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Volumn , Issue , 2010, Pages 301-309

Feature clustering with self-organizing maps and an application to financial time-series for portfolio selection

Author keywords

Correlation hunting; Feature clustering; Portfolio selection; Self organizing maps; Time series clustering

Indexed keywords

CORRELATION HUNTING; DISTANCE MATRICES; DYNAMIC SYSTEMS; FEATURE CLUSTERING; FINANCIAL RISKS; GENERIC METHOD; HIERARCHICAL CLUSTERING METHODS; INPUT DATAS; MARKET DOWNTURN; NON-LINEAR CORRELATIONS; NON-LINEAR RELATIONSHIPS; PORTFOLIO SELECTION; STOCK MARKET;

EID: 78651432006     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (25)

References (33)
  • 2
    • 84974489693 scopus 로고
    • Numerical valuation of high dimensional multivariate american securities
    • Barraquand, J. and Martineau, D. (1995). Numerical valuation of high dimensional multivariate american securities. Journal of Financial and Quantitative Analysis, 30(03):383-405.
    • (1995) Journal of Financial and Quantitative Analysis , vol.30 , Issue.3 , pp. 383-405
    • Barraquand, J.1    Martineau, D.2
  • 3
    • 37549029793 scopus 로고    scopus 로고
    • The properties of high-dimensional data spaces: Implications for exploring gene and protein expression data
    • Clark, R., Ressom, H. W, Wang, A., Xuan, J., Liu, M., Gehan, E., and Wang, Y (2008). The properties of high-dimensional data spaces: implications for exploring gene and protein expression data. Nature Reviews Cancer, 8:37-49.
    • (2008) Nature Reviews Cancer , vol.8 , pp. 37-49
    • Clark, R.1    Ressom, H.W.2    Wang, A.3    Xuan, J.4    Liu, M.5    Gehan, E.6    Wang, Y.7
  • 4
    • 0031641473 scopus 로고    scopus 로고
    • Financial applications of selforganizing maps
    • Deboeck, G. J. (1998). Financial applications of selforganizing maps. In NEURAL NETWORK WORLD, volume 8, pages 213-241.
    • (1998) Neural Network World , vol.8 , pp. 213-241
    • Deboeck, G.J.1
  • 5
    • 2942723846 scopus 로고    scopus 로고
    • A divisive information theoretic feature clustering algorithm for text classification
    • Dhillon, I. S., Mallela, S., and Kumar, R. (2003). A divisive information theoretic feature clustering algorithm for text classification. The Journal of Machine Learning Research, 3:1265-1287.
    • (2003) The Journal of Machine Learning Research , vol.3 , pp. 1265-1287
    • Dhillon, I.S.1    Mallela, S.2    Kumar, R.3
  • 6
    • 21444445247 scopus 로고    scopus 로고
    • Clustering of financial time series with application to index and enhanced index tracking portfolio
    • Dose, C. and Cincotti, S. (2005). Clustering of financial time series with application to index and enhanced index tracking portfolio. PhysicaA: Statistical Mechanics and its Applications, 355(1):145-151.
    • (2005) PhysicaA: Statistical Mechanics and Its Applications , vol.355 , Issue.1 , pp. 145-151
    • Dose, C.1    Cincotti, S.2
  • 7
    • 0000256876 scopus 로고
    • Le traitement des variables vectorielles
    • Escoufier, Y (1973). Le traitement des variables vectorielles. Biometrics.
    • (1973) Biometrics.
    • Escoufier, Y.1
  • 8
    • 84956853519 scopus 로고    scopus 로고
    • On the use of self-organizing maps for clustering and visualization
    • Flexer, A. (1999). On the use of self-organizing maps for clustering and visualization. In Principles of Data Mining and Knowledge Discovery, pages 80-88.
    • (1999) Principles of Data Mining and Knowledge Discovery , pp. 80-88
    • Flexer, A.1
  • 9
    • 0032269108 scopus 로고    scopus 로고
    • How many clusters? which clustering method? answers via model-based cluster analysis
    • Fraley, C. and Raftery, A. E. (1998). How many clusters? which clustering method? answers via model-based cluster analysis. The Computer Journal, 41:578-588.
    • (1998) The Computer Journal , vol.41 , pp. 578-588
    • Fraley, C.1    Raftery, A.E.2
  • 14
    • 0004090577 scopus 로고    scopus 로고
    • SpringerVerlag New York, Inc., Secaucus, NJ, USA
    • Kohonen, T. (2001). Self-Organizing Maps. SpringerVerlag New York, Inc., Secaucus, NJ, USA.
