import numpy as np
import pandas as pd
import options.lsm as lsm
table = lsm.price_table(100000, 50)
np.transpose(pd.DataFrame.from_dict(table))
European Price | LSM American Price | LSM American SE | Simulated European Price | Simulated European SE | |
---|---|---|---|---|---|
36 0.2 1 | 3.844308 | 4.473337 | 0.009876 | 3.841138 | 0.013635 |
36 0.2 2 | 3.763001 | 4.827320 | 0.011893 | 3.982655 | 0.016281 |
36 0.4 1 | 6.711399 | 7.104770 | 0.019679 | 6.711362 | 0.023006 |
36 0.4 2 | 7.700040 | 8.465423 | 0.024178 | 8.184778 | 0.028316 |
38 0.2 1 | 2.851932 | 3.256599 | 0.009656 | 2.855663 | 0.012149 |
38 0.2 2 | 2.990557 | 3.728441 | 0.011645 | 3.155735 | 0.014785 |
38 0.4 1 | 5.834321 | 6.154242 | 0.019369 | 5.837305 | 0.021935 |
38 0.4 2 | 6.978802 | 7.637595 | 0.023774 | 7.442247 | 0.027542 |
40 0.2 1 | 2.066401 | 2.322347 | 0.008958 | 2.079413 | 0.010584 |
40 0.2 2 | 2.355866 | 2.877937 | 0.010946 | 2.501114 | 0.013323 |
40 0.4 1 | 5.059623 | 5.323717 | 0.018379 | 5.057777 | 0.020805 |
40 0.4 2 | 6.325999 | 6.903202 | 0.022808 | 6.719609 | 0.026494 |
42 0.2 1 | 1.464504 | 1.613934 | 0.007747 | 1.456605 | 0.008882 |
42 0.2 2 | 1.841354 | 2.205585 | 0.009963 | 1.960058 | 0.011901 |
42 0.4 1 | 4.378718 | 4.572274 | 0.017662 | 4.386564 | 0.019659 |
42 0.4 2 | 5.735618 | 6.222996 | 0.022171 | 6.062861 | 0.025483 |
44 0.2 1 | 1.016915 | 1.110343 | 0.006563 | 1.011694 | 0.007398 |
44 0.2 2 | 1.429215 | 1.689388 | 0.009085 | 1.528936 | 0.010495 |
44 0.4 1 | 3.782799 | 3.949719 | 0.016644 | 3.776469 | 0.018460 |
44 0.4 2 | 5.201995 | 5.652219 | 0.021964 | 5.572470 | 0.024679 |