Wasserstein methods for measuring market memory, monitoring stress, and examining distributional states.
Distributional-regime methods often summarize market geometry with a small set of reference distributions. In the Distributional Regime Persistence (DRP) framework, the maintained representation has been a calm/stress pair o…
Volatility persistence is commonly summarized by the persistence parameter of a conditional variance recursion or by the autocorrelation of realized volatility. Neither statistic directly answers whether an empirical return …
Volatility persistence is usually represented by a scalar conditional variance, even though return distributions can remain abnormal through dispersion, center shifts, shape distortions, or continued movement. This paper dev…
The results identify a conditional cross-market portability pattern for an online Wasserstein stress coordinate. Eight equity indices are evaluated strictly out of sample from January 2007 through June 2026 under a design fr…
The results show that an online Wasserstein stress coordinate contributes to one-step tail forecasting after current volatility scale is filtered. Daily returns for the S&P 500, FTSE 100, Nikkei 225, and Hang Seng from 2000 …
Reversing a return series leaves its empirical distribution unchanged. Its mean, variance, skewness, kurtosis, quantiles, and Wasserstein distance from the original sample are therefore identical. Yet the risk process need n…
We develop a real-time framework for monitoring market stress through the geometry of rolling return distributions. A Wasserstein score locates each current distribution relative to low- and high-stress prototypes learned fr…
We define distributional regime persistence as the duration for which a rolling empirical return distribution remains geometrically aligned with a high-volatility prototype. Building on Wasserstein market-regime clustering, …