We investigate changepoints in the cross-section of stock returns using an ensemble of dedicated unsupervised learning methods. Our large-scale study reveals a sustained incidence of changepoints in the mean, variance, and distribution. This finding is robust to the choice of the changepoint...

In this paper, we extend the literature on crash prediction models in three main ways. First, we explicitly relate crash prediction measures and asset pricing models. Second, we present a simple, effective statistical significance test for crash prediction models. Finally, we propose a...

We provide a historical perspective focusing on Ziemba's experiences and research on the bond-stock earnings yield differential model (BSEYD) starting from when he first used it in Japan in 1988 through to the present in 2014. The model has called many but not all crashes. Those called have high...

I have used four measures that have had considerable success in predicting stock market declines of ten percent or more and average twenty-five percent. Other declines of 5-15% seem to be hard to predict ex ante, while some can be explained ex post. In this paper, I focus on six of the latter...