About this document
Copula Models for Financial Time Series by Vinícius Almeida is a document available to read on EtoBox.
The document presents a study on copula-based models for analyzing serial dependence in univariate financial time series, focusing on both linear and non-linear dependencies. It highlights the advantages of using copulas over traditional ARIMA models, particularly in capturing tail dependence and improving Value-at-Risk estimates. The methodology is illustrated using data from 62 U.S. stocks, demonstrating the effectiveness of copula functions in modeling financial time series dynamics.
- Author
- Vinícius Almeida
- Language
- EN