GARCH models are useful to estimate daily volatility in financial return series. When intra-day return data are available realized volatility may be used for the same purpose. We formulate a new model ...

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The issue of finite-sample inference in Generalised Autoregressive Conditional Heteroskedasticity (GARCH)-like models has seldom been explored in the theoretical literature, although its potential ...

There are several approaches to dealing with heteroscedasticity. If the error variance at different times is known, weighted regression is a good method. If, as is ...

This is a preview. Log in through your library . Abstract Empirical research indicates that the volatility of stock return time series has long memory. However, it has been demonstrated that short ...

Volatility modeling is no longer just about pricing derivatives—it's the foundation for modern trading strategies, hedging precision, and portfolio optimization. Whether you're trading gold futures, ...