The paper proposes a model for the dynamics of stock prices that incorporates increased asset co-movements during extreme market downturns in a continuous-time setting. The model is based on the construction of a multivariate diffusion with a pre-specified stationary density with tail dependence. I estimate the model with Markov Chain Monte Carlo using a sequential inference procedure that proves to be well-suited for the problem. The model is able to reproduce stylized features of the dependence structure and the dynamic behaviour of asset returns.
# 12-125/IV/DSF45 (2012-11-21)
- Denitsa Stefanova, VU University Amsterdam
- tail dependence, multivariate diffusion, Markov Chain Monte Carlo
- JEL codes:
- C11, C51, C58