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International Yield Curve Prediction with Common Functional Principal Component Analysis

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Robustness in Econometrics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 692))

Abstract

We propose an international yield curve predictive model, where common factors are identified using the common functional principal component (CFPC) method that enables a comparison of the variation patterns across different economies with heterogeneous covariances. The dynamics of the international yield curves are further forecasted based on the data-driven common factors in an autoregression framework. For the 1-day ahead out-of-sample forecasts of the US, Sterling, Euro and Japanese yield curve from 07 April 2014 to 06 April 2015, the CFPC factor model is compared with an alternative factor model based on the functional principal component analysis.

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References

  1. Ash RB, Gardner MF (1975) Topics in stochastic processes, Probability and mathematical statistics series. Academic Press, New York

    Google Scholar 

  2. Benko M (2006) Functional data analysis with applications in finance. Phd thesis, Humboldt-Universität, Berlin

    Google Scholar 

  3. Benko M, Härdle WK, Kneip A (2009) Common functional principal components. Ann Stat 37(1):1–34

    Article  MathSciNet  MATH  Google Scholar 

  4. Boente G, Rodriguez D, Sued M (2010) Inference under functional proportional and common principal component models. J Multivar Anal 101(2):464–475

    Article  MathSciNet  MATH  Google Scholar 

  5. Chen Y, Li B (2011) Forecasting yield curves in an adaptive framework. Cent Eur J Econ Model Econometrics 3(4):237–259

    Google Scholar 

  6. Chen Y, Niu L (2014) Adaptive dynamic nelson-siegel term structure model with applications. J Econometrics 180(1):98–115

    Article  MathSciNet  MATH  Google Scholar 

  7. Coffey N, Harrison AJ, Donoghue OA, Hayes K (2011) Common functional principal components analysis: a new approach to analyzing human movement data. Hum Mov Sci 30(6):1144–1166

    Google Scholar 

  8. Di C-Z, Crainiceanu CM, Caffo BS, Punjabi NM (2009) Multilevel functional principal component analysis. Ann Appl Stat 3(1):458–488

    Article  MathSciNet  MATH  Google Scholar 

  9. Diebold FX, Li C (2006) Forecasting the term structure of government bond yields. J Econometrics 130(2):337–364

    Article  MathSciNet  MATH  Google Scholar 

  10. Diebold FX, Li C, Yue VZ (2008) Global yield curve dynamics and interactions: A dynamic nelson-siegel approach. J Econometrics 146(2):351–363

    Article  MathSciNet  MATH  Google Scholar 

  11. Duffee GR (2002) Term premia and interest rate forecasts in affine models. J Finance 57(1):405–443

    Google Scholar 

  12. Duffee GR (2011) Forecasting with the term structure: the role of no-arbitrage restrictions. The Johns Hopkins University, Department of Economics, Economics Working Paper Archive (576)

    Google Scholar 

  13. Egorov AV, Li H, Ng D (2011) A tale of two yield curves: modeling the joint term structure of dollar and euro interest rates. J Econometrics 162(1):55–70

    Article  MathSciNet  MATH  Google Scholar 

  14. Estrella A, Hardouvelis GA (1991) The term structure as a predictor of real economic activity. J Finance 46(2):555

    Article  Google Scholar 

  15. Ferraty F, Vieu P (2006) Nonparametric functional data analysis: theory and practice, Springer series in statistics. Springer, New York

    MATH  Google Scholar 

  16. Flury BN (1988) Common principal components and related multivariate models, Wiley series in probability and mathematical statistics. Wiley, New York

    MATH  Google Scholar 

  17. Hall P, Müller H-G, Wang J-L (2006) Properties of principal component methods for functional and longitudinal data analysis. Ann Stat 34(3):1493–1517

    Article  MathSciNet  MATH  Google Scholar 

  18. Hays S, Shen H, Huang JZ (2012) Functional dynamic factor models with application to yield curve forecasting. Ann Appl Stat 6(3):870–894

    Article  MathSciNet  MATH  Google Scholar 

  19. Hyndman RJ, Yasmeen F (2014) Common functional principal component models for mortality forecasting. Contributions in infinite-dimensional statistics and related topics, Societa Editrice Esculapio, Bologna, pp 19–24

    Google Scholar 

  20. Knez PJ, Litterman RB, Scheinkman J (1994) Explorations into factors explaining money market returns. J Finan 49(5):1861–1882

    Article  Google Scholar 

  21. Litterman RB, Scheinkman J (1991) Common factors affecting bond returns. J Fixed Income 1(1):54–61

    Article  Google Scholar 

  22. Müller H-G, Sen R, Stadtmüller U (2011) Functional data analysis for volatility. J Econometrics 165(2):233–245

    Article  MathSciNet  MATH  Google Scholar 

  23. Nelson CR, Siegel AF (1987) Parsimonious modeling of yield curves. J. Bus 60(4):473–489

    Article  Google Scholar 

  24. Piazzesi M (2010) Affine term structure models. In: Handbook of financial econometrics. Handbooks in finance, vol 1. North-Holland, Boston, pp 691–766

    Google Scholar 

  25. Ramsay JO, Dalzell CJ (1991) Some tools for functional data analysis. J Roy Stat Soc Ser B (Stat Methodol) 53(3):539–572

    MathSciNet  MATH  Google Scholar 

  26. Ramsay JO, Ramsey JB (2002) Functional data analysis of the dynamics of the monthly index of nondurable goods production. J Econometrics 107(1–2):327–344

    Article  MathSciNet  MATH  Google Scholar 

  27. Stoer J (2005) Numerische Mathematik: Eine Einführung, Springer-Lehrbuch, 9th edn. Springer, Berlin

    Google Scholar 

  28. Wang Z, Sun Y, Li P (2014) Functional principal components analysis of Shanghai stock exchange 50 index. Discrete Dyn Nat Soc 2014(3):1–7

    Google Scholar 

  29. Wooldridge JM (2013) Introductory econometrics: a modern approach, 5th edn. South-Western Cengage Learning, Mason

    Google Scholar 

  30. Yao F, Müller H-G, Wang J-L (2005) Functional data analysis for sparse longitudinal data. J Am Stat Assoc 100(470):577–590

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore

    Jiejie Zhang & Ying Chen

  2. Center for Mathematics, Technische Universität München, Munich, Germany

    Stefan Klotz

  3. Lee Kong Chian School of Business, Singapore Management University, Singapore, Singapore

    Kian Guan Lim

Authors
  1. Jiejie Zhang
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  2. Ying Chen
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  3. Stefan Klotz
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  4. Kian Guan Lim
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Corresponding author

Correspondence to Jiejie Zhang .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso Department of Computer Science, El Paso, TX, USA

    Vladik Kreinovich

  2. Faculty of Economics, Chiang Mai University Faculty of Economics, Chiang Mai, Thailand

    Songsak Sriboonchitta

  3. Japan Adv. Inst. of Sci. & Tech. (JAIST) , Ishikawa, Japan

    Van-Nam Huynh

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Zhang, J., Chen, Y., Klotz, S., Lim, K.G. (2017). International Yield Curve Prediction with Common Functional Principal Component Analysis. In: Kreinovich, V., Sriboonchitta, S., Huynh, VN. (eds) Robustness in Econometrics. Studies in Computational Intelligence, vol 692. Springer, Cham. https://doi.org/10.1007/978-3-319-50742-2_17

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  • DOI: https://doi.org/10.1007/978-3-319-50742-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50741-5

  • Online ISBN: 978-3-319-50742-2

  • eBook Packages: EngineeringEngineering (R0)

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