3 papers
q-fin.CP2026
Calibrating the Heston model with deep differential networks
Giovanni Amici, Marco Morandotti, Chen Zhang
We propose a gradient-based deep learning framework to calibrate the Heston option pricing model (Heston, 1993). Our neural network, henceforth deep differential network (DDN), lea…
math.ST2025
Optimal Estimation for General Gaussian Processes
Tetsuya Takabatake, Jun Yu, Chen Zhang
This paper proposes a novel exact maximum likelihood (ML) estimation method for general Gaussian processes, where all parameters are estimated jointly. The exact ML estimator (MLE)…
q-fin.ST2025
Modeling and Forecasting Realized Volatility with Multivariate Fractional Brownian Motion
Markus Bibinger, Jun Yu, Chen Zhang
A multivariate fractional Brownian motion (mfBm) with component-wise Hurst exponents is used to model and forecast realized volatility (RV). We investigate the interplay between co…