This paper discusses the effects of temporal aggregation on causality and forecasting in multivariate GARCH processes. It is shown that spurious instantaneous causality in variance will only appear in ...

ABSTRACT: The global financial landscape is increasingly becoming interconnected, with financial markets exhibiting complex interdependencies. This increases the possibility of market risk spreading ...

The chosen stocks are Tesla and Nvidia on the time frames 2011-01-01 to 2023-12-31. The implemented univariate models are GARCH(1,1) and t-GARCH(1,1) and the multivariate model implemented is ...

├── README.md <-- Main README file explaining the project's business case, │ methodology, and findings │ ├── Notebooks <-- Jupyter Notebooks for exploration and presentation │ └── Exploratory <-- ...

Appropriate modeling of time-varying dependencies is very important for quantifying financial risk, such as the risk associated with a portfolio of financial assets. Most of the papers analyzing ...

Abstract: This paper discusses the application of five t-GARCH models to the problem of accurately modeling three univariate but mutually dependent wind speed series taken from three US metering sites ...

We introduce a multivariate generalized autoregressive conditional heteroskedasticity (GARCH) copula model to describe joint dynamics of overnight and daytime returns for multiple assets. The ...

ABSTRACT: The global financial landscape is increasingly becoming interconnected, with financial markets exhibiting complex interdependencies. This increases the possibility of market risk spreading ...

This is a preview. Log in through your library . Abstract Previous research indicates that the price-output correlation is time varying. This paper therefore ...