Volatility modeling with jumps: applications to Russian and American stock markets (in Russian)
It is well known that stock returns exhibit conditional heteroskedasticity, and their distribution displays leptokurtosis. Moreover, modern financial markets are characterized by large discrete changes in asset returns. One of the most popular models describing this behavior is the GARCH-J(ump) model, where the arrival of jumps is governed by a Poisson distribution. In this paper we propose a new specification called GARCH-TJI, where the jump intensity depends on the absolute lagged return and whether it exceeds some threshold. The comparative analysis demonstrates a higher effectiveness of the GARCH-TJI model than of the GARCH-ARJI specification described in the literature.
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