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SHAREX: A MULTIPERIOD PORTFOLIO MANAGEMENT MODEL

SHAREX: A MULTIPERIOD PORTFOLIO MANAGEMENT MODEL. Key Features. Integrated system of: stock price forecasting portfolio optimization inventory management facilities for incorporating alternative techniques. Key Features:. t he necessary financial relations included

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SHAREX: A MULTIPERIOD PORTFOLIO MANAGEMENT MODEL

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  1. SHAREX: A MULTIPERIOD PORTFOLIO MANAGEMENT MODEL

  2. Key Features Integrated system of: • stock price forecasting • portfolio optimization • inventory management • facilities for incorporating alternative techniques

  3. Key Features: • the necessary financial relations included • liquidity and debt, inventory, risk control • transactions in discrete batch sizes • fixed and variable transactions costs • free specification of planning horizon • forecasting and optimization combined • extensive simulations for strategy specification • real time management • guaranteed feasibility

  4. Large Scale Portfolio Management

  5. Immediate research Topics: • parametric search under different economic conditions • mixture density forecast models for skewed markets • multicomputer implementation of SHAREX • connections to efficient MINLP-solvers • Utilizing VMA and IMA (volume/price index moving averages) in turning point detection

  6. Östermark, R. (1990): Portfolio Efficiency of Capital Asset Pricing Models. Empirical Evidence on Thin Stock Markets. Åbo Akademi University, ISBN 951-649-703-9. Östermark, R. (1991): Vector forecasting and dynamic portfolio selection. European Journal of Operational Research 55, 46-56. Östermark, R & Aaltonen J (1992): Recursive Portfolio Management: Large-Scale Evidence from Two Scandinavian Stock Markets. Computer Science in Economics and Management 5, 81-103. Östermark, R (2000a): A Hybrid Genetic Fuzzy Neural Network Algorithm Designed for Classification Problems Involving Several Groups. Fuzzy Sets and Systems114:2, pp. 311-324. Östermark, R. (2000b) A Flexible Genetic Hybrid Algorithm for Nonlinear Mixed-integer Programming Problems. Accepted in EvolutionaryOptimization. Background Research

  7. Research (cont) Östermark, R., Westerlund, T. & Skrifvars, H. (2000): A Nonlinear Mixed-Integer Multiperiod Firm Model. International Journal of Production Economics 67, p. 188-199. Östermark, R. (2001): “Genetic modelling of multivariate EGARCHX-processes. Evidence on the international asset return signal response mechanism”. Forthcoming in Computational Statistics & Data Analysis38/1, 2001, pp. 1-124. Östermark, R. (2002a): “Automatic detection of parsimony in heteroskedastic time series processes. Empirical tests on global asset returns with parallel geno-mathematical programming”. Soft Computing6/1, pp. 45-63. Östermark, R. (2002b): “A Multipurpose Parallel Genetic Hybrid Algorithm for Nonlinear Non-convex Programming Problems”. Forthcoming in The European Journal of Operational Research.

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