    • (2001) Self-Organizing Maps.
    • Kohonen, T.1
  • 17
    • 3543076856 scopus 로고    scopus 로고
    • chapter The Self-Organizing Map as a Tool in Knowledge Engineering, Soft Computing. World Scientific Publishing
    • Pal, N. R., editor (2001). Pattern Recognition in Soft Computing Paradigm, chapter The Self-Organizing Map as a Tool in Knowledge Engineering, pages 38-65. Soft Computing. World Scientific Publishing.
    • (2001) Pattern Recognition in Soft Computing Paradigm , pp. 38-65
    • Pal, N.R.1
  • 18
    • 0000325341 scopus 로고
    • On lines and planes of closest fit to systems of points in space
    • Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine, 2(6):559-572.
    • (1901) Philosophical Magazine , vol.2 , Issue.6 , pp. 559-572
    • Pearson, K.1
  • 19
    • 84899118834 scopus 로고    scopus 로고
    • Distance and feature-based clustering of time series: An application on neurophysiology
    • London, UK. SpringerVerlag
    • Potamias, G. (2002). Distance and feature-based clustering of time series: An application on neurophysiology. In SETN '02: Proceedings of the Second Hellenic Conference on Al, pages 237-248, London, UK. SpringerVerlag.
    • (2002) SETN '02: Proceedings of the Second Hellenic Conference on Al , pp. 237-248
    • Potamias, G.1
  • 20
    • 79952389669 scopus 로고    scopus 로고
    • A hybrid parallel som algorithm for large maps in data-mining
    • Neves, J., Santos, M. R, and Machado, J., editors, Portugal. Associação Portuguesa para a Inteligência Artificial (APPIA)
    • Silva, B. and Marques, N. (2007). A hybrid parallel som algorithm for large maps in data-mining. In Neves, J., Santos, M. R, and Machado, J., editors, New Trends in Artificial Intelligence, Guimarães. Portugal. Associação Portuguesa para a Inteligência Artificial (APPIA).
    • (2007) New Trends in Artificial Intelligence, Guimarães
    • Silva, B.1    Marques, N.2
  • 22
    • 0345689416 scopus 로고    scopus 로고
    • Cluster analysis of frnri data using dendrogram sharpening
    • Stanberry, L., Nandy, R., and Cordes, D. (2003). Cluster analysis of frnri data using dendrogram sharpening. Human brain mapping.
    • (2003) Human Brain Mapping
    • Stanberry, L.1    Nandy, R.2    Cordes, D.3
  • 23
    • 0346507583 scopus 로고    scopus 로고
    • Forming of the investment portfolio using the self-organizing maps (som)
    • Stankevicius, G. (2001). Forming of the investment portfolio using the self-organizing maps (som). INFORMATICA.
    • (2001) Informatica
    • Stankevicius, G.1
  • 26
    • 38049168357 scopus 로고    scopus 로고
    • SOM-based data visualization methods
    • Vesanto, J. (1999). SOM-based data visualization methods. Intelligent-Data-Analysis, 3:111-26.
    • (1999) Intelligent-Data-Analysis , vol.3 , pp. 111-126
    • Vesanto, J.1
  • 27
    • 0003642575 scopus 로고    scopus 로고
    • Licentiate's thesis in the Helsinki University of Technology
    • Vesanto, J. (2000). Using som in data mining. Licentiate's thesis in the Helsinki University of Technology.
    • (2000) Using Som in Data Mining
    • Vesanto, J.1
  • 29
    • 0036790884 scopus 로고    scopus 로고
    • Recursive self-organizing maps
    • Voegtlin, T. (2002). Recursive self-organizing maps. Neural Vetworks, 15(8-9):979-991.
    • (2002) Neural Vetworks , vol.15 , Issue.8-9 , pp. 979-991
    • Voegtlin, T.1
  • 31
    • 84944178665 scopus 로고
    • Hierarchical grouping to optimize an objective function
    • Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. J. Am. Statist. Assoc.
    • (1963) J. Am. Statist. Assoc.
    • Ward, J.H.1
  • 33
    • 33845236924 scopus 로고    scopus 로고
    • Unsupervised feature extraction for time series clustering using orthogonal wavelet transform
    • Zhang, H., Ho, T. B., Zhang, Y., and Lin, M.-S. (2006). Unsupervised feature extraction for time series clustering using orthogonal wavelet transform. Informatica.
    • (2006) Informatica
    • Zhang, H.1    Ho, T.B.2    Zhang, Y.3    Lin, M.-S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.