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Synchronising a database of stock specific news with 5 years worth of orderbook data on 300 stocks, we show that abnormal price movements following newsreleases (exogenous) exhibit markedly different dynamical features from thosearising spontaneously (endogenous). On average, large volatility fluctuationsinduced by exogenous events occur abruptly and are followed by a decayingpower-law relaxation, while endogenous price jumps are characterized byprogressively accelerating growth of volatility, also followed by a power-lawrelaxation, but slower than for exogenous jumps. Remarkably, our results arereminiscent of what is observed in different contexts, namely Amazon book salesand YouTube views. Finally, we show that fitting power-laws to {\it individual}volatility profiles allows one to classify large events into endogenous andexogenous dynamical classes, without relying on the news feed.

Exogenous and Endogenous Price Jumps Belong to Different Dynamical Classes