This paper discusses the computation of hedging strategies under affine Gaussian GARCH dynamics. The risk‐minimization hedging strategy is derived in closed‐form and related to minimum variance delta hedging. Several numerical experiments are conducted to investigate the accuracy and properties of the proposed hedging formula, as well as the convergence to its continuous‐time counterpart based on the GARCH diffusion limit process. An empirical analysis with S&P 500 option data over 2001–2015 indicates that risk‐minimization hedging with the affine Gaussian GARCH model outperforms benchmark delta hedges. Our study also reveals that the variance‐dependent pricing kernel contributes to improving the hedging performance.

中文翻译：

---

仿射GARCH模型中套期保值策略的计算。

本文讨论了仿射高斯GARCH动力学下的套期保值策略的计算。风险最小化对冲策略以封闭形式导出，与最小方差增量对冲相关。进行了一些数值实验，以研究所提议对冲公式的准确性和性质，以及基于GARCH扩散极限过程对其连续时间对等公式的收敛性。对2001-2015年间S＆P 500期权数据的实证分析表明，使用仿射高斯GARCH模型进行的风险最小化套期交易优于基准三角套期保值。我们的研究还表明，依赖于方差的定价内核有助于提高套期保值绩效。