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Systems and methods for multi-objective portfolio analysis using pareto sorting evolutionary algorithms

  • US 8,219,477 B2
  • Filed: 02/20/2004
  • Issued: 07/10/2012
  • Est. Priority Date: 02/20/2004
  • Status: Active Grant
First Claim
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1. A method for multi-objective portfolio analysis using Pareto Sorting Evolutionary Algorithms, the method comprising the steps of:

  • (a) randomly drawing an initial population of individual portfolio allocations that are generated from a portfolio allocations archive by using a combination of linear programming and sequential linear programming algorithms using a processor of a computing device;

    (b) passing the initial population of portfolio allocations through a dominance filter to identify a non-dominated subset of parent portfolio allocations using the processor of the computing device;

    (c) committing the non-dominated subset of parent portfolio allocations to a non-dominated portfolio allocations archive using the processor of the computing device;

    (d) randomly combining matched pairs of parent portfolio allocations to create offspring portfolio allocations using the processor of the computing device;

    (e) passing the offspring portfolio allocations through the dominance filter to identify a non-dominated subset of offspring portfolio allocations using the processor of the computing device;

    (f) combining the non-dominated subset of parent portfolio allocations with the non-dominated subset of offspring portfolio allocations into a larger set of portfolio allocations using the processor of the computing device;

    (g) passing the larger set of portfolio allocations through a non-crowding filter to identify a reduced subset of portfolio allocations using the processor of the computing device;

    (h) creating a new population of individual portfolio allocations from the reduced subset of portfolio allocations using the processor of the computing device;

    (i) updating the non-dominated portfolio allocations archive with the new population of individual portfolio allocations using the processor of the computing device;

    (j) repeating steps (a) through (i) for a plurality of generations using the processor of the computing device; and

    (k) passing the updated non-dominated portfolio allocations archive through the dominance filter to generate an interim efficient frontier in a portfolio performance space having at least three-dimensions using the processor of the computing device, the interim efficient frontier being used in investment decisions.

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