GitHub

This repo describes python code and input data files for "Forecasting stock return distributions around the globe with quantile neural networks".

torch 2.2.2 PyTorch framework for neural networks. The documented GPU setup targets the official CUDA 12.1 wheel. FF3.CSV Ken French Data Library Full file included Fama-French 3-factor returns. Only ...
IEEE

Evaluating Cryptocurrency Market Risk on the Blockchain: An Empirical Study Using the ARMA-GARCH-VaR Model

Abstract: Cryptocurrency, a novel digital asset within the blockchain technology ecosystem, has recently garnered significant attention in the investment world. Despite its growing popularity, the ...
GitHub

Psaurav-01/Time_Series-

An interactive web dashboard for univariate GARCH(1,1) and multivariate DCC-GARCH(1,1) volatility modelling across user-selectable asset universes (11 S&P 500 sectors, stock/bond, NASDAQ vs SPX, ...
IEEE

Gaussian Process-Mixture Conditional Heteroscedasticity

Abstract: Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial ...