individual banks to liquidity across the financial system. Market and funding liquidity can interact through collateral values, margin calls, forced selling, and reduced dealer intermediation, creating self-reinforcing liquidity spirals. Post-crisis regulations have strengthened individual institutions, but they may also have shifted risks toward non-bank financial institutions, increased dependence on collateralized funding, and constrained market-making capacity during periods of stress. The roundtable therefore emphasizes system-wide liquidity stress testing covering banks, hedge funds, pension funds, insurers, asset managers, and other institutions, while questioning the appropriate balance between private liquidity buffers and central-bank backstops. More broadly, it argues that liquidity regulation cannot be considered independently of capital requirements, market structure, collateral dynamics, and the ability of supervisors to identify losses and force timely recapitalization.

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