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#include <R.h>
#include <Rmath.h>
#include <string.h>
#define MIN(x, y) (((x) < (y)) ? (x) : (y))
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<MIN(M, *N); j++){
sum += q[j];
}
q[*N-1] += 1-sum;
}
Free(qtemp);
}
void lossdistrib_truncated(double *p, int *np, double *w, double *S, int *N,
int *T, 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
T where to truncate the distribution
defaultflat if true computes the default distribution
q the loss distribution */
int i, j, d1, d2, M;
double lu, d, p1, p2, sum;
double *q1, *q2;
lu = 1./(*N-1);
q1 = Calloc( *T, double);
q2 = Calloc( *T, 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;
for(j=0; j < MIN(M, *T); j++){
q1[j] = p1 * q[j];
q2[j] = p2 * q[j];
q[j] = (1-p[i]) * q[j];
}
for(j=0; j < MIN(M, *T-d1); j++){
q[d1+j] += q1[j];
};
for(j=0; j < MIN(M, *T-d2); j++){
q[d2+j] += q2[j];
};
M += d2;
}
Free(q1);
Free(q2);
}
void lossdistrib_joint( double *p, int *np, double *w, double *S, int *N, int *defaultflag, double *q) {
/* recursive algorithm with first order correction
computes jointly the loss and recovery distribution
p vector of default probabilities
np length of p
w vector of issuer weights (length np)
S vector of severities (should be same length as p)
N number of ticks in the grid
defaultflag if true computes the default distribution
q the joint probability distribution */
int i, j, k, m, n;
int Mx, My;
double lu, x, y, sum;
double alpha1, alpha2, beta1, beta2;
double w1, w2, w3, w4;
double *qtemp;
lu = 1./(*N-1);
qtemp = Calloc( (*N) * (*N), double);
q[0] = 1;
Mx=1;
My=1;
for(k=0; k<(*np); k++){
x = (*defaultflag)? w[k] /lu : S[k] * w[k] / lu;
y = (1-S[k]) * w[k] / lu;
i = floor(x);
j = floor(y);
alpha1 = i + 1 - x;
alpha2 = 1 - alpha1;
beta1 = j + 1 - y;
beta2 = 1 - beta1;
w1 = alpha1 * beta1;
w2 = alpha1 * beta2;
w3 = alpha2 * beta2;
w4 = alpha2 * beta1;
for(n=0; n<MIN(My, *N); n++){
memcpy(qtemp+n*(*N), q+n*(*N), MIN(Mx, *N) * sizeof(double));
}
for(n=0; n<MIN(My, *N); n++){
for(m=0; m<MIN(Mx, *N); m++){
q[m+(*N)*n] = (1-p[k])* q[m+(*N)*n];
}
}
for(n=0; n < MIN(My, *N-j-1); n++){
for(m=0; m < MIN(Mx, *N-i-1); m++){
q[i+m+(*N)*(j+n)] += w1 * p[k] * qtemp[m+(*N)*n];
q[i+m+(*N)*(j+1+n)] += w2 * p[k] * qtemp[m+(*N)*n];
q[i+1+m+(*N)*(j+1+n)] += w3 * p[k] * qtemp[m+(*N)*n];
q[i+1+m+(*N)*(j+n)] += w4 * p[k] *qtemp[m+(*N)*n];
}
}
Mx += i+1;
My += j+1;
}
/* correction for weight loss */
if(Mx>*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<MIN(M, *N); j++){
sum += q[j];
}
q[*N-1] += 1-sum;
}
Free(qtemp);
}
void lossdistrib_prepay_joint(double *dp, double *pp, int *ndp, double *w,
double *S, int *N, int *defaultflag, double *q) {
int i, j1, j2, k, m, n;
double lu, x, y1, y2, sum;
double alpha1, alpha2, beta1, beta2;
double dpw1, dpw2, dpw3, dpw4;
double ppw1, ppw2, ppw3;
double temp;
double *qtemp;
int Mx, My;
lu = 1./(*N-1);
qtemp = Calloc((*N) * (*N), double);
q[0] = 1;
Mx=1;
My=1;
for(k=0; k<(*ndp); k++){
y1 = (1-S[k]) * w[k]/lu;
y2 = w[k]/lu;
x = (*defaultflag)? y2: y2-y1;
i = floor(x);
j1 = floor(y1);
j2 = floor(y2);
alpha1 = i + 1 - x;
alpha2 = 1 - alpha1;
beta1 = j1 + 1 - y1;
beta2 = 1 - beta1;
dpw1 = alpha1 * beta1 * dp[k];
dpw2 = alpha1 * beta2 * dp[k];
dpw3 = alpha2 * beta2 * dp[k];
dpw4 = alpha2 * beta1 * dp[k];
/* by default distribution, we mean names fractions of names that disappeared
either because of default or prepayment */
for(n=0; n<MIN(My, *N); n++){
memcpy(qtemp+n*(*N), q+n*(*N), MIN(Mx, *N) * sizeof(double));
}
for(n=0; n<MIN(My, *N); n++){
for(m=0; m<MIN(Mx, *N); m++){
q[m+(*N)*n] = (1-dp[k]-pp[k]) * q[m+(*N)*n];
}
}
if(*defaultflag){
ppw1 = alpha1 * alpha1 * pp[k];
ppw2 = alpha1 * alpha2 * pp[k];
ppw3 = alpha2 * alpha2 * pp[k];
for(n=0; n < MIN(My, *N-j2-1); n++){
for(m=0; m < MIN(Mx, *N-i-1); m++){
q[i+m+(*N)*(j1+n)] += dpw1 * qtemp[m+(*N)*n];
q[i+m+(*N)*(j1+1+n)] += dpw2 * qtemp[m+(*N)*n];
q[i+1+m+(*N)*(j1+1+n)] += dpw3 * qtemp[m+(*N)*n];
q[i+1+m+(*N)*(j1+n)] += dpw4 * qtemp[m+(*N)*n];
q[i+m+(*N)*(j2+n)] += ppw1 * qtemp[m+(*N)*n];
temp = ppw2 * qtemp[m+(*N)*n];
q[i+m+(*N)*(j2+1+n)] += temp;
q[i+1+m+(*N)*(j2+1+n)] += ppw3 * qtemp[m+(*N)*n];
q[i+1+m+(*N)*(j2+n)] += temp;
}
}
}else{
for(n=0; n < MIN(My, *N-j2-1); n++){
for(m=0; m < MIN(Mx, *N-i-1); m++){
q[i+m+(*N)*(j1+n)] += dpw1 * qtemp[m+(*N)*n];
q[i+m+(*N)*(j1+1+n)] += dpw2 * qtemp[m+(*N)*n];
q[i+1+m+(*N)*(j1+1+n)] += dpw3 * qtemp[m+(*N)*n];
q[i+1+m+(*N)*(j1+n)] += dpw4 * qtemp[m+(*N)*n];
q[m+(*N)*(j2+n)] += pp[k]*(j2+1-y2) * qtemp[m+(*N)*n];
q[m+(*N)*(j2+1+n)] += pp[k]*(y2-j2) * qtemp[m+(*N)*n];
}
}
}
Mx += i + 1;
My += j2 + 1;
}
/* correction for weight loss */
if(Mx>*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 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<n; i++){
Y[i] += alpha*X[i];
}
}
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;
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);
}
}
Free(gshocked);
Free(Rshocked);
Free(Sshocked);
free(Lw);
free(Rw);
}
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