PREDICTING VOLUME-WEIGHTED AVERAGE PRICE BEHAVIOUR USING GARCH MODEL

Abstract

In this competitive era of financial expertise predicting stock behavior has become significant because it facilitates data-driven decisions that help traders design their investment strategy which impacts their portfolios. This research aims to use a statistical model to analyze Volume-weighted average prices and make predictions. By examining data and interrelated financial variables the project aims to provide forecasts that reveal trends and risks involved in investment decisions. Utilizing GARCH model will help the understanding of the future ahead of us which gives insights in decision-making. This study not only contributes to the field of analytics but also has practical applications that contribute to investment strategies, risk management, and policy development. The GARCH model is a statistical framework widely used for analyzing and forecasting volatility in time-series data.