System and method for multi-dimensional risk analysis

• US 7,756,896 B1
• Filed: 04/07/2005
• Issued: 07/13/2010
• Est. Priority Date: 03/11/2002
• Status: Active Grant

• Current Assignee: JP Morgan Chase Bank, N.A. (JP Morgan Chase & Co)
• Original Assignee: JP Morgan Chase Bank, N.A. (JP Morgan Chase & Co)
• Inventors: Feingold, Vincent
• Primary Examiner(s): Mofiz; Apu M
• Assistant Examiner(s): Bibbee; Jared M
• Application Number:
  US11/100,841
• Time in Patent Office: 1,923 Days
• Field of Search: 707/2, 707/705, 707/791
• US Class Current: 707/791
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

A risk analysis method uses a multi-dimensional risk representation that allows a standard OLAP engine to perform analysis on multi-dimensional data corresponding to a portfolio of financial positions. The analysis includes context-dependent, heterogeneous aggregation functions. The multi-dimensional data is represented as a multi-layered multi-dimensional cube (“outer” cube), which consists of dimensions and cells. Each cell includes a set of coordinates and an inner multi-dimensional cube (“inner” cube). Dimensions of the inner cube include all dimensions required for aggregations. Dimensions of the outer cube include only dimensions needed for context (or reporting). An aggregation is performed on the set of measures of the inner cube based on a context for the aggregation provided by the outer cube.

Claims

1. A method of representing a portfolio of financial positions on which a risk analysis is to be performed, comprising the steps of:

constructing an outer cube representing the portfolio of financial positions as a multi-layered multi-dimensional cube that includes cells and dimensions; and

constructing each cell of the plurality of cells to include a set of coordinates and an inner cube, wherein the inner cube is a multi-dimensional cube that includes cells and dimensions,

wherein the dimensions of the outer cube include information relating to a context of the risk analysis,

wherein the dimensions of the inner cube include all dimensions required to perform an aggregation operation on the portfolio of financial positions, and wherein, for each position P to be added to an inner-cube cell C,

P includes a measures object M_P and a set of coordinates S_P,

C includes a measures object M_C and a set of coordinates S_C,

for all k where k is an element of a set that includes 1 through n, and v_k is a value from a data hierarchy for the k^th dimension, a mapping operation for mapping coordinates and measures of P to C is given by;

C→

S_C→

v_k={P→

S_P→

v_k|“

−

”

}, set C→

M_C+=P→

M_P.

2. A method according to claim 1, wherein a dimension is removed from an inner-cube cell by projecting the dimension to be removed onto one or more other dimensions of the inner cube, such that:

for I^N={C^N}, in which I^N denotes an N-dimensional inner cube as a collection of N-dimensional cells C^N, I^N is projected onto an (N−

1)-dimensional cube (I^N-1_J), where a dimension J is removed, for each N-dimensional cell C^N that is an element of I^N, and for all k where k is an element of a set that includes 1 through n, with k≠

J, every cell C′

of I^N-1_J is found such that I^N-1_J→

C′

→

S_C→

v_k=I^N→

C→

S_C→

v_k, and a mapping operation is set in which I^N-1_J→

C′

→

M_C=f_J^OC,μ

(I^N-1_J→

C′

→

M_C, I^N→

C→

M_C), where f_J^OC,μ

( . . . ) is a J-dependent aggregation function.

3. A method according to claim 1, wherein, for a total projection of a dimension of an inner cube,

if I^Z_J denotes an inner cube in which a set of values for a J^th dimension is drawn from a level Z, and

if I^Z-1_J denotes an inner cube in which a set of values for the J^th dimension is drawn from a level Z−

1,

then, for each cell C that is an element of I^Z_J, a cell C′

of I^Z-1_J is found such that I^Z-1_J→

C′

→

M_C=f^Z_J^OC,μ

(I^Z-1_J→

C′

→

M_C, I^Z_J→

C→

M_C),

wherein a value I^Z-1_J→

C′

→

S_C→

v_J is a parent of a value I^Z_J→

C→

S_C→

v′

_J,

wherein f^Z_J^OC,μ

( . . .) is a J-dependent and Z-dependent aggregation function,

wherein OC refers to the outer cube, and

wherein μ

refers to an aggregation methodology.

