Abstract
To manage interest rate risk effectively, it would be desirable to have an idea of how the term structure changes over time. Techniques ranging from econometric modelling, time series analysis, including multivariate and non-linear systems, as well as neural networks and pattern recognition are used for forecasting purposes. However, for pricing derivative instruments the theory of diffusion processes and stochastic calculus are employed. The purpose of this paper is to present a technique that can be used for forecasting purposes and for valueing contingent daims.
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References
Babes, S. (1991): A Family of Ito Process Models for the Term Structure of Interest Rates, FORC Preprint: 90/24, University of Warwick, Coventry.
Breckling, J. and Dal Dosso, L. (1992): A Non-parametric Approach to Term Structure Estimation, Deutsche Bank Research, Frankfurt.
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© 1994 Physica-Verlag Heidelberg
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Breckling, J., Dal Dosso, L. (1994). Modelling of Term Structure Dynamics Using Stochastic Processes. In: Bol, G., Nakhaeizadeh, G., Vollmer, KH. (eds) Finanzmarktanwendungen neuronaler Netze und ökonometrischer Verfahren. Wirtschaftswissenschaftliche Beiträge, vol 93. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-46948-0_7
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DOI: https://doi.org/10.1007/978-3-642-46948-0_7
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-0748-6
Online ISBN: 978-3-642-46948-0
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