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.
One-dimensional empirical measures, order statistics and kantorovich transport distances
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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.