Patent Document ID: 20110125673
Application ID: 13011411
Patent Flag: 0

Claim One:
1. A computer-implemented method for generating an integrated market and credit loss distribution for the purpose of calculating one or more risk measures associated with a portfolio of instruments by performing a simulation, wherein acts of said method are performed by computer, said computer comprising at least one computer processor and at least one memory, said method comprising: identifying, by the at least one computer processor, at least a first time horizon for said simulation; receiving, by the at least one computer processor, data identifying X, wherein X is a vector of scalar-valued market risk factor processes, each market risk factor process defined by a start value, at least one function representing a model, and zero or more parameters for the model; receiving, by the at least one computer processor, data identifying Y, wherein Y is a vector of scalar-valued credit driver processes, each credit driver process defined by a start value, at least one function representing a model, and zero or more parameters for the model; receiving, by the at least one computer processor, data comprising one or more co-variance matrices that define the joint evolution of X and Y over said first time horizon; identifying, by the at least one computer processor, a first parameter M, wherein M>0, and a second parameter S, wherein S>1; wherein M defines a desired number of market risk factor samples and S defines a desired number of systemic credit driver samples for each of M market risk factor samples; the at least one computer processor generating MS conditional loss distributions for said first time horizon to compute an unconditional loss distribution {circumflex over (F)} for said first time horizon by performing acts comprising: the at least one computer processor generating MS scenarios, said MS scenarios defined by MS sets of X and Y values (X m ,Y ms ) for all m from 1 to M, and for all s from 1 to S; wherein said act of the at least one computer processor generating MS scenarios comprises: for each m from 1 to M, generating a sample, having index m, of a vector of normal random variables represented by Ξ; for each m from 1 to M and for each s from 1 to S, generating a random sample, having index ms, of ΔY from a conditional distribution of ΔY derived from the sample of the vector Ξ having index m and from at least one of the one or more co-variance matrices, ΔY being an increment of Y; computing said MS sets of X and Y values (X m ,Y ms ) for all m from 1 to M, and for all s from 1 to S, wherein X m is calculated as a value of X at the first time horizon based on a previous value of X m , the at least one function associated with X, and the sample having index m of the vector Ξ, and wherein Y ms is calculated as a value of Y at the first time horizon based on a previous value of Y ms , the at least one function associated with Y, and the random sample having index ms of ΔY, and wherein if said first time horizon comprises exactly one time step, said previous value of X m and Y ms is the start value associated with X and Y respectively, for all m from 1 to M, and for all s from 1 to S; for each of the MS scenarios defined by MS sets of X and Y values (X m ,Y ms ) for all m from 1 to M, and for all s from 1 to S, analytically deriving a conditional loss distribution F X m Y ms to generate said MS conditional loss distributions for said first time horizon; and producing the unconditional loss distribution {circumflex over (F)} for said first time horizon as a mixture of the MS conditional loss distributions for said first time horizon; and providing, by the at least one computer processor, the unconditional loss distribution {circumflex over (F)} for said first time horizon for calculating one or more risk measures from said unconditional loss distribution {circumflex over (F)}, said one or more risk measures for use in evaluating risk associated with said portfolio.