A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This study examines chaos in FIGARCH processes using various metrics.
We review statistical properties of models generated by the application of a (positive and negative order) fractional derivative operator to a standard random walk and show that the resulting stochastic walks display slowly-decaying autocorrelation functions. The relation between these correlated walks and the well-kno…
Study introduces AMVP and AMRR for dynamic portfolio optimization in volatile markets.
Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia. One advantage of these models is their ability to capture nonlinear dynam…
The MAXFLAT low-pass filter improves factor adjustment for better portfolio performance in China's stock market.
Study finds long-range dependence in financial markets, but deep generative models struggle to replicate it.
Estimates roughness of financial volatility paths using horizontal visibility graphs.