I would like to ask "how to do GARCH modelling on stata".
Basically I want to estimate stock market volatility using daily data. I have one variable as return series, $r_t=\ln(\frac{P_t}{P_{t-1}})$.
I need a step by step explanation.
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Sign up to join this communityI would like to ask "how to do GARCH modelling on stata".
Basically I want to estimate stock market volatility using daily data. I have one variable as return series, $r_t=\ln(\frac{P_t}{P_{t-1}})$.
I need a step by step explanation.
I don't use Stata often, but the help()
function is typically very good. Try help(garch)
. It looks like the command is
garch _depvar_ _indepvars_ _options_
Here's the help page on the web.
You need to find the values of the GARCH parameters which fit best your data.
To do so, you usually create a function simulating a GARCH simulation taking, as input the parameters, and you run it through an optimizer to that the sum of the squares of the differences of the simulations points and the sample points are minimal.
Note that it will not give you a number (the volatility, which is not very useful), it will give you a time series of the volatility for each data point.
Finally, beware that this is just a model, it is not the ultimate answer. Try looking at different GARCH versions on the wiki page if you need to.
Note: This is the manual way of doing it. You have packages available in R and MATLAB who handle all that for you, it might exist in Stata.