SYSTEM AND METHOD FOR RISK MANAGEMENT AND PORTFOLIO OPTIMIZATION

• US 20140317019A1
• Filed: 03/14/2014
• Published: 10/23/2014
• Est. Priority Date: 03/14/2013
• Status: Abandoned Application

• Current Assignee: Jochen Papenbrock, Peter Schwendner
• Original Assignee: Jochen Papenbrock, Peter Schwendner
• Inventors: Papenbrock, Jochen, Schwendner, Peter
• Application Number:
  US14/213,986
• Publication Number:
  US 20140317019A1
• Time in Patent Office: Days
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A processor-based analytical system accesses financial data for a group of assets over a plurality of time periods and identifies relationship characteristics for the financial data during those time periods. The system compares the relationship characteristics to compute pair-wise similarity measures, which are used to group different time periods into states. The system also accesses information identifying an investment portfolio, such as information identifying particular assets in that portfolio as well as the weightings of those assets in the portfolio. The system evaluates the performance of the portfolio in the states. The system alters the investment portfolio by altering the weightings of the assets in the investment portfolio in order to achieve a predetermined investment goal.

Claims

1. A processor-based system for portfolio management, the system comprising:

a first tangible, non-transitory storage medium adapted to store sets of time series of financial data for a predefined group of investment assets, the sets of time series spanning a set of predefined time periods;

a second tangible, non-transitory storage medium adapted to store information identifying assets in an investment portfolio;

one or more processors operatively coupled to the first tangible, non-transitory storage medium to access the sets of time series of financial data and to the second tangible, non-transitory storage medium to access the information identifying assets in the investment portfolio, the one or more processors being adapted to;

compute a plurality of relationship characteristics with respect to the financial data for the predefined group of investment assets, with each relationship characteristic of the plurality of relationship characteristics corresponding to a time period of the plurality of predefined time periods;

compute pair-wise similarity measures between each of the relationship characteristics;

determine groupings of similar relationship characteristics using the pair-wise similarity measures in order to define a plurality of states; and

evaluate the investment portfolio in at least one of the plurality of states by computing a performance measure based on the financial data time series for each asset in the investment portfolio in the at least one state of the plurality of states.

2. The processor-based system of claim 1, wherein the one or more processors are further adapted to modify weightings of the assets in the investment portfolio based on the evaluated performance of the investment portfolio in the at least one state of the plurality of states.

3. The processor-based system of claim 2, wherein the one or more processors are further adapted to identify an state of the plurality of states in which a performance measure of the investment portfolio in that state is worse than a predefined threshold, and wherein the one or more processors are further adapted to modify weightings of the assets of the investment portfolio in order to improve the performance of the investment portfolio for that state.

4. The processor-based system of claim 3, further comprising a display, wherein the one or more processors are adapted to convey the modified weightings of the assets of the investment portfolio using the display.

5. The processor-based system of claim 1, further comprising a display, wherein the one or more processors are adapted to convey the performance measure in the at least one state using the display.

6. The processor-based system of claim 1, wherein the one or more processors are further adapted to rank each state of the plurality of states according to the performance measure for the investment portfolio in each state.

7. The processor-based system of claim 1, wherein the one or more processors are further adapted to compute a transition probability for transitions between each state of the plurality of states.

8. The processor-based system of claim 7, wherein the one or more processors are further adapted to modify weightings of the assets of the investment portfolio based on the transition probabilities.

9. The processor-based system of claim 1, wherein the assets of the investment portfolio consist essentially of assets of the predefined group of assets.

10. The processor-based system of claim 1, wherein the one or more processors are further adapted to construct, for at least one state of the plurality of states, a network model of assets in the at least one state, the network model comprising:

a plurality of nodes, each of the nodes representing one asset;

a plurality of edges, each edge linking two nodes of the plurality of nodes and representing a relationship value for the assets of the nodes linked by the edge in the at least one state, wherein the relationship values represented by the plurality of edges correspond to a representative relationship matrix for the assets in the at least one state.

11. The processor-based system of claim 10, further comprising a display, wherein the one or more processors are adapted to convey a graphical representation of the network model of the assets in the at least one state using the display.

