System and method for tax sensitive portfolio optimization

• US 7,016,873 B1
• Filed: 09/05/2000
• Issued: 03/21/2006
• Est. Priority Date: 03/02/2000
• Status: Expired due to Term

• Current Assignee: Charles Schwab Trust Company (Charles Schwab Corporation)
• Original Assignee: Charles Schwab & Company Incorporated (Charles Schwab Corporation)
• Inventors: Peterson, James, Pietranico, Paul-Charles A., Kleinbauer, Christopher, McDonald, Bill D.
• Primary Examiner(s): Colbert, Ella
• Application Number:
  US09/654,627
• Time in Patent Office: 2,023 Days
• Field of Search: 705 35- 37, 902/41
• US Class Current: 705/36.00R
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A method and apparatus are provided which account for tax impact in predicting investment return. Data for taxable investments, data for non-taxable investments and investor data are received and an optimization is performed which includes all of these data. An investment recommendation is provided to the investor based on the optimization.

Claims

1. In a computer system a method for characterizing an investment portfolio, comprising the steps of:

identifying a group of possible investments to be held in the investment portfolio, and wherein the group of possible investments includes a plurality of mutual funds, and one or more of the plurality of mutual finds having a corresponding investment minimum;

inputting data for taxable investments;

inputting data for non-taxable investments;

inputting investor profile information;

providing a processor programmed to perform an iterative routine that provides an optimization which utilizes the data for the taxable investments, the data for the non-taxable investments and the investor profile information and accounts for capital gains or losses on taxable investments which would be sold;

wherein the iterative routine provides an investment recommendation which includes a recommended weighting for each investment held in the investment portfolio;

wherein the processor is further programmed to output the investment recommendation;

wherein the iterative routine performed by the processor includes an optimization routine, and the iterative routine includes a first step, a second step, and a third step, and the three steps are executed automatically, without any user interaction;

wherein the first step provides for running the optimization routine using different sets of predetermined initial weights for each of the possible investments, in an attempt to identify an optimal solution which provides an optimum weight for each investment of the group of the possible investments to be held in the portfolio;

wherein when the first step does not provide an optimal solution with any of the predefined different sets of initial weights, the second step is performed, wherein the second step includes;

identifying a result from the first step, which provides a weighting for each investment of the group of the possible investments, and provides that at least one of the possible investments has a weighting of zero; and

using the result from the first step as a starting point and then re-running the optimization routine, using only those investments with non-zero weights from the result of the first step, to identify the optimal solution providing an optimum weight for each investment of the group of possible investments to be held in the portfolio; and

wherein after the optimal solution is found using the first step or the second step, performing a third step of re-running the optimization routine to account for a minimum investment value which corresponds to a mutual fund to be held in the portfolio.

2. The method of claim 1, further including:

wherein during the first step of the iterative routine the processor is programmed to use three sets of predetermined initial weights for each of the possible investments;

wherein during the first step the optimization routine is initially run with a first set of the predetermined initial weights, and if an optimal solution is reached using the first set of predetermined weights, then the first step of the iterative routine is terminated prior to running the optimization routine with a second set of predetermined weights, and a third set of predetermined weights.

3. The method of claim 2, wherein when an optimal solution is found during the first step, the third step operates to set a lower limit for a first investment from the optimal solution at an investment minimum which corresponds to a minimum investment amount for the first investment, and then to rerun the optimization routine to provide a first solution which accounts for minimum investment amounts.

4. The method of claim 3, wherein when an optimal solution is found during the first step, the third step operates hold certain investments in the optimal solution at zero, and to rerun the optimization routine to provide a second solution which accounts for minimum investment amounts.

5. The method of claim 4, wherein the third step further includes selecting between the first solution and the second solution to provide the investment recommendation.

6. The method of claim 1 further including:

wherein the identifying a group of possible investments to be held in an investment portfolio includes excluding investments with an investment minimum amount of at least $3,000 from the group of possible investments.