arXiv Open Access 2026

Fast Times, Slow Times: Timescale Separation in Financial Timeseries Data

Jan Rosenzweig
Lihat Sumber

Abstrak

Financial time series exhibit multiscale behavior, with interaction between multiple processes operating on different timescales. This paper introduces a method for separating these processes using variance and tail stationarity criteria, framed as generalized eigenvalue problems. The approach allows for the identification of slow and fast components in asset returns and prices, with applications to parameter drift, mean reversion, and tail risk management. Empirical examples using currencies, equity ETFs and treasury yields illustrate the practical utility of the method.

Penulis (1)

J

Jan Rosenzweig

Format Sitasi

Rosenzweig, J. (2026). Fast Times, Slow Times: Timescale Separation in Financial Timeseries Data. https://arxiv.org/abs/2601.11201

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2026
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