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http://dx.doi.org/10.7465/jkdi.2012.23.1.151

Multi-currencies portfolio strategy using principal component analysis and logistic regression  

Shim, Kyung-Sik (Department of Information and Industrial Engineering, Yonsei University)
Ahn, Jae-Joon (Department of Information and Industrial Engineering, Yonsei University)
Oh, Kyong-Joo (Department of Information and Industrial Engineering, Yonsei University)
Publication Information
Journal of the Korean Data and Information Science Society / v.23, no.1, 2012 , pp. 151-159 More about this Journal
Abstract
This paper proposes to develop multi-currencies portfolio strategy using principal component analysis (PCA) and logistic regression (LR) in foreign exchange market. While there is a great deal of literature about the analysis of exchange market, there is relatively little work on developing trading strategies in foreign exchange markets. There are two objectives in this paper. The first objective is to suggest portfolio allocation method by applying PCA. The other objective is to determine market timing which is the strategy of making buy or sell decision using LR. The results of this study show that proposed model is useful trading strategy in foreign exchange market and can be desirable solution which gives lots of investors an important investment information.
Keywords
Foreign exchange market; logistic regression; multi-currencies portfolio; principal component analysis;
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Times Cited By KSCI : 6  (Citation Analysis)
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1 White. (1989). Multilayer feedforward networks are universal a pproximators. Neural Networks, 2, 359-366.   DOI   ScienceOn
2 Zhang, G. Q. and Michael, Y. H. (1998). Neural network forecasting of the British pound/US dollar exchange rate. Omega, 26, 495-506.   DOI   ScienceOn
3 Fernando, F. R., Simon, S. R. and Julian, A. F. ( 1999). Exchange rate forecasts with simultaneous nearestneighbor methods: Evidence from the EMS. International Journal of Forecasting, 15, 383-392.   DOI   ScienceOn
4 Frankel, J. A. (1984). Tests of monetary and portfolio balance models of exchange rate determination. In Exchange rate theory and practice, edited by J. Bilson, R. Marston, University of Chicago Press, Chicago.
5 Gencay, R. (1999). Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules. Journal of International Economics, 47, 91-107.   DOI   ScienceOn
6 Huang, A. Y., Peng, S. P., Li, F. and Ke, C. J. (2011). Volatility forecasting of exchange rate by quantile regression. International Review of Economics and Finance, 20, 591-606.   DOI   ScienceOn
7 McCullagh, P. and Nelder, J. (1989). Generalized linear models, second edition, Chapman and Hall/CRC, Boca Raton.
8 Pai, P. F., Chen, S. Y., Huang, C. W. and Chang, Y. H. (2010). Analyzing foreign exchange rates by rough set theory and directed acyclic graph support vector machines. Expert Systems with Applications, 37, 5993-5998.   DOI   ScienceOn
9 Seemann, L., McCauley, J. L. and Gunaratne G. H. (2011). Intraday volatility and scaling in high frequency foreign exchange markets. International Review of Financial Analysis, 20, 121-126.   DOI   ScienceOn
10 Quinlan, J. R. (1986). Induction of decision tree. Machine Learning, 1, 81-106.
11 Song, G. M., Park, B. C. and Kang, H. K. (2007). A CUSUM algorithm for early detection of structural changes in won/dollar exchange m arket. Journal of the Korean Data & Information Science Society, 18, 345-356.
12 Tarumi, T., Tanaka, Y. and Shin, J. K. (1991). Sensitivity analysis in principal component regression. Journal of the Korean Data & Information Science Society, 2, 1-9.
13 강명욱, 김부용, 홍주희 (2010). 로지스틱모형에서 그래픽을 이용한 회귀와 모형평가. <한국데이터정보과학회지>, 21, 21-32
14 권세혁 (2010). 시뮬레이션 실험조건 이상 진단 연구. <한국데이터정보과학회지>, 21, 853-861
15 권오진, 김태윤, 송규문 (2010). 붓스트랩 기법을 이용한 환율의 장단기 신뢰구간 예측. <한국데이터정보과학회지>, 21, 493-502
16 김윤대, 전치혁, 이혜선 (2011). 벌점 부분최소자승법을 이용한 분류방법. <한국데이터정보과학회지>, 22, 931-940
17 김태윤, 권오진 (2011). 경제위기시 환율신뢰구간 예측 알고리즘 개발. <한국데이터정보과학회지>, 22, 895-902
18 변현우, 송치우, 한성권, 이태규, 오경주 (2009). 변동성 지수기반 유전자 알고리즘을 활용한 계층구조 포트폴리오 최적화에 관한 연구. <한국데이터정보과학회지>, 20, 467-478.
19 Beran, J. and Ocker, D. (1999). SEMIFAR forecasts, with applications to foreign exchange rates. Journal of Statistical Planning and Inference, 80, 137-153.   DOI   ScienceOn
20 Bahmani-Oskooee, M. and Harvey, H. (2011). Exchange-rate volatility and industry trade between the U.S. and Malaysia. Research in International Business and Finance, 25, 127-155.   DOI   ScienceOn
21 Breiman, L., Friedman, J. H., Olshen, R. A. and Stone, C. J. (1984). Classification and regression trees, Wadsworth Intl Group, Belmont.
22 Cherkassky, V. and Mulier, F. (1998). Learning from data : Concepts, theory and methods. Wiley, New York.
23 Cushman, D. O. (2007). A portfolio balance approach to the Canadian-U.S. exchange rate. Review of Financial Economics, 16, 305-320.   DOI   ScienceOn