By  Mark Kritzman ,  Huili Song ,  David Turkington
We apply a technique called dynamic warp analysis to rescale the unique cadences of 2,638 bubbles into synchronized steps. We then observe the distributions of chosen stock characteristics for each step across all the bubbles. We also observe these stock characteristics during periods when a stock is not experiencing a bubble. We use this information to detect when a bubble is underway and how far it has progressed, and test several trading rules to assess the potential to profit from this information.

This research shows how warping time renders stock price bubbles comparable, revealing common patterns that investors can use to detect new bubbles and time exposure to their rise and fall.

Can history offer a guide to understanding future stock-price bubbles? The answer is yes, but we have to learn how to bend time. Thankfully, a method called dynamic time warping offers the solution. Previous bubbles occur at different paces: some rise fast and others slowly, some crash after weeks while others persist for years. By stretching and shrinking the timeline of thousands of bubble events, we systematically place them side by side and find more commonalities in their attributes' patterns than a calendar view suggests. We use many attributes collectively to assess the likelihood of a developing bubble and estimate its lifecycle stage, from inception to peak to conclusion. A simple trading rule seeking to invest in bubble run-ups and post-crash over reactions, while avoiding the peak, generates compelling performance in out-of-sample backtests.