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Interest rates mapping

Author

Listed:
  • M. Kanevski
  • M. Maignan
  • A. Pozdnoukhov
  • V. Timonin

Abstract

The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a two-dimensional feature space - time and maturity. Geostatistical models and machine learning algorithms (multilayer perceptron and Support Vector Machines) were applied to produce interest rate maps. IR maps can be used for the visualisation and patterns perception purposes, to develop and to explore economical hypotheses, to produce dynamic asses-liability simulations and for the financial risk assessments. The feasibility of an application of interest rates mapping approach for the IRC forecasting is considered as well.

Suggested Citation

  • M. Kanevski & M. Maignan & A. Pozdnoukhov & V. Timonin, 2007. "Interest rates mapping," Papers 0709.4361, arXiv.org.
    • Handle: RePEc:arx:papers:0709.4361
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    References listed on IDEAS

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    1. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and multifractality in the term structure of LIBOR interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 603-614.
    2. McNelis, Paul D., 2004. "Neural Networks in Finance," Elsevier Monographs, Elsevier, edition 1, number 9780124859678.
    3. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
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