A Bayesian method clusters time series by similarity in the timing of their most recent volatility change-points via a metric on posterior distributions, demonstrated on S&P 500 returns.
Clustering financial time series: how long is enough? In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pages 2583--2589
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Dynamic time series clustering via volatility change-points
A Bayesian method clusters time series by similarity in the timing of their most recent volatility change-points via a metric on posterior distributions, demonstrated on S&P 500 returns.