论文标题
二次粗糙的赫斯顿模型和联合S＆P 500/VIX微笑校准问题
The quadratic rough Heston model and the joint S&P 500/VIX smile calibration problem
论文作者
论文摘要
众所周知，同时拟合SPX和VIX微笑是波动性建模中最具挑战性的问题之一。由于朱利安·盖恩（Julien Guyon）引起的长期猜想是，不可能用具有连续样品路径的模型共同校准这两个量。我们将二次粗糙的赫斯顿模型作为此猜想的反例。关键的想法是粗糙波动率与价格回馈（Zumbach）效果的结合。
Fitting simultaneously SPX and VIX smiles is known to be one of the most challenging problems in volatility modeling. A long-standing conjecture due to Julien Guyon is that it may not be possible to calibrate jointly these two quantities with a model with continuous sample-paths. We present the quadratic rough Heston model as a counterexample to this conjecture. The key idea is the combination of rough volatility together with a price-feedback (Zumbach) effect.
