Time Varying Sensitivities on a GRID architecture

Mattia Ciprian and Stefano d'Addona
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Mattia Ciprian: mciprian@gmail.com

Finance from EconWPA

Abstract: We estimate time varying risk sensitivities on a wide range of stocks' portfolios of the US market. We empirically test, on a 1926-2004 Monthly CRSP database, a classic one factor model augmented with a time varying specification of betas. Using a Kalman filter based on a genetic algorithm, we show that the model is able to explain a large part of the variability of stock returns. Furthermore we run a Risk Management application on a GRID computing architecture. By estimating a parametric Value at Risk, we show how GRID computing offers an opportunity to enhance the solution of computational demanding problems with decentralized data retrieval.

JEL-codes: G (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp and nep-rmg
Date: 2005-11-16
Note: Type of Document - pdf
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