ADVANCING VOLATILITY FORECASTING: A GARCH-BASED APPROACH FOR FINANCIAL MARKET PREDICTIONS

The main reasons for modeling and predicting volatility with GARCH models are the capturing of time-varying volatility in financial time series like returns on stocks, foreign currency prices, and commodity prices, and their prediction. There are periods of high volatility as well as low volatility which are not constant across different time periods in a financial market. Such dynamic behaviour can be quantified using GARCH models by accounting for the fact that large price movements are typically followed by further large movements of either direction, while small movements follow small ones. In this regard, GARCH models are critical in the risk management, option pricing, portfolio optimization, and financial decision-making contexts. They help practitioners and researchers to make better predictions for future market conditions, appraise possible risks, and design strategies to hedge adverse movements in the market more efficiently.