Interest rate prediction: a neuro-hybrid approach with data preprocessing

References

• Aliev, R. A., B. Fazlollahi, and R. R. Aliev. 2004. Soft Computing and Its Applications in Business and Economics. Warsaw: Springer Verlag: 450.
   Google Scholar
• Aliev, R. A., B. G. Guirimov, B. Fazlollahi, and R. R. Aliev. 2009. “Evolutionary Algorithm-based Learning of Fuzzy Neural Networks, Part 2: Recurrent Fuzzy Neural Networks.” Fuzzy Sets and Systems 160 (17): 2553–2566.
   Web of Science ®Google Scholar
• Barkoulas, J. T., C. F. Baum, and J. Onochie. 1997. “A Nonparametric Investigation of the 90-day T-bill Rate.” Review of Financial Economics 6: 187–198.
   Google Scholar
• BIS. 2005. Zero-coupon Yield Curves: Technical Documentation. Bank for International Settlements: Basel.
   Google Scholar
• Björk, T., and B. J. Christensen. 2009. “Interest Rate Dynamics and Consistent Forward Rate Curves.” Mathematical Finance 9: 323–348.
   Web of Science ®Google Scholar
• Bliss, R. R. 1997. “Testing Term Structure Estimation Methods.” Advances in Futures and Options Research 9: 197–231.
   Google Scholar
• Bo, Q., and R. Khaled. 2004. “Hurst Exponent and Financial Market Predictability.” IASTED Conference on Financial Engineering and Applications FEA 203–209.
   Google Scholar
• Boyacioglu, M. A., and D. Avci. 2010. “An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the Prediction of Stock Market Return: The Case of the Istanbul Stock Exchange.” Expert Systems with Applications 37 (12): 7908–7912.
   Web of Science ®Google Scholar
• Chen, M-Y, and D. A. Linkens. 2004. “Rule-base Self-generation and Simplification for Data-driven Fuzzy Models.” Journal of Fuzzy Sets and Systems 142: 243–265.
   Web of Science ®Google Scholar
• Cleveland, W. S., and S. J. Devlin. 1988. “Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting.” Journal of the American Statistical Association 83: 596–610.
   Web of Science ®Google Scholar
• Cox, J., J. E. Ingersoll, and S. A. Ross. 1985. “A Theory of the Term Structure of Interest Rates.” Econometrica 53: 385–407.
   Web of Science ®Google Scholar
• Dai, Q., and K. J. Singleton. 2000. “Specification Analysis of Affine Term Structure Models.” Journal of Finance 55: 1943–1978.
   Web of Science ®Google Scholar
• Das, S. R. 1994. Mean Rate Shifts and Alternative Models of the Interest Rate: Theory and Evidence, 39. Boston, MA: Division of Research, Harvard Business School.
   Google Scholar
• Diebold, F. X., and C. Li. 2006. “Forecasting the Term Structure of Government Bond Yields.” Journal of Econometrics 130: 337–364.
   Web of Science ®Google Scholar
• Duffie, D., and R. Kan. 1996. “A Yield-Factor Model of Interest Rates.” Mathematical Finance 6: 379–406.
   Google Scholar
• Van Gestel, T., J. A. K. Suykens, D. Baestaens, A. Lambrechts, G. Lanckriet, B. Vandaele, B. De Moor, and J. Vandewalle. 2001. “Financial Time Series Prediction Using Least Squares Support Vector Machines Within the Evidence Framework.” IEEE Transactions on Neural Networks 12 (4): 809–821.
   PubMed Web of Science ®Google Scholar
• Gong, F., and E. M. Remolona. 1997. A Three-factor Econometric Model of the US Term Structure. Federal Reserve Bank of New York Staff Reports, No. 19.
   Google Scholar
• Gower, J. C. 1967. “A Comparison of Some Methods of Cluster Analysis.” Biometrics 4 (23): 623–638.
   Web of Science ®Google Scholar
• Granger, C. W., and T. Terasvirta. 1993. Non-linear Economic Relationships. Oxford: Oxford University Press.
   Google Scholar
• Hamilton, J. 1988. “Rational Expectations Econometric Analysis of Changes in Regimes: An Investigation of the Term Structure of Interest Rates.” Journal of Economic Dynamics and Control 12 (2–3): 385–423.
   Web of Science ®Google Scholar
• Hurst, H. E. 1951. “Long-term Storage of Reservoirs: An Experimental Study.” Transactions of the American Society of Civil Engineers 116: 770–799.
   Google Scholar
• Ince, H., and B. T. Trafalis. 2007. “Kernel Principal Component Analysis and Support Vector Machines for Stock Price Prediction.” IIE Transactions 39 (6): 629–637.
