Option Pricing with Time-Varying Volatility Risk Aversion
提出一个具有时变波动率风险厌恶的定价核，结合Heston-Nandi GARCH模型得到易处理的期权定价模型，方差风险比率是关键变量，实证表明能显著降低S&P 500指数、VIX和期权价格的定价误差。
Abstract We introduce a pricing kernel with time-varying volatility risk aversion to explain the observed time variations in the shape of the pricing kernel. When combined with the Heston-Nandi GARCH model, this framework yields a tractable option pricing model in which the variance risk ratio (VRR) emerges as a key variable. We show that the VRR is closely linked to economic fundamentals, as well as sentiment and uncertainty measures. A novel approximation method provides analytical option pricing formulas, and we demonstrate substantial reductions in pricing errors through an empirical application to the S&P 500 index, the CBOE VIX, and option prices.