void updateError(int x_pos, int y_pos, uint sim_time) {
normalizeBallParams(x_pos, y_pos, sim_time);
float r = R_x();
float curr_V = INV_DELTA_TIME * V_x();
error_x = r + GAMMA*curr_V - old_V_x;
old_V_x = curr_V;
r = R_y();
curr_V = INV_DELTA_TIME * V_y();
error_y = r + GAMMA*curr_V - old_V_y;
old_V_y = curr_V;
//io_printf(IO_STD,"error x %d, error y %d\n", (int)(error_x*1000), (int)(error_y*1000));
}
//Simulate the price process:
void
Sim_Price_Disc::simulate(int retries) {
//If we are re-simulating, we need to reset:
if (simulated) {
//X.simulate(retries); //Re-simulate X
X.simulate2();
//Clear Y
Y.clear();
Y.push_back(y_0);
//Reset the SBM Z:
Z.reset();
}
else {
simulated = true;
//Simulate volatility if necessary:
if (X.is_simulated() == false) {
//X.simulate(retries);
X.simulate2();
}
}
//Get the timestep vector from the volatility:
vector<double> timestep = X.get_timestep();
double h_t, drift;
matrix vola(n,n), tmp(n,n);
//For each discretisation step:
for (unsigned int i=1; i<timestep.size(); ++i) {
//Compute stepsize of the Brownian motion (in case this has changed):
h_t = timestep[i] - timestep[i-1];
//Even though we are not interested in eigenvalues anymore, we need the decomposition
// for the matrix square root.
matrix V_x(n,n), D_x(n,n);
eig(V_x, D_x, X.get_X_i(i-1));
//Compute next simulation point using the discretisation formula (see Section 5)
matrix V_r(n,n), D_r(n,n);
eig(V_r, D_r, (eye(n) - R * flens::transpose(R)));
drift = (r - 0.5*trace(X.get_X_i(i-1))) * h_t;
mat4mult(vola, Z.increment(h_t), V_r, matsqrt_diag(D_r), flens::transpose(V_r));
tmp = X.get_W_incr_i(i) * flens::transpose(R) + vola;
mat4mult(vola, V_x, matsqrt_diag(D_x), flens::transpose(V_x), tmp);
//Add simulation point to storage:
Y.push_back(Y[i-1] + drift + trace(vola));
}
}
