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In this context, unconditional variance refers to the stationary variance level predicted by your GARCH model. This quantity need not coincide with the sample variance of the data on which the latter model has been calibrated. That being said, in an effort to reduce the complexity of the GARCH parameters' estimation process (nasty non-linear optimisation ...


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The reason is earnings and other idiosyncratic corporate actions like takeovers, major product releases, etc. There are three terms in garch(1,1), the constant, term proportional to previous day's volatility, and a term proportional to "stock noise". Earnings jump is much larger than previous "regular" volatility, and also much larger than "regular" noise. ...



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