Numerical Comparison of Quasi-Maximum Likelihood and the Simulated Method of Moments Estimation for Stochastic Volatility Model

Student: Anton Aksenov

Educational Programme: Economics (Bachelor)

Year of Graduation: 2024

This work continues the studies of Borzykh (2013), which compared the effectiveness of two methods for estimating the parameters of a stochastic volatility (SV) model: the maximum quasi-likelihood (QML) method and the simulated method of moments (SMM). To our knowledge, It was the first time these methods were compared in the literature. In the work (Borzykh, 2013), a general conclusion was made that SMM provides more effective estimates than QML. In this study, we show that this conclusion is not always true. Depending on the length of the time series and the true values of the model parameters, the advantage of SMM over QML may be reversed. We also modified the SMM method used by Borzykh (2013) to improve its effectiveness and stability. QML and SMM techniques were also applied to the Russian stocks included in the <<IMOEX >> index. To our knowledge, the SV model has not previously been applied to Russian data.

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