Recent research has been able to key in on factors that can help give us insights into the life cycle of a bubble. We rely on these factors, or variations of them, to better characterize sector-level bubbles. We also build a composite model of factors to try to predict when these bubbles occur and when they burst. We find that by using the framework described in this paper, it is possible to better time extreme movements among sectors, resulting in reductions in the size of maximum drawdowns, therefore increasing returns and lowering risk.
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