Description Usage Arguments Value Author(s) References Examples
Calculates the price of a Barrier Option using 10000 Monte Carlo simulations. The helper function BarrierCal() aims to calculate expected payout for each stock prices.
Important Assumptions:
The option follows a General Brownian Motion (GBM)
ds = mu * S * dt + sqrt(vol) * S * dW where dW ~ N(0,1).
The value of mu (the expected percent price increase) is assumed to be o$r-o$q
.
1 2 |
o |
The |
knock |
Defines the Barrier option to be " |
B |
The Barrier price level |
NPaths |
The number of simulation paths to use in calculating the price |
The option o
with the price in the field PxMC
based on MC simulations and the Barrier option
properties set by the users themselves
Huang Jiayao, Risk Management and Business Intelligence at Hong Kong University of Science and Technology, Exchange student at Rice University, Spring 2015
Hull, John C., Options, Futures and Other Derivatives, 9ed, 2014. Prentice Hall. ISBN 978-0-13-345631-8, http://www-2.rotman.utoronto.ca/~hull/ofod/index.html. Also, http://stackoverflow.com/questions/25946852/r-monte-carlo-simulation-price-path-converging-volatility-issue
1 2 3 4 5 6 7 8 9 10 |
[1] 7.288736
[1] 6.73134
[1] 16.39553
[1] 5.474722
[1] 0.1317789
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