Chapter 5: Synthetic Financial Data
Stylized Facts of Financial Time Series for Simulation and Validation foundational
A synthetic market path is only useful if it reproduces the empirical pathologies that make financial returns hard to model in the first place.
A synthetic market path is only useful if it reproduces the empirical pathologies that make financial returns hard to model in the first place.
Register to Read
Sign up for a free account to access all 112 primer topics.
Create Free AccountAlready have an account? Sign in
References
Generalized autoregressive conditional heteroskedasticity
Tim Bollerslev
(1986)
— Journal of Econometrics
Universal features of price formation in financial markets: perspectives from deep learning
Justin Sirignano, Rama Cont
(2019)
— Quantitative Finance
Volatility Clustering in Financial Markets: Empirical Facts and Agent-Based Models
Rama Cont, Gilles Teyssière, Alan P. Kirman
(2007)
— Springer
Tail-GAN: Learning to Simulate Tail Risk Scenarios
Rama Cont, Mihai Cucuringu, Renyuan Xu, Chao Zhang
(2025)