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Interest rates mapping

Author

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

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. Exploratory data analysis includes a variety of tools widely used in econophysics and geostatistics. 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 pattern perception purposes, to develop and to explore economical hypotheses, to produce dynamic asset-liability simulations and for financial risk assessments. The feasibility of an application of interest rates mapping approach for the IRC forecasting is considered as well.

Suggested Citation

  • Kanevski, M. & Maignan, M. & Pozdnoukhov, A. & Timonin, V., 2008. "Interest rates mapping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3897-3903.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:15:p:3897-3903
    DOI: 10.1016/j.physa.2008.02.069
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    References listed on IDEAS

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    1. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871.
    2. 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.
    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.
    4. Di Matteo, T. & Aste, T. & Hyde, S.T. & Ramsden, S., 2005. "Interest rates hierarchical structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 21-33.
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    Cited by:

    1. Cousin, Areski & Maatouk, Hassan & Rullière, Didier, 2016. "Kriging of financial term-structures," European Journal of Operational Research, Elsevier, vol. 255(2), pages 631-648.
    2. Manuel Nunes & Enrico Gerding & Frank McGroarty & Mahesan Niranjan, 2020. "Long short-term memory networks and laglasso for bond yield forecasting: Peeping inside the black box," Papers 2005.02217, arXiv.org.

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