12. The processor-based system of claim 10, wherein the one or more processors are further adapted to determine a function of at least one asset within the network model and to change a weighting of the at least one asset in a portfolio based on the function of the at least one asset within the network model.

13. The processor-based system of claim 1, wherein the one or more processors are further adapted to construct, for at least one state of the plurality of states, a hierarchical or partitional cluster model for assets in the at least one state, wherein constructing the hierarchical or partitional cluster model includes grouping the assets into overlapping or non-overlapping clusters based on a transformation of a representative relationship matrix for the assets in the at least one state

14. The processor-based system of claim 13, further comprising a display, wherein the one or more processors are adapted to convey a graphical representation of the cluster model for the assets in the at least one state using the display.

15. The processor-based system of claim 13, wherein the one or more processors are further adapted to determine a function of at least one asset within the cluster model and to change a weighting of the at least one asset in a portfolio based on the function of the at least one asset within the cluster model.

16. A method for risk management for an investment portfolio that includes assets selected from investment markets, the method comprising:

creating, using one or more processors operatively coupled to a tangible, non-transitory medium in which financial data for assets in investment markets are stored, a plurality of states that each comprise discontinuous time segments in which financial data for these assets exhibit similar relationship characteristics as determined by a clustering algorithm;

evaluating, using the one or more processors, a performance characteristic for the investment portfolio in at least one of the states using the financial data stored in the tangible, non-transitory medium; and

modifying, using the one or more processors, the investment portfolio in order to improve the performance characteristics for the investment portfolio in at least one of the states.

17. The method of claim 16, the method further comprising:

creating a correlation matrix for each of the plurality of states;

creating, using the one or more processors, a new correlation matrix for the assets in the investment markets over an additional time segment; and

determining, using the one or more processors, similarity measures between the new correlation matrix and each of the correlation matrices for the states of the plurality of states.

18. The method of claim 17, the method further comprising a step of merging the new correlation matrix and the correlation matrix for a particular state.

19. The method of claim 17, the method further comprising a step of establishing a new state that includes the new correlation matrix.

20. The method of claim 19, further comprising:

evaluating, using the one or more processors, a performance characteristic for the investment portfolio in each state of the plurality of states, including the new state; and

modifying, using the one or more processors, the investment portfolio in order to improve performance characteristics of the investment portfolio in each state of the plurality of states.

21. The method of claim 16, further comprising:

computing, using the one or more processors, transition probabilities between each of the states in of the plurality of states;

identifying a particular state of the plurality of states whose time segments include a current time segment; and

forecasting a probability of a transition from the particular state of the plurality of states to a different state of the plurality of states.

22. The method of claim 21, wherein forecasting the probability of the transition from the particular state of the plurality of states to the different state of the plurality of states includes creating a probability table identifying a probability of a transition from the particular state to each of the remaining states of the plurality of states.

23. The method of claim 22, further comprising a step of displaying the probability table in conjunction with the performance of the investment portfolio for each state of the plurality of states.

24. A computer-implemented method for improving performance of an investment portfolio, the method comprising:

using one or more processors to access financial data for a selected group of assets in an investment market, the financial data being stored in a tangible, non-transitory storage medium;

identifying discrete time segments in which the financial data for the selected group of assets in the investment market have similar correlation characteristics;

grouping the discrete time segments to create states;

creating a correlation matrix for each state using the financial data for the selected group of assets;

identifying assets of the investment market pertaining to an investment portfolio;

analyzing, for at least one state, the financial data for the assets of the investment portfolio during the discrete time segments forming the at least one state to create performance information for the investment portfolio specific to the at least one state.

25. The computer-implemented method of claim 24, further comprising:

analyzing, for at least two states, the financial data for the assets of the investment portfolio during the discrete time segments forming each to create performance information for the investment portfolio specific to each state;

comparing the performance information for the investment portfolio specific to the at least two states to identify at least one state in which the performance information for the investment portfolio is incongruous with at least one predetermined investment goal.

26. The computer-implemented method of claim 24, further comprising a step of modifying the investment portfolio so that the performance information for the at least one state is congruous with at least one predetermined investment goal.

27. The computer-implemented method of claim 24, further comprising a step of modifying the investment portfolio so that the performance information for the portfolio in the at least one state is within a predefined range.