论文标题
在LETF期权市场上以型号驱动的统计套利
Model-driven statistical arbitrage on LETF option markets
论文作者
论文摘要
在本文中，我们研究了Leung and Sircar（2015）的货币缩放变换的统计特性。这种转变调整了隐含波动性微笑的货币度坐标，以消除IV微笑之间的差异和未杠杆ETF选项之间的差异。我们构建自举统一的置信带，表明在进行了货币度缩放后，隐含的波动性微笑在统计上是不同的。经验应用表明，LETF市场可能会有一些交易机会。提出了基于动态半参数因子模型的统计套利类型策略。该策略提出了一种统计决策算法，该算法根据模型的比较并观察到LETF隐含波动率表面生成贸易建议。证明它会产生高概率的正回报。对LETF隐含波动过程的广泛计量经济学分析是基于半参数因子模型和统一置信带的研究，包括样本外预测。它为隐含波动率表面的潜在动力学提供了新的见解。我们还将赫斯顿随机波动率纳入了货币度缩放方法中，以更好地拖动模型。
In this paper, we study the statistical properties of the moneyness scaling transformation by Leung and Sircar (2015). This transformation adjusts the moneyness coordinate of the implied volatility smile in an attempt to remove the discrepancy between the IV smiles for levered and unlevered ETF options. We construct bootstrap uniform confidence bands which indicate that the implied volatility smiles are statistically different after moneyness scaling has been performed. An empirical application shows that there are trading opportunities possible on the LETF market. A statistical arbitrage type strategy based on a dynamic semiparametric factor model is presented. This strategy presents a statistical decision algorithm which generates trade recommendations based on comparison of model and observed LETF implied volatility surface. It is shown to generate positive returns with a high probability. Extensive econometric analysis of LETF implied volatility process is performed including out-of-sample forecasting based on a semiparametric factor model and uniform confidence bands' study. It provides new insights into the latent dynamics of the implied volatility surface. We also incorporate Heston stochastic volatility into the moneyness scaling method for better tractability of the model.
