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A comparison of multi-factor term structure models for interbank rates

Author

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  • Frank J. Fabozzi

    (EDHEC Business School)

  • Francesco A. Fabozzi

    (Yale School of Management)

  • Diana Tunaru

    (University of Kent)

Abstract

In this paper, we present a robust predictive comparison of several continuous-time multi-factor models in the context of interbank rates. Recognizing the specific dynamics of the short-term segment of the yield curve, we examine the U.S. money market by extending two continuous-time frameworks with different factor structures, the Chan-Karolyi-Longstaff-Sanders (CKLS) model and the arbitrage-free dynamic Nelson-Siegel (AFDNS) model. A battery of formal forecasting accuracy tests is employed to select a subset of superior predictive models. Despite a better goodness-of-fit measure, additional factors improve the forecasting performance only for the CKLS family. With implications for monetary policy formulation, we found evidence of two separate maturity segments as the three-factor AFDNS and the five-factor CKLS models outperform parsimonious benchmarks in predicting the interbank rates for very short maturities. Our comparative forecasting results are re-confirmed with stronger out-of-sample performance for the five-factor CKLS model when the post global financial crisis sub-sample is analyzed.

Suggested Citation

  • Frank J. Fabozzi & Francesco A. Fabozzi & Diana Tunaru, 2023. "A comparison of multi-factor term structure models for interbank rates," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 323-356, July.
    • Handle: RePEc:kap:rqfnac:v:61:y:2023:i:1:d:10.1007_s11156-023-01147-2
    DOI: 10.1007/s11156-023-01147-2
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    More about this item

    Keywords

    Interbank rates; Continuous-time models; Multi-factor term structure models; Forecasting tests;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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