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Interest Rate Risk - The Impact of the Yield Curve on Treasury Bill Returns

Received: 14 September 2016    Accepted: 13 October 2016    Published: 14 November 2016
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Abstract

Interest rate risk involves the risk to earnings or capital arising from movement of interest rates. It arises from differences between the timing of rate changes and the timing of cash flows (re-pricing risk); changing rate relationships among yield curves that affect bank activities (basic risk); from changing rate relationships across the spectrum of maturities (yield curve risk); and from interest-rate-related options entrenched in bank products (option risk). This paper assessed the impact of the level, slope and curvature components of the yield curve on treasury bill returns using secondary data to draw quarterly yield curves for the various maturity periods. This approach was extended to capture the sensitivity to changes in the level, slope, and curvature of the term structure using the parameters of the dynamic [14] model to fit the term structure. The results revealed that, the shorter the yield to maturity the stable and better the returns or yield. Applying dynamic factor models, it was seen that, the slope factor representing the short term component had better returns compared to the medium term and the long term components. Also, the results revealed that, the 91 day T-bill which represents the short term component produced better and much stable returns compared with the 182 day T- bill and 1 year note representing the medium and long term components respectively.

Published in Advances in Applied Sciences (Volume 1, Issue 3)
DOI 10.11648/j.aas.20160103.13
Page(s) 63-68
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Yield Curve, Interest Rate Risk, Term Structure, Dynamic Factor

References
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[2] Allen, F., and Santomero, A. M., (2001): What do financial intermediaries do? Journal of Banking and Finance, 25: 271-294.
[3] Dai, Q., and Singleton K., (2000). Specification Analysis of Affine Term Structure Models. Journal of Finance, 55 (1): 943-1,978.
[4] Diebold, F., Rudebusch S., and Aruoba S., (2006). The Macroeconomy and the Yield Curve. J. Econometrics, 131: 309-338.
[5] Diebold, F., and Li C., (2006): Forecasting the term structure of government bond yields. Journal of Econometrics, 130 (2): 337-364.
[6] Durbin, J., and Koopman S. J., (2001). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.
[7] Watson M. W., and Engle, R. F., (1983). Alternative Algorithms for Estimation of Dynamic MIMIC, Factor, and Time Varying Coefficient Regression Models. Journal of Econometrics, 23: 385-400.
[8] Evans, C., and Marshall, D., (2001). Economic Determinants of the Nominal Treasury Yield Curve. FRB Chicago, Working Paper 01-16.evidence. Financial Markets, Institutions, and Instruments, 12: 257-289. Finance, 36: 323-335.
[9] Fogler, H. R., John K., and Tipton, J., (1981): Three factors, interest rate differentials and stock groups. Journal of Finance, 36; 323-335.
[10] French, R., Ruback, R. S., and Schwert, W. G., (1983). Effects of Nominal Contracting on Stock Returns. Journal of Political Economy, 91: 70-96.
[11] Geweke, J., (1977). The Dynamic Factor Analysis of Economic Time Series, in Latent Variables in Socio-Economic Models, ed. by D. J. Aigner and A. S. Goldberger, Amsterdam: North-Holland.
[12] Litterman, R., and Scheinkman, J., (1991). Common factors affecting bond returns. Journal of Fixed Income, 1(1): 54-61.
[13] Lynge, J., and Zumwalt, J. K., (1980). An Empirical Study of the Interest Rate Sensitivity of Commercial Bank Returns: a Multi-index Approach. Journal of Financial and Quantitative Analysis, 15: 731-742.
[14] Nelson, C., and Siegel A., (1987). Parsimonious Modelling of Yield Curves. Journal of Business, 60: (4); 473-489.
[15] Samuelson, P. A., (1945). The effect of interest rate increases on the banking system. American Economic Review, 35: 16-27.
[16] Sargent, T. J., and Sims, C. A., (1977). Business Cycle Modeling Without Pretending to Have Too Much A-Priori Economic Theory, in New Methods in Business Cycle Research, ed. by C. Sims et al., Minneapolis: Federal Reserve Bank of Minneapolis.
[17] Stock, J. H., and Watson M. W., (1988). Testing for Common Trends. Journal of the American Statistical Association, 83: 404, 1097-1107.
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  • APA Style

