This study employs machine learning models to forecast and comprehend the implied volatility of China ETF50. We develop a hybrid model named LSTM-ML, leveraging historical implied volatility, moneyness, and time-to-maturity as input features. The LSTM component captures dynamic hidden...

This study investigates European option pricing under fractional Brownian motion (fBm) and applies it to realized volatility (RV). The RV measure is selected because it uniquely exhibits simultaneous stationarity and long-range dependency properties in financial time series, as shown in our...

We apply a new numerical method, the singular Fourier-Pade (SFP) method invented by Driscoll and Fornberg (2001, 2011), to price European-type options in Levy and affine processes. The motivation behind this application is to reduce the ineffciency of current Fourier techniques when they are...

Closed-form pricing formulae and option Greeks are obtained for European-type options using an orthogonal polynomial series -- complex Fourier series. We assume that risky assets are driven by exponential Lévy processes and stochastic volatility models. We provide a succinct error analysis to...

While option price data play an essential role in numerous applications in economics, little attention has been devoted to their preprocessing. To offer protection against errors and to ensure that the informational content of the data is meaningful, this paper proposes a simple filtering...