论文标题
夹心伏特拉波动率模型：马尔可夫近似和对冲
Sandwiched Volterra Volatility model: Markovian approximations and hedging
论文作者
论文摘要
我们认为由一般的Hölder连续Volterra型噪声和无界漂移驱动的随机波动动力学。对于这些所谓的SVV模型，我们考虑了二次套期保值策略的明确计算。尽管理论对冲在所有可正式集成主张的非预料衍生物方面都是众所周知的，但这些模型通常是非马尔科夫提供的事实在直接计算有条件期望的核心核心是显式套期保值策略的核心中的挑战。为了克服这一难度，我们提出了模型的马尔可夫近似，该模型源于Volterra噪声中内核的足够近似。我们研究了波动率，价格和最佳均方对冲的近似值。我们提供相应的误差估计。该工作通过数值模拟完成。
We consider stochastic volatility dynamics driven by a general Hölder continuous Volterra-type noise and with unbounded drift. For these so-called SVV-models, we consider the explicit computation of quadratic hedging strategies. While the theoretical hedge is well-known in terms of the non-anticipating derivative for all square integrable claims, the fact that these models are typically non-Markovian provides is a challenge in the direct computation of conditional expectations at the core of the explicit hedging strategy. To overcome this difficulty, we propose a Markovian approximation of the model which stems from an adequate approximation of the kernel in the Volterra noise. We study the approximation of the volatility, of the prices and of the optimal mean-square hedge. We provide the corresponding error estimates. The work is completed with numerical simulations.
