Andrew D. Sanford

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Working Abstract: It is only recently that banks have begun to take seriously the measurement and management of operational risks. The inclusion of operational risk within Basel II is evidence of its increased importance. Although much previous research into operational risk has been directed at methods for determining levels of economic capital, our(More)
A Bayesian simulation-based method is developed for estimating a class of interest rate models known as Affine Term Structure (ATS) models. The technique is based on a Markov Chain Monte Carlo algorithm, with the discrete observations on yields augmented by additional higher frequency latent data. The introduction of augmented yield data reduces the bias(More)
The business unit level operational risk manager is responsible for measuring, recording, predicting, communicating and controlling operational risks within their organizational units. In support of the risk manager's role, Bayesian networks have been recommended as a tool for operational risk management. In this research, we describe the development of a(More)
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