Lesson 18: Monte Carlo Simulation

April 13, 2016

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Wed Apr 13

Review:

• Multiple Regression in Python

Presentation:

• Monte Carlo Simulation
• Resources
  • Tutorial
  • Basic Income vs Basic Job
  • Excel Solver with Monte Carlo Simulation
• Sample Code

Assignment:

• Create a simple Monte Carlo Simulation with Python
• Simulate a simple Dice Game:
  • Roll 2-7, lose
  • Roll 8-12, win
  • Start with $100
    • bet $1 per roll (win pays $1, loss takes $1 bet)
    • roll 100 times and find ending balance (could be negative)
    • simulate 100 outcomes (10,000 total rolls of the dice)
  • Report the mean, median, and standard deviation of your final balances
  • Repeat using 1,000 rolls per outcome (100,000 total rolls of the dice) and report the mean, median and standard deviation of final outcomes

[highlight color=”options: yellow, black”]Here’s some python code to help you get going (and plain text below): [/highlight]

import random

def rollDice():
roll = random.randint(1,6)
return roll

j = 0
rollcount = 0
rolls = []

while j < 100:
i = 0
j = j + 1

while i < 100:
i = i + 1
result = rollDice()
rolls.append(result)
rollcount += 1

import scipy
mr = scipy.mean(rolls)
print(“Total rolls = “)
print rollcount
print(“Mean roll = “)
print mr