A list of papers tackling the Bayesian estimation of Ito processes (or their discrete time version).

To download the papers referenced here you need to execute the following commands:

git clone https://github.com/RonsenbergVI/MCMC-estimation-of-Stochastic-Differential-Equations-Papers.git
cd MCMC-estimation-of-Stochastic-Differential-Equations-Papers
sh run.sh

• MCMC Methods for Continuous-Time Financial Econometrics, Johannes, M., and Polson, N. (2003). [pdf].

• Jumps in Equity Index Returns Before and During the Recent Financial Crisis: A Bayesian Analysis, Kou, S., Yu, C., & Zhong, H. (2016). [pdf].

• Stochastic Volatility and Jumps: Exponentially Affine Yes or No? An Empirical Analysis of S&P500 Dynamics, Katja Ignatieva Paulo J. M. Rodrigues Norman Seeger (2009) [pdf].

• Consistent non-parametric Bayesian estimation for a time-inhomogeneous Brownian motion Gugushvili, Shota, and Peter Spreij (2014). [pdf].

• Nonparametric Bayesian drift estimation for multidimensional stochastic differential equations, Gugushvili, S. and Spreij, P. (2014). [pdf].

• Bayesian inference for Stable Levy driven Stochastic Differential Equations with high-frequency data, Jasra A, Kamatani K, Masuda H. (2017). [pdf].

• Bayesian Estimation of Time-Changed Default Intensity Models Gordy, M.B. and Szerszen, P., (2015). [pdf].

• Bayesian Estimation and Option Mispricing, Alberto Vargas Mendoza (2011). [pdf].

• Sequential Monte Carlo Methods for Stochastic Volatility Models with Jumps, Raggi, D., and Bordignon, S. (2008). [pdf].

• Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices: Application of a Bivariate Kalman Filter Forbes, C. S., Martin, G. M., and Wright, J. (2003). [pdf].

• A New Bayesian Unit Root Test in Stochastic Volatility Models, Yong LI Jun YU (2010). [pdf].

• Bayesian Analysis of Stochastic Volatility Models with Lévy Jumps: Application to Risk Analysis, Pawel Szerszen (2009). [pdf].

• MCMC Estimation of Multiscale Stochastic Volatility Models, German Molina, Chuan-Hsiang Han, Jean-Pierre Fouque (). [pdf].

• Markov Chain Monte Carlo Calibration of Stochastic Volatility Models, Xin Ge, Chuanshu Ji (2008). [pdf].

• Markov Chain Monte Carlo Estimation of Stochastic Volatility Models with Finite and Infinite Activity Lévy Jumps, Yang H. (2015). [pdf].

• Bayesian Estimation of a Stochastic Volatility ModelUsing Option and Spot Prices: Application of a Bivariate Kalman Filter, Catherine S. Forbes, Gael M. Martin and Jill Wright (2004). [pdf].

• Bayesian Filtering for Jump-Diffusions with Applications to Stochastic Volatility, Andrew Golightly (2007). [pdf].

• Estimating the Parameters of Stochastic Volatility Models using Option Price Data, A. S. Hurn, K. A. Lindsay and A. J. McClelland (). [pdf].

These requirements reflect the testing environment. It is possible that the download script will work with older versions.

• Python (3+)