Randomized Signature Methods in Optimal Portfolio Selection

no code implementations • 27 Dec 2023 • Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou

We present convincing empirical results on the application of Randomized Signature Methods for non-linear, non-parametric drift estimation for a multi-variate financial market.

Portfolio Optimization

Applications of Signature Methods to Market Anomaly Detection

no code implementations • 7 Jan 2022 • Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou

In this case, we are able to identify pump and dump attempts organized on social networks with F1 scores up to 88% by means of our unsupervised learning algorithm, thus achieving results that are close to the state-of-the-art in the field based on supervised learning.

Anomaly Detection Time Series +1