Morgan Chase, CitiGroup, and AIG, from Januto December 31, 2009. The performance of the proposed VG NGARCH model is compared with that of the GARJI model using daily stock prices of five financial companies contained in the S&P 500, namely, Bank of America, Wells Fargo, J.P. Being an extension of the variance-gamma model developed by Madan, Carr, and Chang (1998), the proposed VG NGARCH model imposes an autoregressive structure on the conditional shape parameters, which describes the arrival rates for news with different degrees of impact on price movements, and provides an ex ante probability for the occurrences of large price movements. This study proposes and calibrates a more informative and parsimonious model, the VG NGARCH model. The resulting model specifically accounts for the volatility clustering and leverage effect, however, it is overparameterized and provides only an ex post filter for the probability of large price movements occurring. Chan and Maheu (2002) developed a GARCH-jump mixture model, namely, the GARCH-jump with autoregressive conditional jump intensity (GARJI) model, in which two conditional independent processes, i.e., a diffusion and a compounded Poisson process, are used to describe stock price movements caused by normal and extreme news events, respectively.
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