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1) You are computing the "actual" VaR, in the sense that you are not forecasting it to see if your VaR model is able to estimate it, but you are just computing the VaR that "has taken place". To obtain a volatility forecast (either in-sample or out-of-sample) you can use the "ugarchforecast" function. 2) I think you are estimating the VaR on the wrong side ...


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I agree with everything dnl said. This time period choice can get very involved. You are explicitly choosing an historical period that you think will be repeated in the future. Unfortunately, history does not repeat exactly. There is an old saying, all models are wrong, but some are useful. There is no right answer for the period. Should you include just a ...


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Speaking about portfolio optimization in general, historical data is required to estimate the variance-covariance matrix that gives you the volatilities of the stock returns and the covariances thereof. The estimation depends on the periodicity of your returns, i.e. whether you are using intraday, daily, weekly, or monthly returns. (For intraday/daily ...



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