统计与数据科学系系列学术报告之四百二十七期

时间：2024年5月7日（周二）16:00-17:00

地点：史带楼502室

主持人：复旦大学管理学院统计与数据科学系黎德元教授

报告人：Prof. Ying Chen National University of Singapore

题目：Neural Tangent Kernel in Implied Volatility Forecasting: A Nonlinear Functional Autoregression Approach

摘要：Implied volatility (IV) remains a pivotal yet intricate component of financial markets, posing continuous challenges for accurate forecasting. We present a Nonlinear Functional Autoregression framework tailored to the series of implied volatility surfaces-a dynamic domain influenced by moneyness and maturity. This approach, designed for European put and call options, adeptly navigates the nonlinear and asymmetric temporal and spatial dependencies intrinsic to IV. Central to our approach is the functional Neural Tangent Kernel (fNTK) estimator. Grounded in the Neural Tangent Kernel parameterization, this estimator presents a modern statistical solution, parsing the intertwined dependencies found within the projections on the covariance operator of the IV surfaces’ time series. A methodological contribution lies in establishing the nexus between fNTK and kernel regression, emphasizing fNTK’s place in contemporary nonparametric statistical modeling. Transitioning from methodology to empirical evidence, we showcase the framework’s real-world utility via an analysis of the S&P 500 index spanning January 2009 to December 2021. The fNTK not only stands out in forecasting accuracy, achieving an average improvement of 4.54% to 39.44% in RMSE forecast accuracy for 5 to 20-day-ahead forecasts but also paves the way for practical trading strategies. When underpinned by our model, straddle trading yields a remarkable Sharpe ratio between 3.72 and 5.41, culminating in a staggering 107.79% to 528.36% relative enhancement in trading results. This convergence of methodological rigor and empirical results offers both a statistical advancement and a beacon for practitioners in the options market.

个人简介：Dr. Ying Chen is a financial statistician and data scientist, focusing on non-stationary, high-frequency, and large dimensional complex data forecasting. She also works on quantitative fintech, quantitative finance, and quantum computing and algorithms. Dr. Chen is an Associate Professor in the Department of Mathematics, Interim Director of Centre for Quantitative Finance, PI at the Asian Institute of Digital Finance, and a Joint Appointee in the Risk Management Institute at the National University of Singapore. Dr. Chen is a Council Member of the International Statistical Institute (ISI) for the period 2023–2027, Scientific Secretary and Executive Committee member of the International Association for Statistical Computing (IASC), and chairperson-elect of the Asian Regional Section (ARS) of IASC.