#include #include #include #include #define MIN(x, y) (((x) < (y)) ? (x) : (y)) extern int dgemv_(char* trans, int *m, int *n, double* alpha, double* A, int* lda, double* x, int* incx, double* beta, double* y, int* incy); extern double ddot_(int* n, double* dx, int* incx, double* dy, int* incy); extern int daxpy_(int* n, double* da, double* dx, int* incx, double* dy, int* incy); void lossdistrib(double *p, int *np, double *w, double *S, int *N, int *defaultflag, double *q); double shockprob(double p, double rho, double Z, int give_log); void lossdistrib_Z(double *p, int *np, double *w, double *S, int *N, int *defaultflag, double *rho, double *Z, double *wZ, int *nZ, double *q); void lossdistrib_truncated(double *p, int *np, double *w, double *S, int *N, int *T, int *defaultflag, double *q); void lossdistrib_joint( double *p, int *np, double *w, double *S, int *N, int *defaultflag, double *q); void recovdist(double *dp, double *pp, int *n, double *w, double *S, int *N, double *q); void lossdistrib_prepay_joint(double *dp, double *pp, int *ndp, double *w, double *S, int *N, int *defaultflag, double *q); double dqnorm(double x); double dshockprob(double p, double rho, double Z); void shockprobvec2(double p, double rho, double* Z, int nZ, double *q); double shockseverity(double S, double Z, double rho, double p); void fitprob(double* Z, double* w, int* nZ, double* rho, double* p0, double* result); void stochasticrecov(double* R, double* Rtilde, double* Z, double* w, int* nZ, double* rho, double* porig, double* pmod, double* q); void lossdistrib_prepay_joint_Z(double *dp, double *pp, int *ndp, double *w, double *S, int *N, int *defaultflag, double *rho, double *Z, double *wZ, int *nZ, double *q); void lossdistrib_joint_Z(double *dp, int *ndp, double *w, double *S, int *N, int *defaultflag, double *rho, double *Z, double *wZ, int *nZ, double *q); void BClossdist(double *SurvProb, int *dim1, int *dim2, double *issuerweights, double *recov, double *Z, double *w, int *n, double *rho, int *N, int *defaultflag, double *L, double *R); void lossdistrib(double *p, int *np, double *w, double *S, int *N, int *defaultflag, double *q) { /* recursive algorithm with first order correction for computing the loss distribution. p vector of default probabilities np length of p S vector of severities (should be same length as p) N number of ticks in the grid defaultflat if true compute the default distribution q the loss distribution */ int i, j, d1, d2, M; double lu, d, p1, p2, sum; double *qtemp; lu = 1./(*N-1); qtemp = Calloc(*N, double); q[0] = 1; M = 1; for(i=0; i<(*np); i++){ d = (*defaultflag)? w[i]/lu : S[i] * w[i]/ lu; d1 = floor(d); d2 = ceil(d); p1 = p[i] * (d2-d); p2 = p[i] - p1; memcpy(qtemp, q, MIN(M, *N) * sizeof(double)); for(j=0; j < MIN(M, *N); j++){ q[j] = (1-p[i]) * q[j]; } for(j=0; j < MIN(M, *N-d2); j++){ q[d1+j] += p1 * qtemp[j]; q[d2+j] += p2 * qtemp[j]; }; M+=d2; } /* correction for weight loss */ if(M>*N){ sum = 0; for(j=0; j*N || My>*N){ sum = 0; for(m=0; m < MIN(Mx, *N); m++){ for(n=0; n < MIN(My, *N); n++){ sum += q[m+n*(*N)]; } } q[MIN(*N, Mx)*MIN(My,*N)-1] += 1 - sum; } Free(qtemp); } void