    Abonongo John, Luguterah Albert, Anuwoje Ida Logubayom. (2016). Interest Rate Risk - The Impact of the Yield Curve on Treasury Bill Returns. Advances in Applied Sciences, 1(3), 63-68. https://doi.org/10.11648/j.aas.20160103.13

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    ACS Style

    Abonongo John; Luguterah Albert; Anuwoje Ida Logubayom. Interest Rate Risk - The Impact of the Yield Curve on Treasury Bill Returns. Adv. Appl. Sci. 2016, 1(3), 63-68. doi: 10.11648/j.aas.20160103.13

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    AMA Style

    Abonongo John, Luguterah Albert, Anuwoje Ida Logubayom. Interest Rate Risk - The Impact of the Yield Curve on Treasury Bill Returns. Adv Appl Sci. 2016;1(3):63-68. doi: 10.11648/j.aas.20160103.13

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  • @article{10.11648/j.aas.20160103.13,
      author = {Abonongo John and Luguterah Albert and Anuwoje Ida Logubayom},
      title = {Interest Rate Risk - The Impact of the Yield Curve on Treasury Bill Returns},
      journal = {Advances in Applied Sciences},
      volume = {1},
      number = {3},
      pages = {63-68},
      doi = {10.11648/j.aas.20160103.13},
      url = {https://doi.org/10.11648/j.aas.20160103.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20160103.13},
      abstract = {Interest rate risk involves the risk to earnings or capital arising from movement of interest rates. It arises from differences between the timing of rate changes and the timing of cash flows (re-pricing risk); changing rate relationships among yield curves that affect bank activities (basic risk); from changing rate relationships across the spectrum of maturities (yield curve risk); and from interest-rate-related options entrenched in bank products (option risk). This paper assessed the impact of the level, slope and curvature components of the yield curve on treasury bill returns using secondary data to draw quarterly yield curves for the various maturity periods. This approach was extended to capture the sensitivity to changes in the level, slope, and curvature of the term structure using the parameters of the dynamic [14] model to fit the term structure. The results revealed that, the shorter the yield to maturity the stable and better the returns or yield. Applying dynamic factor models, it was seen that, the slope factor representing the short term component had better returns compared to the medium term and the long term components. Also, the results revealed that, the 91 day T-bill which represents the short term component produced better and much stable returns compared with the 182 day T- bill and 1 year note representing the medium and long term components respectively.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - Interest Rate Risk - The Impact of the Yield Curve on Treasury Bill Returns
    AU  - Abonongo John
    AU  - Luguterah Albert
    AU  - Anuwoje Ida Logubayom
    Y1  - 2016/11/14
    PY  - 2016
    N1  - https://doi.org/10.11648/j.aas.20160103.13
    DO  - 10.11648/j.aas.20160103.13
    T2  - Advances in Applied Sciences
    JF  - Advances in Applied Sciences
    JO  - Advances in Applied Sciences
    SP  - 63
    EP  - 68
    PB  - Science Publishing Group
    SN  - 2575-1514
    UR  - https://doi.org/10.11648/j.aas.20160103.13
    AB  - Interest rate risk involves the risk to earnings or capital arising from movement of interest rates. It arises from differences between the timing of rate changes and the timing of cash flows (re-pricing risk); changing rate relationships among yield curves that affect bank activities (basic risk); from changing rate relationships across the spectrum of maturities (yield curve risk); and from interest-rate-related options entrenched in bank products (option risk). This paper assessed the impact of the level, slope and curvature components of the yield curve on treasury bill returns using secondary data to draw quarterly yield curves for the various maturity periods. This approach was extended to capture the sensitivity to changes in the level, slope, and curvature of the term structure using the parameters of the dynamic [14] model to fit the term structure. The results revealed that, the shorter the yield to maturity the stable and better the returns or yield. Applying dynamic factor models, it was seen that, the slope factor representing the short term component had better returns compared to the medium term and the long term components. Also, the results revealed that, the 91 day T-bill which represents the short term component produced better and much stable returns compared with the 182 day T- bill and 1 year note representing the medium and long term components respectively.
    VL  - 1
    IS  - 3
    ER  - 

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Author Information
  • College of Science, Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

  • Faculty of Mathematical Sciences, Department of Statistics, University for Development Studies, Navrongo, Ghana

  • Faculty of Mathematical Sciences, Department of Statistics, University for Development Studies, Navrongo, Ghana

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