Splines for Financial Volatility

Francesco Audrino () and Peter Bühlmann ()

University of St. Gallen Department of Economics working paper series 2007 from Department of Economics, University of St. Gallen

Abstract: We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework for non-Gaussian observations. As the dimension of the B-spline basis is large, i.e. many parameters, we use regularized and sparse model fitting with a boosting algorithm. Our method is computationally attractive and feasible for large dimensions. We demonstrate its strong predictive potential for financial volatility on simulated and real data, also in comparison to other approaches, and we present some supporting asymptotic arguments.

Keywords: Boosting; B-splines; Conditional variance; Financial time series; GARCH model; Volatility (search for similar items in EconPapers)
JEL-codes: C13 C14 C22 C51 C53 C63 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2007-04
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Journal Article: Splines for financial volatility (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:usg:dp2007:2007-11

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