recovdist(double *dp, double *pp, int *n, double *w, double *S, int *N, double *q) { /* recursive algorithm with first order correction for computing the recovery distribution in case of prepayment. dp vector of default probabilities pp vector of prepay probabilities n length of p S vector of severities (should be same length as p) w vector of weights N number of ticks in the grid q the loss distribution */ int i, j, d1l, d1u, d2l, d2u; int M; double lu, d1, d2, dp1, dp2, pp1, pp2, sum; double *qtemp; lu = 1./(*N - 1); qtemp = Calloc( (*N), double); q[0] = 1; M=1; for(i=0; i<(*n); i++){ d1 = w[i] * (1-S[i]) /lu; d2 = w[i]/lu; d1l = floor(d1); d1u = d1l + 1; d2l = floor(d2); d2u = d2l + 1; dp1 = dp[i] * (d1u - d1); dp2 = dp[i] - dp1; pp1 = pp[i] * (d2u - d2); pp2 = pp[i] - pp1; memcpy(qtemp, q, MIN(M, *N) * sizeof(double)); for(j = 0; j< MIN(M, *N); j++){ q[j] = (1-dp[i]-pp[i]) * q[j]; } for(j=0; j < MIN(M, *N-d2u); j++){ q[d1l+j] += dp1 * qtemp[j]; q[d1u+j] += dp2 * qtemp[j]; q[d2l+j] += pp1 * qtemp[j]; q[d2u+j] += pp2 * qtemp[j]; }; M += d2u; } /* correction for weight loss */ if(M>*N){ sum = 0; for(j=0; j*N || My>*N){ sum = 0; for(m=0; m < MIN(Mx, *N); m++){ for(n=0; n < MIN(My, *N); n++){ sum += q[m+n*(*N)]; } } q[MIN(*N, Mx)*MIN(My,*N)-1] += 1 - sum; } Free(qtemp); } double shockprob(double p, double rho, double Z, int give_log){ return( pnorm( (qnorm(p, 0, 1, 1, 0) - sqrt(rho) * Z)/sqrt(1 - rho), 0, 1, 1, give_log)); } double dqnorm(double x){ return 1/dnorm(qnorm(x, 0, 1, 1, 0), 0, 1, 0); } double dshockprob(double p, double rho, double Z){ return( dnorm((qnorm(p, 0, 1, 1, 0) - sqrt(rho) * Z)/sqrt(1-rho), 0, 1, 0) * dqnorm(p)/sqrt(1-rho) ); } void shockprobvec2(double p, double rho, double* Z, int nZ, double *q){ /* return a two column vectors with shockprob in the first column and dshockprob in the second column*/ int i; #pragma omp parallel for for(i = 0; i < nZ; i++){ q[i] = shockprob(p, rho, Z[i], 0); q[i + nZ] = dshockprob(p, rho, Z[i]); } } double shockseverity(double S, double Z, double rho, double p){ return( exp(shockprob(S * p, rho, Z, 1) - shockprob(p, rho, Z, 1)) ); } /* void addandmultiply(double *X, double alpha, double *Y, int n) { */ /* int i; */ /* for(i = 0; i eps){ phi = 1; while( (p - phi * dp) < 0 || (p - phi * dp) > 1){ phi *= 0.8; } p -= phi * dp; shockprobvec2(p, *rho, Z, *nZ, q); dp = (ddot_(nZ, q, &one, w, &one) - *p0)/ddot_(nZ, q + *nZ, &one, w, &one); } *result = p; } free(q); } void stochasticrecov(double* R, double* Rtilde, double* Z, double* w, int* nZ, double* rho, double* porig, double* pmod, double* q){ double ptemp, ptilde; int i; if(*porig==0){ for(i = 0; i < *nZ; i++){ q[i] = *R; } }else{ ptemp = (1 - *R) / (1 - *Rtilde) * *porig; fitprob(Z, w, nZ, rho, &ptemp, &ptilde); #pragma omp parallel for for(i = 0; i < *nZ; i++){ q[i] = fabs(1 - (1 - *Rtilde) * exp( shockprob(ptilde, *rho, Z[i], 1) - shockprob(*pmod, *rho, Z[i], 1))); } } } void lossdistrib_prepay_joint_Z(double *dp, double *pp, int *ndp, double *w, double *S, int *N, int *defaultflag, double *rho, double *Z, double *wZ, int *nZ, double *q) { int i, j; double* dpshocked = malloc(sizeof(double) * (*ndp) * (*nZ)); double* ppshocked = malloc(sizeof(double) * (*ndp) * (*nZ)); int N2 = (*N) * (*N); double* qmat = malloc(sizeof(double) * N2 * (*nZ)); double alpha = 1; double beta = 0; int one = 1; #pragma omp parallel for private(j) for(i = 0; i < *nZ; i++){ for(j = 0; j < *ndp; j++){ dpshocked[j + (*ndp) * i] = shockprob(dp[j], *rho, Z[i], 0); ppshocked[j + (*ndp) * i] = shockprob(pp[j], *rho, -Z[i], 0); } lossdistrib_prepay_joint(dpshocked + (*ndp) * i, ppshocked + (*ndp) * i, ndp, w, S + (*ndp) * i, N, defaultflag, qmat + N2 * i); } dgemv_("n", &N2, nZ, &alpha, qmat, &N2, wZ, &one, &beta, q, &one); free(dpshocked); free(ppshocked); free(qmat); } void lossdistrib_joint_Z(double *dp, int *ndp, double *w, double *S, int *N, int *defaultflag, double *rho, double *Z, double *wZ, int *nZ, double *q) { int i, j; double* dpshocked = malloc(sizeof(double) * (*ndp) * (*nZ)); int N2 = (*N) * (*N); double* qmat = malloc(sizeof(double) * N2 * (*nZ)); double alpha = 1; double beta = 0; int one = 1; #pragma omp parallel for private(j) for(i = 0; i < *nZ; i++){ for(j = 0; j < *ndp; j++){ dpshocked[j + (*ndp) * i] = shockprob(dp[j], *rho, Z[i], 0); } lossdistrib_joint(dpshocked + (*ndp) * i, ndp, w, S + (*ndp) * i, N, defaultflag, qmat + N2 * i); } dgemv_("n", &N2, nZ, &alpha, qmat, &N2, wZ, &one, &beta, q, &one); free(dpshocked); free(qmat); } void BClossdist(double *SurvProb, int *dim1, int *dim2, double *issuerweights, double *recov, double *Z, double *w, int *n, double *rho, int *N, int *defaultflag, double *L, double *R) { /* computes the loss and recovery distribution over time with a flat gaussiancorrelation inputs: Survprob: matrix of size dim1 x dim2. dim1 is the number of issuers and dim2 number of time steps recov: vector of recoveries (length dim1) issuerweights: vector of issuer weights (length dim2) Z: vector of factor values (length n) w: vector of factor weights (length n) rho: correlation beta N: number of ticks in the grid defaultflag: if true, computes the default distribution outputs: L: matrix of size (N, dim2) R: matrix of size (N, dim2) */ int t, i, j; double g; double *gshocked, *Rshocked, *Sshocked, *Lw, *Rw; int one = 1; gshocked = Calloc((*dim1), double); Rshocked = Calloc((*dim1), double); Sshocked = Calloc((*dim1), double); Lw = malloc((*N) * sizeof(double)); Rw = malloc((*N) * sizeof(double)); for(t=0; t < (*dim2); t++) { for(i=0; i < *n; i++){ for(j=0; j < (*dim1); j++){ g = 1 - SurvProb[j + (*dim1) * t]; gshocked[j] = shockprob(g, *rho, Z[i], 0); Sshocked[j] = shockseverity(1-recov[j], Z[i], *rho, g); Rshocked[j] = 1 - Sshocked[j]; } /* reset Lw and Rw to 0 */ memset(Lw, 0, *N * sizeof(double)); memset(Rw, 0, *N * sizeof(double)); lossdistrib(gshocked, dim1, issuerweights, Sshocked, N, defaultflag, Lw); lossdistrib(gshocked, dim1, issuerweights, Rshocked, N, defaultflag, Rw); /* addandmultiply(Lw, w[i], L + t * (*N), *N); */ /* addandmultiply(Rw, w[i], R + t * (*N), *N); */ daxpy_(N, w + i, Lw, &one, R + t * (*N), &one); daxpy_(N, w + i, Rw, &one, R + t * (*N), &one); } } Free(gshocked); Free(Rshocked); Free(Sshocked); free(Lw); free(Rw); }