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A Dynamical Model for Forecasting Operational Losses

Listed author(s):
  • Marco Bardoscia
  • Roberto Bellotti

A novel dynamical model for the study of operational risk in banks and suitable for the calculation of the Value at Risk (VaR) is proposed. The equation of motion takes into account the interactions among different bank's processes, the spontaneous generation of losses via a noise term and the efforts made by the bank to avoid their occurrence. Since the model is very general, it can be tailored on the internal organizational structure of a specific bank by estimating some of its parameters from historical operational losses. The model is exactly solved in the case in which there are no causal loops in the matrix of couplings and it is shown how the solution can be exploited to estimate also the parameters of the noise. The forecasting power of the model is investigated by using a fraction $f$ of simulated data to estimate the parameters, showing that for $f = 0.75$ the VaR can be forecast with an error $\simeq 10^{-3}$.

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Paper provided by in its series Papers with number 1007.0026.

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Date of creation: Jun 2010
Date of revision: Feb 2012
Publication status: Published in Physica A 391 (2012), pp. 2641-2655
Handle: RePEc:arx:papers:1007.0026
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