What’s a good prior distribution for degrees of freedom in a t distribution?

I want to use a t distribution to model short interval asset returns in a bayesian model. I’d like to estimate both the degrees of freedom (along with other parameters in my model) for the distribution. I know that asset returns are quite non-normal, but I don’t know too much beyond that.

What is an appropriate, mildly informative prior distribution for the degrees of freedom in such a model?


On page 372 of ARM, Gelman and Hill mention using a uniform distribution on the inverse of DF between 1/DF = .5 and 1/DF = 0.

Specifically, in BUGS, they use:

nu.y <- 1/nu.inv.y 
nu.inv.y ~ dunif(0,.5)

Source : Link , Question Author : John Salvatier , Answer Author : John Salvatier

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