Search Results for author:
Found 3 papers, 2 papers with code
Non-parametric online market regime detection and regime clustering for multidimensional and path-dependent data structures
In this work we present a non-parametric online market regime detection method for multidimensional data structures using a path-wise two-sample test derived from a maximum mean discrepancy-based similarity metric on path space that uses rough path signatures as a feature map.
Non-adversarial training of Neural SDEs with signature kernel scores
Neural SDEs are continuous-time generative models for sequential data.
Clustering Market Regimes using the Wasserstein Distance
The problem of rapid and automated detection of distinct market regimes is a topic of great interest to financial mathematicians and practitioners alike.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
