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How do GARCH processes work? - Answers

GARCH processes are used to model the conditional volatility of financial returns in discrete time. There are many many different types of GARCH, the most popular and simplest being the GARCH(1,1), where returns have mean mu and conditional variance vt (t indexes time): returnt = mu + sqrt(vt)et where et is a standardized innovation.Conditional variance follows a first order autoregressive process: vt= a + b* vt-1 + c* vt-1*et-1^2



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How do GARCH processes work? - Answers

https://math.answers.com/math-and-arithmetic/How_do_GARCH_processes_work

GARCH processes are used to model the conditional volatility of financial returns in discrete time. There are many many different types of GARCH, the most popular and simplest being the GARCH(1,1), where returns have mean mu and conditional variance vt (t indexes time): returnt = mu + sqrt(vt)et where et is a standardized innovation.Conditional variance follows a first order autoregressive process: vt= a + b* vt-1 + c* vt-1*et-1^2



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https://math.answers.com/math-and-arithmetic/How_do_GARCH_processes_work

How do GARCH processes work? - Answers

GARCH processes are used to model the conditional volatility of financial returns in discrete time. There are many many different types of GARCH, the most popular and simplest being the GARCH(1,1), where returns have mean mu and conditional variance vt (t indexes time): returnt = mu + sqrt(vt)et where et is a standardized innovation.Conditional variance follows a first order autoregressive process: vt= a + b* vt-1 + c* vt-1*et-1^2

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      GARCH processes are used to model the conditional volatility of financial returns in discrete time. There are many many different types of GARCH, the most popular and simplest being the GARCH(1,1), where returns have mean mu and conditional variance vt (t indexes time): returnt = mu + sqrt(vt)et where et is a standardized innovation.Conditional variance follows a first order autoregressive process: vt= a + b* vt-1 + c* vt-1*et-1^2

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