A GARCH model with two volatility components and two driving factors

TL;DR

This paper proposes a new GARCH model with dual volatility components and factors, offering improved financial asset volatility modeling, option pricing, and empirical performance over traditional single-factor models.

Contribution

It introduces a novel two-factor GARCH model with semi-analytical option pricing formulas and provides theoretical analysis of its stability and diffusion limits.

Findings

Model outperforms single-factor models in return prediction

Provides semi-analytical formulas for option pricing

Establishes conditions for stationarity and ergodicity

Abstract

We introduce a novel GARCH model that integrates two sources of uncertainty to better capture the rich, multi-component dynamics often observed in the volatility of financial assets. This model provides a quasi closed-form representation of the characteristic function for future log-returns, from which semi-analytical formulas for option pricing can be derived. A theoretical analysis is conducted to establish sufficient conditions for strict stationarity and geometric ergodicity, while also obtaining the continuous-time diffusion limit of the model. Empirical evaluations, conducted both in-sample and out-of-sample using S\&P500 time series data, show that our model outperforms widely used single-factor models in predicting returns and option prices.