Early Warning Signs of Financial Market Turmoils

摘要

Volatility clustering and fat tails are prominently observed in financial markets. Here,we analyze the underlying mechanisms of three agent-based models explaining these stylized facts interms of market instabilities and compare them on empirical grounds. To this end, we first develop ageneral framework for detecting tail events in stock markets. In particular, we introduce Hawkesprocesses to automatically identify and date onsets of market turmoils which result in increasedvolatility. Second, we introduce three different indicators to predict those onsets. Each of the threeindicators is derived from and tailored to one of the models, namely quantifying information content,critical slowing down or market risk perception. Finally, we apply our indicators to simulated andreal market data. We find that all indicators reliably predict market events on simulated data andclearly distinguish the different models. In contrast, a systematic comparison on the stocks of theForbes 500 companies shows a markedly lower performance. Overall, predicting the onset of marketturmoils appears difficult, yet, over very short time horizons high or rising volatility exhibits somepredictive power.