Risk return analysis
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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