Stock price jumps: news and volume play a minor role
By Armand Joulin, Augustin Lefèvre, D. Grunberg, Jean-Philippe Bouchaud. 2008
160 citations recorded by the source corpus.
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.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/6feefc80212a214aac3ac13e946081b2cf7d003b
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Citations in the corpus
- Patterns in high-frequency FX data: discovery of 12 empirical scaling laws (2008, unknown): “It is well-known that the statistical properties of a GRW are different from the ones observed in empirical data; Mandelbrot and Hudson [2004]. However, it is striking to observe how close this simple model can be to the average properties of the market data.”
- Predicting abnormal returns from news using text classification (2008, background): “Joulin et al. (2008) analysed the volatility of returns before and after news releases, also from Dow”
- Universal scaling and nonlinearity of aggregate price impact in financial markets. (2017, unknown): “[7] Armand Joulin, Augustin Lefevre, Daniel Grunberg, and Jean-Philippe Bouchaud.”
- How Markets Slowly Digest Changes in Supply and Demand (2008, unknown): “For example, if we define a jump as a one minute return exceeding three standard deviations, there are the order of ten such jumps per day, reflecting the very heavy tailed distribution of high frequency returns (Joulin et al. [2008]).”
- How Twitter is Changing the Nature of Financial News Discovery (2016, background): “Determining the financial value of a company and evaluating it as an investment opportunity, estimating fair value of assets such as commodities or illiquid fixed income instruments, and analyzing long term potential of different sectors of the economy are all information intensive tasks.”