Title: Monte Carlo Simulation and Personal Finance
1Monte Carlo Simulation and Personal Finance
2Background on myself
- I work at Stephens Financial Partners as a
Financial Advisor - Monte Carlo simulations are the most popular
simulations used by advisors - These simulations failed after the 2008 market
collapse
3Where did it come from?
- John von Neumann and Stanislaw Ulam
- Los Alamos Scientific Laboratory
- Studying radiation shielding
4Why call it Monte Carlo?
- Neuman and Ulams work had to be kept a secret
because it was part of the Manhattan Project - Von Neuman chose the name "Monte Carlo".
5What is it?
- Class of computational algorithms
- Used to solve large systems
- Used when it is unfeasible or impossible to
compute an exact result
6Basic Principle of the Monte Carlo Method.
- The Task Calculate a number I (one number only.
Not an entire functional dependence) - Example Calculate pi
- Numerically look for an appropriate convergent
series and evaluate this approximately - Monte Carlo look for a stochastic model
probability space with random variable
7What makes a method a Monte Carlo Method?
- Define a domain of possible inputs.
- Generate inputs randomly from the domain using a
certain specified probability distribution. - Perform a deterministic computation using the
inputs. - Aggregate the results of the individual
computations into the final result
8Random Numbers
- Uniform Distribution
- The random variable X is uniformly distributed on
the interval a, b
9How many of you have played battleship?
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11Dull Monte Carlo
- hit or miss
- Take a sample point
- The point has two outcomes
- True (hit)
- False (miss)
- Total number of hits and divide it by the total
trials
12Hit or Miss
I unknown area
f(x)
I ? f(x) dx
X
13Crude Monte Carlo
- Write the integral such that I becomes the mean
value of a random variable. - Purposes we generate B numbers
- Uniformly distributed from (0,1)
- Then take their average
14Take Numerical Analysis
- Professor Robert Lewis
- Math 413 and 414
15Applications in the Real World
- Physical sciences
- Design and visuals
- Telecommunications
- Games
- Finance and business
16Monte Carlo in Finance
- First Introduced in 1964
- Risk Analysis in Capital Investment
- David B Hertz
- Harvard Business Review Article
17So how does Monte Carlo apply to Finance?
- Used to value and analyze
- Instruments
- Options
- Portfolios
- Investments
18How does it predict values?
- For each Simulation
- The behavior of the factors impacting the
component instrument is simulated over time - The values of the instrument are calculated
- The value is then observed
- The various values are then combined in a
histogram (i.e. the probability distribution) - The statistical characteristics are then observed
19How is it used in financial planning?
- Simulates the overall market
- Predicts the probability of reaching a target
number - Changes are made to reach the target number
20An Example
- http//www.flexibleretirementplanner.com/
21What works with Monte Carlo?
- Forecasting Earnings
- Modeling portfolio losses
- Provides flexibility
22What is wrong with Monte Carlo?
- Assumes normal return distributions
- We know from history that extreme returns occur
more frequently than expected - Cant predict every outcome
- Most clients see the simulation run through
thousands of iterations and believe that they
have seen all possible outcomes
23What is wrong with Monte Carlo?
- Does not measure bear markets well
- Does not include the human factor
24What is wrong with Monte Carlo?
- Does not recognize that portfolio performance
depends at least as much on the sequence of the
rate of return that it does on the average of
those returns
25What can we do better?
- Lets look at an example
- Assumptions
- 20 year period
- Individual that has just retired in 1988
- Has 1,000,000 invested in DJIA
- Withdraws 50,000 each year that increases by 3
to compensate for inflation
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30Have multiple buckets of money
- Dont just have your money in the stock market
- Have money growing outside of the stock market
31Homework
- Estimate Pi using Monte Carlo
32Thank You!