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 ...

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 ...

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

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those ...

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 estimates a vector autoregression (VAR) ...

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 ...

We investigate the hedging effectiveness of energy derivatives traded at the European Energy Exchange (EEX), which can be used for mitigating the risk exposure of gas- and coal-fired power plants in ...