The generalized autoregressive conditional heteroskedasticity (GARCH) process is an econometric term used to describe an approach to estimate volatility in financial markets.

Volatility forecasting is perhaps the most important concept in risk management.

This paper develops a closed-form option valuation formula for a spot asset whose variance follows a GARCH (p, q) process that can be correlated with the returns of the spot asset. It provides the ...

We apply vine copulas with generalized autoregressive conditional heteroscedasticity (GARCH) marginals to the problem of capturing asset dependence and tail dynamics for currency and commodity ...

The commonly used square-rootof-time rule, which scales the one-day 99% VaR with a factor √10, is compared with alternative 10-day estimators in the case of random walks, GARCH (1,1) and AR (1)-GARCH ...

We examine the persistence of shocks to conditional variance in the GARCH (1,1) model, and show that whether these shocks "persist" or not depends crucially on the definition of persistence. We also ...