ARCH Models in Julia

The volatility of a financial asset is an important ingredient in asset allocation, derivative pricing, and Value at Risk calculations, among others. Consequently, there is a large literature on volatility modeling. The most successful class of models is that of (generalized) autoregressive conditional heteroskedasticity, or (G)ARCH models, pioneered by econometrician Robert Engle in his seminal 1982 paper, and for which he received the Nobel Memorial Prize in Economics in 2003. The author is developing a package which implements these models in Julia, which as a language is particularly well suited for this task.

Speaker's bio

I am an assistant professor of econometrics at the University of Amsterdam, but currently on leave to the University of Zurich under an MSCA indiviual fellowship.