4. A method according to claim 1, wherein, in a merge operation in which an inner cube I^N is merged with an inner cube I′

^N, for each cell C of the inner cube I^N and each cell C′

of the inner cube I′

^N, and for all k where k is an element of a set that includes 1 through n, the merge operation is performed according to;

I^N→

C→

S_C→

v_k=I′

^N→

C′

→

S_C→

v_k and I′

^N→

C′

→

M_C+=I^N→

C→

M_C.

5. A method of performing risk analysis on a portfolio of financial positions, comprising the steps of:

constructing an outer cube representing the portfolio of financial positions as a multi-layered multi-dimensional cube that includes cells and dimensions;

constructing each cell of the plurality of cells to include a set of coordinates and an inner cube, wherein the inner cube is a multi-dimensional cube that includes cells and dimensions,

wherein the dimensions of the outer cube include information relating to a context of the risk analysis,

wherein the dimensions of the inner cube include all dimensions required to perform an aggregation operation on the portfolio of financial positions,

wherein each cell of the inner cube includes a set of measures, which includes at least one scalar measure and at least one vector measure,

wherein, for each position P to be added to an inner-cube cell C,P includes a measures object M_P and a set of coordinates S_P, C includes a measures object M_C and a set of coordinates S_C, for all k where k is an element of a set that includes 1 through n, and v_k is a value from a data hierarchy for the k^th dimension, a mapping operation for mapping coordinates and measures of P to C is given by;

C→

S_C→

v_k={P→

S_P→

v_k|“

−

”

}, set C→

M_C+=P→

M_P; and

performing an aggregation operation on the set of measures according to the dimensions of the inner cube and according to the context of the risk analysis included in the dimensions of the outer cube.

6. A method according to claim 5, wherein a dimension is removed from an inner-cube cell by projecting the dimension to be removed onto one or more other dimensions of the inner cube, such that:

for I^N={C^N}, in which I^N denotes an N-dimensional inner cube as a collection of N-dimensional cells C^N, I^N is projected onto an (N−

1)-dimensional cube (I^N-1_J), where a dimension J is removed,

for each N-dimensional cell C^N that is an element of I^N, and for all k where k is an element of a set that includes 1 through n, with k≠

J, every cell C′

of I^N-1_J is found such that I^N-1_J→

C′

→

S_C→

v_k=I^N→

C→

S_C→

v_k, and a mapping operation is set in which I^N-1_J→

C′

→

M_C=f_J^OC,μ

(I^N-1_J→

C′

→

M_C, I^N→

C→

M_C), where f_J^OC,μ

( . . . ) is a J-dependent aggregation function.

7. A method according to claim 5, wherein, for a total projection of a dimension of an inner cube,

if I^Z_J denotes an inner cube in which a set of values for a J^th dimension is drawn from a level Z, and

if I^Z-1_J denotes an inner cube in which a set of values for the J^th dimension is drawn from a level Z−

1, then, for each cell C that is an element of I^Z_J, a cell C′

of I^Z-1_J is found such that I^Z-1_J→

C′

→

M_C=f^Z_J^OC,μ

(I^Z-1_J→

C′

→

M_C, I^Z_J→

C→

M_C),

wherein a value I^Z-1_J→

C′

→

S_C→

v_J is a parent of a value I^Z_J→

C→

S_C→

v′

_J,

wherein f^Z_J^OC,μ

( . . .) is a J-dependent and Z-dependent aggregation function,

wherein OC refers to the outer cube, and

wherein μ

refers to an aggregation methodology.

8. A method according to claim 5, wherein, in a merge operation in which an inner cube I^N is merged with an inner cube I′

^N, for each cell C of the inner cube I^N and each cell C′

of the inner cube I′

^N, and for all k where k is an element of a set that includes 1 through n, the merge operation is performed according to;

I^N→

C→

S_C→

v_k=I′

^N→

C′

→

S_C→

v_k and I′

^N→

C′

→

M_C+=I^N→

C→

M_C.