Stock price jumps: news and volume play a minor role

Abstract

In order to understand the origin of stock price jumps, we cross-correlate high-frequency time series of stock returns with different news feeds. We find that neither idiosyncratic news nor market wide news can explain the frequency and amplitude of price jumps. We find that the volatility patterns around jumps and around news are quite different: jumps are followed by increased volatility, whereas news tend on average to be followed by lower volatility levels. The shape of the volatility relaxation is also markedly different in the two cases. Finally, we provide direct evidence that large transaction volumes are_not_ responsible for large price jumps. We conjecture that most price jumps are induced by order flow fluctuations close to the point of vanishing liquidity.

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• Noise Dressing of Financial Correlation Matrices
• Scaling of the distribution of price fluctuations of individual companies
• Volatility clustering and scaling for financial time series due to attractor bubbling
• Market reaction to temporary liquidity crises and the permanent market impact

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