In this repository, DCC-GARCH and Diebold-Yilmaz approach is carried out using the R software. DCC-GARCH model is used to estimate the dynamic correlation between ASEAN countries stock indexes. Diebold-Yilmaz approach is used to estimate the spillover between ASEAN countries stock indexes.
Using publicly available daily factor and a panel of stock returns, estimate the time-varying betas to the selected factor using either DCC-GARCH.
Predict correlations and covariances of returns using open-high-low-close data
Directed-network framework for S&P 500 crisis regimes: A-DCC GARCH, Graphical Lasso, a lead/follower cascade, network-topology metrics, and a composite Network Stress Index across twenty 1985-2024 regimes.
DCC GARCH and CCC GARCH covariance forecasting for SPY TLT minimum variance portfolios
This repository contains a multivariate econometric study that has been applied to the financial risk management of an equally-weighted (EW) portfolio.
Quantitative finance portfolio: portfolio optimization, risk modeling and financial econometrics (DCC-GARCH, VaR, Markowitz, ARMA). Includes full Python code for my master's thesis.
Master's thesis — University of Kragujevac, MSc Artificial Intelligence. Forecasting time-varying intermarket dependencies between cryptocurrencies and conventional assets with machine learning (walk-forward, DCC-GARCH benchmark).
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