System and method for displaying and analyzing financial correlation data

• US 9,978,104 B2
• Filed: 06/25/2015
• Issued: 05/22/2018
• Est. Priority Date: 01/30/2013
• Status: Active Grant

• Current Assignee: The Capital Group Companies Incorporated (Morgan Stanley)
• Original Assignee: The Capital Group Companies Incorporated (Morgan Stanley)
• Inventors: Phoa, Wesley Kym-Son
• Primary Examiner(s): Ebersman, Bruce I
• Assistant Examiner(s): Gaw, Mark
• Application Number:
  US14/751,093
• Publication Number:
  US 20150294418A1
• Time in Patent Office: 1,062 Days
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06T 11/203 Drawing of straight lines or curves

Abstract

A method for displaying a matrix of correlations or other statistical measures of co-movement associated with a plurality of financial instruments, portfolios, indices, or asset classes is disclosed. The method includes: converting the matrix of correlations or other co-movement measures into a probability transition matrix; defining a corresponding abstract distance measurement between any two of the plurality of financial instruments, portfolios, indices, or asset classes based on the probability transition matrix; assigning coordinates in a Euclidean space to each of the plurality of financial instruments, portfolios, indices, or asset classes, wherein a Euclidean distance between any two financial instruments, portfolios, indices, or asset classes in the Euclidean space corresponds to the corresponding abstract distance measurement; and displaying on a display device the plurality of financial instruments, portfolios, indices, or asset classes based on more significant dimensions of the Euclidean space.

Claims

1. A method for displaying, on a display device, correlations between N financial instruments, each of the N financial instruments being represented via a graphical representation on the display device such that distances between the graphical representations correspond to the correlations, the method comprising:

identifying, by a computing device, correlation data of the N financial instruments, the correlation data being stored in an N×

N matrix of correlations;

remapping, by the computing device, the correlation data in the matrix of correlations for display in an M-dimensional Euclidean space, wherein N is larger than M, the remapping including;

generating, by the computing device, a probability transition matrix from the matrix of correlations;

defining, by the computing device, a corresponding abstract distance measurement between any two of the financial instruments based on the probability transition matrix; and

assigning, by the computing device, coordinates in the M-dimensional Euclidean space to each of the financial instruments corresponding to non-unit eigenvalues of the probability transition matrix, wherein a Euclidean distance between said any two of the financial instruments in the Euclidean space approximates the corresponding abstract distance measurement;

selecting, by the computing device, M most significant eigenvalues of the probability transition matrix;

rendering, by the computing device, on the display device, views of the graphical representations of the financial instruments based on particular dimensions of the Euclidean space corresponding to the selected M eigen values;

rotating, zooming, or panning, by an input controller coupled to the computing device, the views of the graphical representations of the financial instruments on the display device in response to a first corresponding user commands;

displaying, by the computing device, an identifying label for each of the financial instruments in the M-dimensional Euclidean space; and

adjusting by the computing device, an attribute of the identifying label to correspond to a respective value of an additional numerical characteristic being displayed in the M-dimensional Euclidean space.

2. The method of claim 1, wherein each of the correlations represented by the correlation data is derived from a standard correlation coefficient of a corresponding pair of the financial instruments.

3. The method of claim 2, wherein each of the correlations represented by the correlation data is one more than the standard correlation coefficient of the corresponding pair of the financial instruments.

4. The method of claim 1, wherein M is three.

5. The method of claim 4, wherein the selected M eigenvalues correspond to the three largest ones of the eigenvalues.

6. The method of claim 4, wherein the display device is a 2-D display device, the method further comprising displaying by the computing device the identifying label for each of the financial instruments, portfolios, indices, or asset classes in a 3-dimensional Euclidean representation on the 2-D display device.

7. The method of claim 6 further comprising displaying by the computing device on the 2-D display device successive representations of correlation data as observed on successive dates.

8. The method of claim 6 further comprising adjusting by the computing device a color or size of the identifying label to correspond to a respective value of the additional numerical characteristic being displayed in the 3-dimensional Euclidean representation on the 2-D display device for each of the financial instruments.

9. The method of claim 4, wherein N is equal or greater than 100.

10. The method of claim 4, wherein the computing device includes a graphics processor, wherein the rendering is executed by the graphics processor.

11. The method of claim 1, wherein M is two.

12. The method of claim 11, wherein the selected M eigenvalues correspond to the two largest ones of the eigenvalues.

13. The method of claim 1 further comprising generating by the computing device a measure of diversification of the financial instruments.

