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机器学习能否修正期权定价模型？AI 解读

We introduce a novel two-step approach to predict implied volatility surfaces. Given any fitted parametric option pricing model, we train a feedforward neural network on the model-implied pricing errors to correct for mispricing and boost performance. Using a large dataset of S&P 500 options, we test our nonparametric correction on several parametric models ranging from ad-hoc Black–Scholes to structural stochastic volatility models and demonstrate the boosted performance…

人口特征与社交距离指标在美国COVID-19病例深度预测中的作用AI 解读

With the severity of the COVID-19 outbreak, we characterize the nature of the growth trajectories of counties in the United States using a novel combination of spectral clustering and the correlation matrix. As the United States and the rest of the world are still suffering from the effects of the virus, the importance of assigning growth membership to counties and understanding the determinants of the growth is increasingly evident. For the two communities (faster versus…