A GARCH model with two volatility components and two driving factors
提出一种包含两个不确定性来源的新型GARCH模型，能更好捕捉金融资产波动的多成分动态，并给出准封闭形式的特征函数用于期权定价，实证表明在预测收益和期权价格上优于单因子模型。
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. The code for estimating the model, as well as for computing option prices, is made accessible in MATLAB language. 1