Abstract
The two large scale crises that hit the world economy in the last century, i.e. the Great Depression and the Great Recession, have similar outbreak and recovery patterns with respect to several macroeconomic variables. In particular, the largest depressions are likely to be accompanied by stock-market crashes. This study investigates the behavior of the U.S. stock market before, during and after deep downturns, focusing particularly on the tails of the return distribution. We develop two automatic procedures to identify multiple change-points in the tail of financial time series as well as in the co-crash and co-boom probabilities of different markets. We then apply our methodology to twelve time series representative of the sectors of the U.S. economy. We find that regime shifts in the lower tail of the distribution tend to co-occur before deep downturns. Our results contribute to a better understanding of the origin and systemic nature of large scale events to make policy interventions more timely and effective.
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