Teaching

‘Infinite-State Markov-switching for Dynamic Volatility’

(last version : here — Complementary file : here — CORE Discussion paper : here)

Dufays A., Journal of Financial Econometrics, 2016, 14 (2): 418-460

Generalized auto-regressive conditional heteroskedastic model with changing parameters is specified using the sticky infinite hidden Markov-chain framework. Estimation by Bayesian inference determines the adequate number of regimes as well as the optimal specification (Markov-switching or change-point). The new provided algorithms are studied in terms of mixing properties and computational time. Applications highlight the flexibility of the model and compare it to existing parametric alternatives.