Abstract
This paper presents a novel use of SQL language to solve a practical optimization problem to find the portfolio size and the quantity of money for securities. This problem is known as the Portfolio Selection Problem (PSP). The approach was tested on 9 random instances of PSP. Each instance has up to 12 securities and 50 different choices of money. Each security follows a non-linear profit model. The limitations of our approach are bounded by the computer resources, given that potentially SQL constructs the Cartesian product of the investment options, but it has the advantages of not requiring complex structures and it is easy to understand.
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References
Bienstock, D.: Computational study of a family of mixed-integer quadratic programming problems. Mathematical Programming: Series A and B 74(2), 121–140 (1996)
Campbell, J., et al.: The Econometrics of Financial Markets. Princeton University Press, Princeton (1997)
Chang, T.J., Meade, N., Beasley, J.E., Sharaiha, Y.M., Stanley, M., Witter, D.: Heuristics for Cardinality Constrained Portfolio Optimisation. Computers and Operations Research 27, 1271–1302 (1998)
Codd, E.F.: A relational model of data for large shared data banks. ACM Commun. 13(6), 377–387 (1970)
Codd, E.F.: Further Normalization of the Data Base Relational Model. IBM Research Report, San Jose, California, FJ909 (1971)
Coutino-Gomez, C.A., Torres-Jimenez, J., Villarreal-Antelo, B.M.: Heuristic Methods for Portfolio Selection at the Mexican Stock Exchange. In: Liu, J., Cheung, Y.-m., Yin, H. (eds.) IDEAL 2003. LNCS, vol. 2690, pp. 919–923. Springer, Heidelberg (2003)
Dong, J., Du, H.S., Wang, S., Chen, K., Deng, X.: A framework of Web-based Decision Support Systems for portfolio selection with OLAP and PVM. Decision Support Systems 37(3), 367–376 (2004)
Friedman, J.: A computer system for transformational grammar. ACM Commun. 12(6), 341–348 (1969)
Ghasemzadeh, G., Archer, N.P.: Project portfolio selection through decision support. Decision Support Systems 29(1), 73–88 (2000)
Hiroshi, K., Ken-ichi, S.: A mean variance-skewness portfolio optimization model. Journal of the Operations Research Society of Japan 2(37), 173–187 (1995)
Konno, H., Yamazaki, H.: Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market. Management Science 37(5), 519–531 (1991)
Mancini, T., Flener, P., Hossein Monshi, A., Pearson, J.: Constrained optimisation over massive databases. In: Proceedings of RCRA 2009, the 16th RCRA International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, vol. 589 (2009)
Mansini, R., Speranza, M.G.: Heuristic algorithms for the portfolio selection problem with minimum transaction lots. European Journal of Operational Research 114(2), 219–233 (1999)
Markowitz, H.: Portfolio Selection. The Journal of Finance 7(1), 77–91 (1952)
Markowitz, H., Todd, P., Xu, G., Yamane, Y.: Computation of mean-semivariance efficient sets by the Critical Line Algorithm. Annals of Operations Research 45(1-4), 307–317 (1993)
Rolland, E.: A tabu search method for constrained real-number search: Applications to portfolio selection. Technical report, Department of Accounting and Management Information Systems, Ohio State University, Columbus (1997)
Schaerf, A.: Local Search Techniques for Constrained Portfolio Selection Problems. CoRR, cs.CE/0104017 (2001)
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Torres-Jimenez, J., Avila-George, H., Rangel-Valdez, N., Martinez-Pena, J. (2010). Optimization of Investment Options Using SQL. In: Kuri-Morales, A., Simari, G.R. (eds) Advances in Artificial Intelligence – IBERAMIA 2010. IBERAMIA 2010. Lecture Notes in Computer Science(), vol 6433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16952-6_4
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DOI: https://doi.org/10.1007/978-3-642-16952-6_4
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