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Monte Carlo Method in Finance[edit]

Monte Carlo Method[edit]

Monte Carlo
Monte Carlo
Monte Carlo
H₂ H²

Monte Carlo Monte Carlo

dS = μS dt + σS dW_t
dS = μS dt + σS dW_t

header 1	header 2	header 3
row 1, cell 1	row 1, cell 2	row 1, cell 3
row 2, cell 1	row 2, cell 2	row 2, cell 3

Antithetic paths[edit]

A simple technique is, for every sample path obtained, to take its antithetic path — that is given a path $\{\varepsilon _{1},\dots ,\varepsilon _{M}\}$ to also take $\{-\varepsilon _{1},\dots ,-\varepsilon _{M}\}$ . Since the variables $\varepsilon _{i}$ and $-\varepsilon _{i}$ form an antithetic pair, a large value of one is accompanied by a small value of the other. This suggests that an unusually large or small output computed from the first path may be balanced by the value computed from the antithetic path, resulting in a reduction in variance. ^[1]Not only does this reduce the number of normal samples to be taken to generate N paths, but also, under same conditions, such as negative correlation between two estimates, reduces the variance of the sample paths, improving the accuracy.

References[edit]

^ Glasserman, P. (2004). Monte Carlo methods in financial engineering. New York: Springer. p. 205.

[1] Glasserman, P. (2004). Monte Carlo methods in financial engineering. New York: Springer. p. 205.

[1]