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 a 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 then use various attributes collectively to assess the likelihood of a developing bubble and identify 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.
 

Key highlights
Imagine that two people read aloud the same passage from a book. One speaks fast but takes long pauses between sentences. The other speaks slowly but races through exciting parts. We can all recognize that they are telling the same story.

Eventually computers learned this skill, often using a technique called dynamic time warping. Finding the similarities between fast and slow is not only useful for speaking or music – it helps with understanding bubbles in financial markets, too.