From GARCH to Neural Network for Volatility Forecast

Volatility, as a measure of uncertainty, plays a crucial role in numerous financial activities such as risk management. The Econometrics and Machine Learning communities have developed two distinct approaches for financial volatility forecasting: the stochastic approach and the neural network (NN) approach. Despite their individual strengths, these methodologies have conventionally evolved in separate research trajectories with little interaction between them. This study endeavors to bridge this gap by establishing an equivalence relationship between models of the GARCH family and their …

communities cs.lg econometrics financial forecast forecasting garch machine machine learning management network neural network q-fin.st risk role stochastic uncertainty