Abstract
Modem statistical methods are introduced for the accurate forecasting of the profit and loss distribution that is associated with a given financial instrument portfolio and a set time horizon. These methods provide a theoretically consistent approach to the evaluation of market risk and can be used in such a way as to improve the bottom line of the firm. Based on backtesting, a new and powerful technique of model assessment is presented. It is further shown how credit risk can also be incorporated in this framework. Finally, by relating the P&L distribution to the common chance and risk paradigm it is demonstrated how the concept extends to portfolio management.
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Kokic, P., Breckling, J., Eberlein, E. (2000). A New Framework for the Evaluation of Market and Credit Risk. In: Bol, G., Nakhaeizadeh, G., Vollmer, KH. (eds) Datamining und Computational Finance. Wirtschaftswissenschaftliche Beiträge, vol 174. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57656-0_5
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DOI: https://doi.org/10.1007/978-3-642-57656-0_5
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1284-8
Online ISBN: 978-3-642-57656-0
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