GARCH Processes with Non-parametric Innovations for Market Risk Estimation
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- Hernández-Lobato J.M., Hernández-Lobato D., Suárez A. (2007) GARCH Processes with Non-parametric Innovations for Market Risk Estimation. In: de Sá J.M., Alexandre L.A., Duch W., Mandic D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4669. Springer, Berlin, Heidelberg
A procedure to estimate the parameters of GARCH processes with non-parametric innovations is proposed. We also design an improved technique to estimate the density of heavy-tailed distributions with real support from empirical data. The performance of GARCH processes with non-parametric innovations is evaluated in a series of experiments on the daily log-returns of IBM stocks. These experiments demonstrate the capacity of the improved estimator to yield a precise quantification of market risk.
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