Country risk forecasting for major oil exporting countries: A decomposition hybrid approach

Computers and Industrial Engineering

Volumn 63, Issue 3, 2012, Pages 641-651

  Li, Jian Ping ^a   Tang, Ling ^a,b   Sun, Xiao Lei ^a   Yu, Le An ^c,d   He, Wan ^e   Yang, Yu Ying ^a,b  

^a Chinese Academy of Sciences   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c INSTITUTE OF SYSTEMS SCIENCE   (China)

^d INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^e STATE GRID CORPORATION OF CHINA   (China)

Author keywords

Country risk; Decomposition; Energy security; Forecasting; Hybrid methodology; Risk control

Indexed keywords

COUNTRY RISKS; DECOMPOSITION METHODS; DECOMPOSITION PROCESS; DIVIDE AND CONQUER; ENERGY SECURITY; ENSEMBLE EMPIRICAL MODE DECOMPOSITION; HYBRID APPROACH; HYBRID METHODOLOGIES; LEAST SQUARES SUPPORT VECTOR REGRESSION; PREDICTION MODEL; PREDICTION TOOLS; RISK CONTROLS; STUDY SAMPLES;

DECOMPOSITION; ENGINEERING; INDUSTRY;

FORECASTING;

EID: 84866309960     PISSN: 03608352     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cie.2011.12.003     Document Type: Article

References (34)

1. I.M. Baek, A. Bandopadhyaya, and C. Du Determinants of market-assessed sovereign risk: Economic fundamentals or market risk appetite? Journal of International Money and Finance 24 2005 533 548
2. C. Borio, and F. Packer Assessing new perspectives on country risk BIS Quarterly Review 2004
3. E.C. Bouchet, and B. Groslambert Country risk assessment: A guide to global investment strategy 2003 John Wiley & Sons New York
4. G.E.P. Box, and G. Jenkins Time series analysis: Forecasting and control 1st ed. 1970 Holden Day Press San Francisco
5. R. Cantor, and P. Packe Determinants and impact of sovereign credit ratings Economic Policy Review 2 2 1996 37 54
6. J.C.B. Cooper Artificial neural networks versus multivariate statistics: An application from economics Journal of Applied Statistics 26 8 1999 909 921
7. J.C. Cosset, and J. Roy The determinants of country risk ratings Journal of International Business Studies 22 1 1991 135 142
8. G. Cuadra, and H. Sapriza Sovereign default, interest rates and political uncertainty in emerging markets Journal of International Economics 76 2008 78 88
9. J.L. Deng Control problems of grey systems System and Control Letter 5 2 1982 288 294
10. F.X. Diebold, and R.S. Mariano Comparing predictive accuracy Journal of Business & Economic Statistic 13 3 1995 253 263
11. Y. Fan, and L. Zhu A real options based model and its application to China's overseas oil investment decisions Energy Economics 32 2 2010 627 637
12. M.K. Hassan, N.C. Maroney, H.M. El-Sady, and A. Telfah Country risk and stock market volatility, predictability, and diversification in the Middle East and Africa Economic Systems 27 2003 63 82
13. He, W.; Sun, X. L.; Tang, L.; Li, J. P. (2009). Modeling on oil-importing risk under risk correlation. In Proceedings of 2009 international joint conference on computational sciences and optimization (Vol. 2, pp. 439-442). IEEE Computer Society CPS.
14. K. Hornik, M. Stinchocombe, and H. White Multilayer feedforward networks are universal approximators Neural Networks 2 5 1989 359 366
15. S. Hoti Modelling country spillover effects in country risk ratings Emerging Markets Review 6 4 2005 324 354
16. S. Hoti, M. McAleer, and L.L. Pauwels Modelling international tourism and country risk spillovers for Cyprus and Malta Tourism Management 28 6 2007 1472 1484
17. S. Hoti, M. McAleer, and R. Shareef Modelling country spillover effects in country risk ratings Emerging Markets Review 6 4 2005 324 345
18. Huang, N. E.; Shen, Z.; Long, S. R. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis. Proceedings of the Royal Society A 454, 903-995.
19. J.P. Li, X.L. Sun, W. He, L. Tang, and W.X. Xu Modeling dynamic correlations and spillover effects of country risk: Evidence from Russia and Kazakhstan International Journal of Information Technology & Decision Making 8 4 2009 803 818
20. D.H. Meldrum Country risk and foreign direct investment Business Economics 35 1 2000 33 40
21. R. Rios-Morales, D. Gamberger, T. Smuc, and F. Azuaje Innovative methods in assessing political risk for business internationalization Research in International Business and Finance 23 2009 144 156
22. J.L. Simpson, and J.P. Evans Systemic risk in the major Eurobanking markets: Evidence from inter-bank offered rates Global Finance Journal 16 2 2005 125 144
23. J.A.K. Suykens, and J. Vandewalle Least squares support vector machine classifiers Neural Processing Letters 9 3 1999 293 300
24. Tang, L.; Yu, L.; Wang, S. (2011). EEMD-LSSVR-based decomposition-and- ensemble methodology with application to nuclear energy demand forecasting. In Proceedings of fourth international joint conference on computational sciences and optimization (CSO 2011) (pp. 589-593). IEEE Computer Society.
25. T. Van Gestel, B. Baesens, P.V. Dijcke, J. Garcia, J.A.K. Suykens, and J. Vanthienen A process model to develop an internal rating system: Sovereign credit ratings Decision Support Systems 42 2 2006 1131 1151
26. V. Vapnik The nature of statistical learning theory 1995 Springer, Verlag New York
27. S. Wang, L. Yu, L. Tang, and S.Y. Wang A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China Energy 36 11 2011 6542 6554
28. S.Y. Wang, L. Yu, and K.K. Lai Crude oil price forecasting with TEI@I methodology Journal of Systems Sciences and Complexity 18 2 2005 145 166
29. H. White Connectionist nonparametric regression: multilayer feedforward networks can learn arbitrary mappings Neural Networks 3 1990 535 549
30. Wu, Z.; Huang, N. E. (2004). Ensemble empirical mode decomposition: a noise-assisted data analysis method, Centre for Ocean-Land-Atmosphere Studies, Technical Report 193(51).
31. Q.W. Xie, X. Bo, S.L. Peng, J.P. Li, W.X. Xu, and H. Han Bandwidth empirical mode decomposition and its application International Journal of Wavelets, Multiresolution and Information Processing 6 6 2008 777 798
32. J. Yim, and H. Mitchell Comparison of country risk models: Hybrid neural networks, logit models, discriminant analysis and cluster techniques Expert Systems with Applications 28 2005 137 148
33. L. Yu, S.Y. Wang, and K.K. Lai Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm Energy Economics 30 5 2008 2623 2635
34. X. Zhang, K.K. Lai, and S.Y. Wang A new approach for crude oil price analysis based on empirical mode decomposition Energy Economics 30 3 2008 905 918