Title:	High Frequency Financial Econometrics - Volatilities, Correlations and Portfolio Analysis
DNr:	NAISS 2024/22-1588
Project Type:	NAISS Small Compute
Principal Investigator:	Igor Ferreira Batista Martins <igor.ferreira-batista-martins@oru.se>
Affiliation:	Örebro universitet
Duration:	2024-12-02 – 2026-01-01
Classification:	50201
Keywords:

Abstract

This project develops and applies novel high frequency financial econometrics methods focusing on the integration of exogenous variables into volatility and correlation structures. The project incorporates factors such as scheduled monetary policy meetings into multivariate stochastic volatility models. Unlike traditional approaches, which face challenges in maintaining the positive definiteness of the covariance matrix, the proposed method employs a novel eigenvector-based decomposition that ensures this condition is preserved. By potentially improving the modeling of volatility and correlations, this framework may offer actionable insights with potential to enhance financial decision-making.