[R-SIG-Finance] Risk return analysis

[sidharth mallik]

also, the methods of estimation should be rigorously checked again.
please see this link : http://mahalanobis.twoday.net/stories/2684143/.
parameter estimation for these models may not be as easy as a simple
GARCH model.

On 6/30/13, Wildi Marc (wlmr) <wlmr at zhaw.ch> wrote:
> This is a classic topic of/for confusion:
>
> -Garch-in-Mean (as you use) is not related to Markowitz: the former
> (Garch-in-Mean) emphasizes longitudinal dynamics whereas Markowitz
> emphasizes cross-sectional `diversity'.
>
> -Typically, the link between return and volatility in the Garch-in-mean is
> negative. This means: high-volatility is associated with draw-downs
> (negative returns): asymmetry of markets.
>
> -In contrast, in a Markowitzian cross-sectional perspective the link between
> vola and return is positive: higher returns offset higher risk.
>
> Do not stumble into this trap...
>
> Marc
>
>
>
>
> ________________________________________
> Von: r-sig-finance-bounces at r-project.org
> [r-sig-finance-bounces at r-project.org]" im Auftrag von "Christofer
> Bogaso [bogaso.christofer at gmail.com]
> Gesendet: Samstag, 29. Juni 2013 20:49
> An: r-sig-finance at r-project.org
> Betreff: [R-SIG-Finance] Risk return analysis
>
> Hello again,
>
> I have estimated a garch model with following specification:
>
> r[t] = mu + k * sigma[t] + epsilon[t]
>
> sigma[t] ~ garch(1,1)
>
> However I see that estimate of k is positive but insignificant.
>
> My question what does it mean? Does it mean that, for that asset people are
> not risk adverse? they do not demand higher return for higher risk?
>
> Or it just some noise?
>
> I am using daily log-return for 10 years.
>
> Thanks for your help.
>
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>
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