   Web of Science ®Google Scholar
• Johnson, R. A., and D. W. Wichern. 2002. Applied Multivariate Statistical Analysis. Upper Saddle River, NJ: Prentice-Hall.
   Google Scholar
• De Jong, F. 2000. “Time Series and Cross-section Information in Affine Term-structure Models.” Journal of Business & Economic Statistics 18: 300–314.
   Web of Science ®Google Scholar
• Kang, S. 1991. An Investigation of the Use of Feed Forward Neural Networks for Forecasting. Kent, OH: University Microfilms Int./UMI.
   Google Scholar
• Karri, V., T. Ho, and O. Madsen. 2008. “Artificial Neural Networks and Neuro-fuzzy Inference Systems as Virtual Sensors for Hydrogen Safety Prediction.” International Journal of Hydrogen Energy 33 (11): 2857–2867.
   Web of Science ®Google Scholar
• Kasabov, N. K., and Q. Song. 2002. “DENFIS: Dynamic Evolving Neural-Fuzzy Inference System and Its Application for Time-series Prediction.” IEEE Transactions on Fuzzy Systems 10 (2): 144–154.
   Web of Science ®Google Scholar
• Khashei, M., S. R. Hejazi, and M. Bijari. 2008. “A New Hybrid Artificial Neural Networks and Fuzzy Regression Model for Time Series Forecasting.” Fuzzy Sets and Systems 159: 769–786.
   Web of Science ®Google Scholar
• Kim, K. J., and I. Han. 2000. “Genetic Algorithms Approach to Feature Discretization in Artificial Neural Networks for the Prediction of Stock Price Index.” Expert Systems with Applications 19: 125–132.
   Web of Science ®Google Scholar
• Kruse, R. 2008. “Combining Fuzzy Systems With Neural Networks.” Scholarpedia 3 (11): 6043 (Germany).
   Google Scholar
• Kung, C. Y., and K. L. Wen. 2007. “Applying Grey Relational Analysis and Grey Decision-Making to evaluate the relationship between company attributes and its financial performance – A case study of venture capital enterprises in Taiwan.” Decision Support Systems 43 (3): 842–852.
   Web of Science ®Google Scholar
• Larrain, M. 1991. “Testing Chaos and Nonlinearities in T-bill Rates.” Financial Analysts Journal 47 (5): 51–62.
   Google Scholar
• LeRoy, F. S. 1989. “Efficient Capital Markets and Martingales.” Journal of Economic Literature 27 (4): 1583–1621.
   Web of Science ®Google Scholar
• Litterman, R., and J. Scheinkman. 1991. “Common Factors Affecting Bond Returns.” Journal of Fixed Income 1 (1): 54–61.
   Google Scholar
• Milligan, G. W., and M. C. Cooper. 1980. “An Examination of the Effect of Six Types of Error Perturbation on Fifteen Clustering Algorithms.” Psychometrika 45 (3): 159–179.
   Web of Science ®Google Scholar
• Mingoti, A. S., and O. J. Lima. 2006. “Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms.” European Journal of Operational Research 174 (3): 1742–1759.
   Web of Science ®Google Scholar
• Naik, Vasant, and M. Lee. 1994. The Yield Curve and Bond Option Prices with Discrete Shifts in Economic Regimes. Retrieved from SSRN: http://ssrn.com/abstract=5684
   Google Scholar
• Nelson, C. R., and A. F. Segel. 1987. “Parsimonious Modeling of Yield Curves.” Journal of Business 60 (4): 473–489.
   Web of Science ®Google Scholar
• Pfann, G. A., P. C. Schotman, and R. Tschernig. 1996. “Non-linear Interest Rate Dynamics and Implications for the Term Structure.” Journal of Econometrics 74: 149–176.
   Web of Science ®Google Scholar
• Svensson, L. E. O. 1994. Estimating and Interpreting Forward Interest Rates: Sweden 1992–1994. Sweden: International Monetary Fund: 29.
   Google Scholar
• Thawornwong, S., and D. Enke. 2003. “The Adaptive Selection of Financial and Economic Variables for Use With Artificial Neural Networks.” Neurocomputing 56: 205–232.
   Web of Science ®Google Scholar
• Thilo, F., M. Grauer, and C. Müller. 2007. “Parallel Direct Search Methods for Optimization Services in Grid Computing.” Frontiers Science Series 49: 423–424.
   Google Scholar
• Thilo, F., M. Grauer, R. Menzel, and C. Müller. 2007. “On Scalability of Distributed Simulation and Optimization of Forming Processes.” AIP Conference Proceedings 908: 1585–1590.
   Google Scholar
• Vasicek, O. A., and H. G. Fong. 1982. “Term Structure Modeling Using Exponential Splines.” Journal of Finance 37: 339–348.
   Web of Science ®Google Scholar