Estimating Stochastic Volatility Models Through Indirect Inference  

Oleh:

Monfardini, Chiara

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The Econometrics Journal vol. 1 no. 1 (1998), page 113-128.
Fulltext: 113.pdf (167.22KB)

Isi artikel

We propose as a tool for the estimation of stochastic volatility models two indirect inference estimators based on the choice of an autoregressive auxiliary model and an ARMA auxiliary model, respectively. These choices make the auxiliary parameter easy to estimate and at the same time allow the derivation of optimal indirect inference estimators. The results of some Monte Carlo experiments provide evidence that the indirect inference estimators perform well in finite sample, although less efficiently than Bayes and Simulated EM algorithms.

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