Monte-Carlo Simulation: Run an MC by simulating 1000 versions of the GBM with the following parameters; Start Value=100 Expected change in each time step (drift): 0% (μ) Volatility (st-dev of random noise): 2% (sigma) Number of Time Steps: 500 According to the simulated 1000 scenarios, what is the probability of reaching a value below 100 (i.e. the starting value) after 500 steps? According to the simulated 1000 scenarios, what is the probability of reaching a value below 75 (i.e. the starting value) after 500 steps? Show with a Python code and the simulation output as a Histogram of values reached at the 500th step. (i.e. Histogram of 1000 final values observed in each of the simulated path)

Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter10: Introduction To Simulation Modeling
Section: Chapter Questions
Problem 41P: At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 =...
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Monte-Carlo Simulation: Run an MC by simulating 1000 versions of the GBM with the following
parameters;
Start Value=100
Expected change in each time step (drift): 0% (μ)
Volatility (st-dev of random noise): 2% (sigma)
Number of Time Steps: 500
According to the simulated 1000 scenarios, what is the probability of reaching a value below 100
(i.e. the starting value) after 500 steps?
According to the simulated 1000 scenarios, what is the probability of reaching a value below 75
(i.e. the starting value) after 500 steps?
Show with a Python code and the simulation output as a Histogram of values reached at the
500th step. (i.e. Histogram of 1000 final values observed in each of the simulated path)
Transcribed Image Text:Monte-Carlo Simulation: Run an MC by simulating 1000 versions of the GBM with the following parameters; Start Value=100 Expected change in each time step (drift): 0% (μ) Volatility (st-dev of random noise): 2% (sigma) Number of Time Steps: 500 According to the simulated 1000 scenarios, what is the probability of reaching a value below 100 (i.e. the starting value) after 500 steps? According to the simulated 1000 scenarios, what is the probability of reaching a value below 75 (i.e. the starting value) after 500 steps? Show with a Python code and the simulation output as a Histogram of values reached at the 500th step. (i.e. Histogram of 1000 final values observed in each of the simulated path)
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