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Volumn 3070, Issue , 2004, Pages 1130-1135

One day prediction of NIKKEI index considering information from other stock markets

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL MODELS; NONLINEAR SYSTEMS; NUMERICAL ANALYSIS; OSCILLATORS (ELECTRONIC); SIGNAL PROCESSING;

EID: 9444265367     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24844-6_177     Document Type: Conference Paper
Times cited : (23)

References (11)
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    • Computational learning techniques for intraday fx trading using popular technical indicators
    • Dempster, T.P., et al.: Computational learning techniques for intraday fx trading using popular technical indicators. IEEE Transactions on Neural Networks 12 (2001) 744-754
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 744-754
    • Dempster, T.P.1
  • 3
    • 0030130832 scopus 로고    scopus 로고
    • A "world" model of integrated financial markets using artificial neural networks
    • Podding, T., Rehkegler, H.: A "world" model of integrated financial markets using artificial neural networks. Neurocomputing 10 (1996) 251-273
    • (1996) Neurocomputing , vol.10 , pp. 251-273
    • Podding, T.1    Rehkegler, H.2
  • 4
    • 0030130754 scopus 로고    scopus 로고
    • A multi-component nonlinear prediction system for the s&p 500 index
    • Chenoweth, T., Obradović, Z.: A multi-component nonlinear prediction system for the s&p 500 index. Neurocomputing 10 (1996) 275-290
    • (1996) Neurocomputing , vol.10 , pp. 275-290
    • Chenoweth, T.1    Obradović, Z.2
  • 5
    • 0035272716 scopus 로고    scopus 로고
    • Divide-and-conquer learning and modular perceptron networks
    • Fu, H.C., Lee, Y.P., et al.: Divide-and-conquer learning and modular perceptron networks. IEEE Transactions on Neural Networks 12 (2001) 250-263
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 250-263
    • Fu, H.C.1    Lee, Y.P.2
  • 6
    • 0033743072 scopus 로고    scopus 로고
    • Combination of artificial neural-network forecasters for prediction of natural gas consumption
    • Khotanzad, A., Elragal, H., et al.: Combination of artificial neural-network forecasters for prediction of natural gas consumption. IEEE Transactions on Neural Networks 11 (2000) 464-473
    • (2000) IEEE Transactions on Neural Networks , vol.11 , pp. 464-473
    • Khotanzad, A.1    Elragal, H.2
  • 8
    • 0035392694 scopus 로고    scopus 로고
    • Financial time series prediction using least squares support vector machnies within the evidence framework
    • Tony Gestel, J.S., et al.: Financial time series prediction using least squares support vector machnies within the evidence framework. IEEE Transactions on Neural Networks 12 (2001) 809-820
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 809-820
    • Tony Gestel, J.S.1
  • 9
    • 0035392695 scopus 로고    scopus 로고
    • Financial volatility trading using recurent neural networks
    • Peter Tino, C.S., et al: Financial volatility trading using recurent neural networks. IEEE Transactions on Neural Networks 12 (2001) 865-874
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 865-874
    • Peter Tino, C.S.1
  • 10
    • 0035329583 scopus 로고    scopus 로고
    • Selecting inputs for modeling using normalized higher order statistics and independent component analysis
    • Back, A., Trappenberg, T.: Selecting inputs for modeling using normalized higher order statistics and independent component analysis. IEEE Transactions on Neural Networks 12 (2001) 612-617
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 612-617
    • Back, A.1    Trappenberg, T.2
  • 11
    • 0035391019 scopus 로고    scopus 로고
    • Forecasting volatility with neural regression: A contribution to model adequacy
    • Refenes, A., Holt, W.: Forecasting volatility with neural regression: A contribution to model adequacy. IEEE Transactions on Neural Networks 12 (2001) 850-864
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 850-864
    • Refenes, A.1    Holt, W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.