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2d
asked Approximation of different volatilities
2d
comment multiperiod optimization using R
@BobJansen I added just an example I found in the web. hope my question is now clearer formulated
2d
revised multiperiod optimization using R
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2d
comment multiperiod optimization using R
thanks for your answer. I will check Model Predictive Control!
2d
awarded  Curious
Aug
19
revised multiperiod optimization using R
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Aug
19
asked multiperiod optimization using R
Jul
24
accepted reference question about portfolio optimization
Jul
23
comment reference question about portfolio optimization
Thank you so much for your answer. I will have a look at the books. It seems you have a quite good overview over the topic. Are there any paper which you would recommend as well?
Jul
23
comment reference question about portfolio optimization
@Taran thanks for your comment. I did not say I want use it. I'm just interested in. If there are more sophisticated models, I would also be interested in a reference. I will update the dynamic part this evening.
Jul
22
asked reference question about portfolio optimization
May
17
revised How to derive equivalent martingale measure using Ito's Lemma
deleted 1 character in body
May
17
answered How to derive equivalent martingale measure using Ito's Lemma
May
17
awarded  Enthusiast
May
7
comment Calculating the VaR from a GARCH(1,1) with Student-t innovations
Maybe this could help: quant.stackexchange.com/questions/11019/… I think predict returns the estimated $\sigma$. Note: GARCH models the conditional variance but has zero conditional mean! Try to use the sample mean and the meanForecast as volatility. Maybe then you get the same result. However, I'm not sure :)
May
2
awarded  Critic
Apr
24
comment GARCH model and prediction
I was able to figure it out. the command m2@sigma.t gives the values up to know. Then I can use the explicit formula and estimators to calculate $\hat{\sigma_{t+1}}$. Again many thanks
Apr
24
accepted GARCH model and prediction
Apr
24
comment GARCH model and prediction
Thanks for your patience, help and editing you answer I will accept your answer. But just one last question: You write: "It is also possible to forecast future variance, $\sigma^2_{t+k}$,as shown, using GARCH formula above." How do I get in R the past values of $\sigma^2$ (the fitted ones)?
Apr
24
comment GARCH model and prediction
Of course, what I would do is: start with ARMA process to model a time series and see which model you prefer, i.e. determine $p$ and $q$. Then check the squared residuals. If appropriate model these with GARCH, i.e. $r_t=\mu_t+\sigma_tZ_t$. Otherwise you can just use the ARMA model. I know that paper and also the particular form of an estimte of $\sigma_{t+1}$ and $\mu_{t+1}$. I just wanted to know if there is a built in function in R (like predict).