Cybersecurity risks and stock liquidity
Qin Zhang & Jin Boon Wong
Abstract
Purpose This paper investigates the impact of ex-ante cybersecurity risks on stock market liquidity at the firm level. Design/methodology/approach Using a US sample of 10,719 firm-year observations from 2007 to 2018, we employ fixed effects regressions, an innovative ex-ante cybersecurity risks measure and control for various market microstructure and firm-specific characteristics to examine the research question. To address endogeneity concerns, a two-stage least squares regression analysis with instrument variables and a propensity-matched sample is utilized to validate the findings. Findings Our results show that ex-ante cybersecurity risks reduce stock liquidity in the form of higher bid-ask spreads and lower trading turnover. The findings are economically significant and accentuate the importance of cybersecurity risks to stakeholders, as a 1-standard deviation rise in cyber risks can increase bid-ask spreads by 15.55–31.20% and reduce trading turnover by 2.97%. Originality/value We provide empirical evidence on the important differences between the instrument choice of ex-ante versus ex-post cybersecurity risks for market microstructure studies. Prior research suggests ex-post cybersecurity breaches lead to lower bid-ask spreads and increased trading volumes. These findings are counterintuitive. Our study contributes a missing piece to this puzzle by showing that increases in ex-ante cybersecurity risks lead to wider bid-ask spreads and lower trading turnover, possibly due to heightened information asymmetry. Furthermore, we show that during periods of elevated market uncertainty, these cyber-risk effects may be “overlooked” as market participants may be preoccupied with greater concerns at the macroeconomic level.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
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