Financial Asset Price Volatility Models and Empirical Analysis Based on Stochastic Differential Equations
Abstract
To accurately characterize the price volatility characteristics of financial assets, this paper uses the closing prices of the CSI 300 Index for 1488 trading days from 2018 to 2023 as a sample. Two types of stochastic differential equation models, basic and extended, are constructed. The basic model is centered on geometric Brownian motion and consists solely of the drift coefficient μ and the volatility coefficient σ. The extended model introduces dynamic jumps and stochastic volatility, accounting for both continuous fluctuations and extreme jumps. Using maximum likelihood estimation (MLE) for parameter estimation, data simulations show that the base model has μ=0.062 (annualized return 6.2%, p
Fields of Study & Subjects
Stochastic processes and financial applications
Financial Risk and Volatility Modeling
Financial Markets and Investment Strategies
Publication details
- Journal / source
- Journal of innovation and development
- Volume
- 14
- Issue
- 2
- Pages
- 159–167
- Publication date
- 9 February 2026
- Language
- EN