RT Report
T1 Evaluating the performance of the skewed distributionsto forecast Value at Risk in the Global Financial Crisis
A1 Abad Romero, Pilar
A1 Benito Muela, Sonia
A1 Sánchez Granero, Miguel Angel
A1 López, Carmen
AB This paper evaluates the performance of several skewed and symmetric distributions in modeling the tail behavior of daily returns and forecasting Value at Risk (VaR). First, we used some goodness of fit tests to analyze which distribution best fits the data. The comparisons in terms of VaR have been carried out examining the accuracy of the VaR estimate and minimizing the loss function from the point of view of the regulator and the firm. The results show that the skewed distributions outperform the normal and Student-t (ST) distribution in fitting portfolio returns. Following a two-stage selection process, whereby we initially ensure that the distributions provide accurate VaR estimates and then, focusing on the firm´s loss function, we can concludethat skewed distributions outperform the normal and ST distribution in forecasting VaR. From the point of view of the regulator, the superiority of the skewed distributions related to ST is not so evident. As the firms are free to choose the VaR model they use to forecast VaR, in practice,skewed distributions will be more frequently used.
YR 2013
FD 2013-12
LK https://hdl.handle.net/20.500.14352/41535
UL https://hdl.handle.net/20.500.14352/41535
LA eng
NO This work has been funded by the Spanish Ministerio de Ciencia y Tecnología (ECO2009-10398/ECON and ECO2011-23959).
NO Spanish Ministerio de Ciencia y Tecnología ( and )
DS Docta Complutense
RD 13 abr 2025