# Python 3.12.13 | glibc 2.28 | QuantLib 1.43 | x86_64
libm exp n=1000000 sha256=26a9e2ac51a70494
libm log n=1000000 sha256=1d16a7cf33682e7a
libm pow n=1000000 sha256=0070b84367b35d4f
discount factor, 1.5 years = 0.95599748183309996 0x1.e978807f10233p-1
process drift at t=0.5 = -0.011250000002571328 -0x1.70a3d70ba7528p-7
European call, Black-Scholes formula = 8.6124356138907761 0x1.1399129292215p+3
European call, delta = 0.49891112654468284 0x1.fee28ef07acf0p-2
European call, Monte Carlo = 8.5408473604976596 0x1.114e9f1faee45p+3
American put, binomial tree = 6.6202385489704172 0x1.a7b1fd06e2f8dp+2
American put, Longstaff-Schwartz = 6.5526994108438767 0x1.a35f6d5985f26p+2
Asian call, Monte Carlo = 6.5329120644316481 0x1.a21b3b34182d7p+2
Down-and-out call, Monte Carlo = 9.5748933379022443 0x1.326586b69f4f3p+3
European call, Heston formula = 10.309224649350977 0x1.49e52b17828b6p+3
European put, local volatility, Monte Carlo = 8.0916614100380553 0x1.02eee3e8cd65fp+3
European put, local volatility, Sobol = 8.2206887394419095 0x1.070fe1d4cff37p+3