14. The method of claim 13, wherein the generating of the measure of diversification of the financial instruments comprises generating the measure of diversification using the particular dimensions of the Euclidean space.

15. The method of claim 13, wherein the measure of diversification comprises a global concentration, a relative global concentration, or a largest local concentration.

16. The method of claim 15, wherein the measure of diversification comprises a global concentration, wherein

generating of the global concentration comprises:

assigning by the computing device weight to each of the financial instruments; and

weighting by the computing device a contribution of each of the financial instruments by its respective said weight in the global concentration.

17. The method of claim 16 further comprising generating by the computing device a portfolio diversification measure by:

identifying by the computing device ones of the financial instruments;

assigning by the computing device second weights to respective said ones of the financial instruments; and

generating by the computing device the local concentration by only using the ones of the financial instruments in place of each of the financial instruments, and using the second weights in place of the weight of each of the financial instruments.

18. The method of claim 1 further comprising generating by the computing device a sequence of successively less significant local concentrations of the financial instruments.

19. The method of claim 1 further comprising generating by the computing device a plurality of relative local concentrations of the Euclidean space.

20. The method of claim 1 further comprising generating by the computing device a numerical summary measure of accuracy with which the Euclidean distance as measured in the particular dimensions of the Euclidean space approximates the corresponding abstract distance measurement.

21. The method of claim 1 further comprising changing by the computing device a sign of one of the coordinates for improving consistency of the displaying of the matrix of correlations of the financial instruments.

22. The method of claim 1 further comprising re-ordering by the computer processor the coordinates for improving consistency of the displaying of the correlations between the N financial instruments over a period of time.

23. The method of claim 1, wherein the financial instruments comprise publicly traded equity securities, publicly traded fixed income securities, publicly available mutual funds, exchange-traded funds, publicly traded currencies, exchange-traded futures, options on exchange-traded, futures, portfolios, indices, or asset classes.

24. The method of claim 1 further comprising:

in response to the displaying on the display device, receiving by the computing device a second user command to modify an attribute for a selected one of the financial instruments; and

modifying by the computing device the attribute in response to the second user command.

25. The method of claim 24, wherein the attribute corresponds to an investment amount.

26. The method of claim 1, wherein the correlations correspond to financial returns.

27. The method of claim 1, wherein the correlation data includes prices of the financial instruments.

28. The method of claim 1, wherein the correlation between two of the financial instruments, over a set period of time, is inversely proportional to the Euclidean distance between the two of the financial instruments.

29. The method of claim 1 further comprising:

identifying, by the computing device, a particular one of the financial instruments based on the rendering of the graphical representation of the particular one of the financial instruments;

including or excluding the particular one of the financial instrument from a portfolio of financial instruments; and

outputting the portfolio of financial instruments.

30. A system for displaying a correlations between N financial instruments, portfolios, indices, or asset classes, each of the N financial instruments, portfolios, indices, or asset classes being represented via a graphical representation on the display device such that distances between the graphical representations correspond to the correlations, the system comprising:

computing device;

a display device coupled to the computing device; and

a nonvolatile storage device coupled to the computing device and storing instructions that, when executed by the computing device, respectively cause the computing device to;

identify correlation data of the N financial instruments, the correlation data being stored in an N×

N matrix of correlations;

remap the correlation data in the matrix of correlations for display in an M-dimensional Euclidean space, wherein N is larger than M, the remapping including;

generate a probability transition matrix from the matrix of correlations;

define a corresponding abstract distance measurement between any two of the financial instruments based on the probability transition matrix; and

assign coordinates in the M-dimensional Euclidean space to each of the financial instruments corresponding to non-unit eigenvalues of the probability transition matrix, wherein a Euclidean distance between said any two of the financial instruments in the Euclidean space approximates the corresponding abstract distance measurement;

select M most significant eigenvalues of the probability transition matrix; and

render, on the display device, views of the financial instruments based on particular dimensions of the Euclidean space corresponding to the selected M eigenvalues;

an input controller coupled to the computing device, the input controller for rotating, zooming, or panning the views of the graphical representations of the financial instruments on the display device in response to a corresponding user command.

31. The system of claim 30, wherein M is three.

32. The system of claim 31, wherein the display device is a 2-D display device, wherein the instructions, when executed by the computing device, further cause the computing device to control the 2-D display device to display the identifying label for each of the financial instruments in a 3-dimensional Euclidean representation on the 2-D display device.

33. The system of claim 32, wherein the instructions further cause the computing device to respectively receive a second user command, and cause the computing device to modify the 3-dimensional Euclidean representation on the 2-D display device in response to the second user command.