| 28 | |
| 29 | template<class ty, bool use_barrier> |
| 30 | static ty monte_carlo_barrier(int N, ty K, ty t, ty vol, ty r, ty strike, |
| 31 | int steps, ty B) { |
| 32 | dtype pres = get_dtype<ty>(); |
| 33 | array payoff = constant(0, N, 1, pres); |
| 34 | |
| 35 | ty dt = t / (ty)(steps - 1); |
| 36 | array s = constant(strike, N, 1, pres); |
| 37 | |
| 38 | array randmat = randn(N, steps - 1, pres); |
| 39 | randmat = exp((r - (vol * vol * 0.5)) * dt + vol * sqrt(dt) * randmat); |
| 40 | |
| 41 | array S = product(join(1, s, randmat), 1); |
| 42 | |
| 43 | if (use_barrier) { S = S * allTrue(S < B, 1); } |
| 44 | |
| 45 | payoff = max(0.0, S - K); |
| 46 | ty P = mean<ty>(payoff) * exp(-r * t); |
| 47 | return P; |
| 48 | } |
| 49 | |
| 50 | template<class ty, bool use_barrier> |
| 51 | double monte_carlo_bench(int N) { |