Monte Carlo Introduction
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1 Monte Carlo Introduction Probability Based Modeling Concepts moneytree.com Toll free
2 What is Monte Carlo? Monte Carlo Simulation is the currently accepted term for a technique used by mathematicians and engineers to find probable answers to highly complex and unpredictable equations. A large number of random trials are run. Patterns in the trials outcomes show the most likely range and concentration of results. Mark Snodgrass, Money Tree Software moneytree.com Toll free
3 How does Monte Carlo work? Mathematical Models are Used to Reflect Future Reality Variables in the Model allow for Future Uncertainty Probability Concepts Create Random Trials in the Model Large Number of Random Trials are Run for Analysis Patterns of Results Demonstrate Trends and Certainty Statistical Results Measure Distribution and Range Graphs Help Illustrate Variability and Show Patterns Mark Snodgrass, Money Tree Software moneytree.com Toll free
4 1000 Simulation Results Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 84% $3,123,022 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $3,165,938 $20,351,776 After tax rates of return average 6.12%, with a std. dev. of 8% (95% of values fall between -9.18% and 22.82%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
5 Monte Carlo Mathematical Model These balances and flows may be projected over time and combined into a cohesive model, an approximation of a complex financial life. Assets, Income, Additions, Growth Expenses, Withdrawals, Taxes Pensions, Social Security, Insurance Plans, Provisions, Special Situations Mark Snodgrass, Money Tree Software moneytree.com Toll free
6 Retirement Expense Projection Mark Snodgrass, Money Tree Software moneytree.com Toll free
7 Retirement Asset Projection Mark Snodgrass, Money Tree Software moneytree.com Toll free
8 Variables within the Model The real world is unpredictable, and things do change: Year by Year Asset Growth Rate of Return on Deposits Year by Year Inflation Effects Mark Snodgrass, Money Tree Software moneytree.com Toll free
9 Why Use Monte Carlo? Illustrate variability & uncertainty Test models in a variable environment Help design portfolios with less variability Show the need for ongoing monitoring Convey a confidence level to the client Demonstrate unequivocally that the client s financial future is unknown and changeable Mark Snodgrass, Money Tree Software moneytree.com Toll free
10 Change, Fluctuations & Chaos Random Behavior in Natural Systems tree growth, weather, populations Noise vs. Trends variations from the norm are normal Chaos is great complexity, multiple interactive influences, questionable predictability Mark Snodgrass, Money Tree Software moneytree.com Toll free
11 Chaos Patterns indiscernible at one level are often clear at higher levels Interactions and relationships are complex and subtle Individual outcomes are unknowable, yet the larger trends and cumulative results may be predictable Mark Snodgrass, Money Tree Software moneytree.com Toll free
12 Simulation Technology Simulation technology uses simulated chaos to find larger trends and cumulative results of complex systems Statistical analysis of results can help relate trends to simpler percentage terms Graphic representations may help illustrate both the technique and the resulting trends and scope of calculations Mark Snodgrass, Money Tree Software moneytree.com Toll free
13 Why Use Simulation Technology? Illustrates & Communicates Uncertainty Full Disclosure / Compliance Issues Promote Scheduled Plan Re-evaluation Annual or Bi-annual Plan Reviews Return/Inflation Sensitivity Measurement Plan performance evaluation Mark Snodgrass, Money Tree Software moneytree.com Toll free
14 How to Present the Simulation State assumptions about the general financial plan, and discuss the results of the average or nominal projections calculated statically Explain the effects of market and economic environment on the plan s assumptions Show the Simulation results as a representation of a potential range of actual results based on changing and unpredictable markets Discuss comfort level and probable outcomes Mark Snodgrass, Money Tree Software moneytree.com Toll free
15 Standard Normal Density Function Mark Snodgrass, Money Tree Software moneytree.com Toll free
16 Normal Distribution & Standard Deviation Mark Snodgrass, Money Tree Software moneytree.com Toll free
17 Standard Deviation Functions Mark Snodgrass, Money Tree Software moneytree.com Toll free
18 Portfolio Standard Deviation Calculations This is an example of a technique used to calculate the standard deviation of a mixed portfolio of 30% Bonds, 40% MidCap fund and 30% SmallCap fund. Bonds MidCap SmallCap Portfolio: 30% 40% 30% Rates of Return: 4.5% 13.0% 18.6% Standard Dev : 3.0% 11.0% 20.0% Portfolio Standard Deviation Calculation: Rate of Return = (.30)(4.5%) + (.40)(13%) + (.30)(18.6%) = 12.13% Variance = (.30)² * (3) ² + (.40) ² * (13) ² + (.30) ² * (20) ² Variance = (.09) * (9) + (.16) * (169) + (.09) * (400) = 63.85% Standard Deviation = Square Root (63.85%) = 7.99% Mark Snodgrass, Money Tree Software moneytree.com Toll free
19 Effects of Standard Deviations Mark Snodgrass, Money Tree Software moneytree.com Toll free
20 Standard Deviation: Zero Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 100% $3,123,022 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $3,123,022 $3,123,022 $3,123,022 After tax rates of return average 6.82%, with a std. dev. of 0% (95% of values fall between 6.82% and 6.82%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
21 Standard Deviation: Two Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 100% $3,123,022 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $653,639 $3,129,001 $6,303,086 After tax rates of return average 6.82%, with a std. dev. of 2% (95% of values fall between 2.82% and 10.82%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
22 Standard Deviation: Four Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 99% $3,123,022 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $3,151,228 $10,119,274 After tax rates of return average 6.82%, with a std. dev. of 4% (95% of values fall between -1.18% and 14.82%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
23 Standard Deviation: Seven Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 86% $3,123,022 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $3,030,590 $19,653,719 After tax rates of return average 6.82%, with a std. dev. of 7% (95% of values fall between -7.18% and 20.82%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
24 Standard Deviation: Eight Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 84% $3,123,022 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $3,165,938 $20,351,776 After tax rates of return average 6.82%, with a std. dev. of 8% (95% of values fall between -9.18% and 22.82%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
25 Standard Deviation: Ten Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 75% $3,123,022 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $3,368,356 $35,466,671 After tax rates of return average 6.82%, with a std. dev. of 8% (95% of values fall between -9.18% and 22.82%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
26 Plan Analysis: Evaluating Projections During Uncertain Conditions Measure plan results, and evaluate the probability of plan success through life expectancy Modify the plan to adjust for uncertainty and provide a comfortable level of plan performance Consider effects of portfolio allocation on risk and uncertainty Review plan performance over time Mark Snodgrass, Money Tree Software moneytree.com Toll free
27 Analysis: Starting Projection Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 59% $526,036 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $932,570 $14,143,859 After tax rates of return average 6.12%, with a std. dev. of 7% (95% of values fall between -7.88% and 20.12%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
28 Analysis: Starting Projection + $3000 Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 60% $751,836 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $1,112,433$ $10,275,389 After tax rates of return average 6.12%, with a std. dev. of 7% (95% of values fall between -7.88% and 20.12%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
29 Analysis: Starting Projection + $6000 Results of 1000 Simulations: Percentage of projections above zero Retirement Projection Estimate 80% $2,037,342 Minimum Monte Carlo projection Average Monte Carlo projection Maximum Monte Carlo projection $0 $2,403,443 $22,440,606 After tax rates of return average 6.12%, with a std. dev. of 7% (95% of values fall between -7.88% and 20.12%). Mark Snodgrass, Money Tree Software moneytree.com Toll free
30 Monte Carlo Thank you for taking the time to review the introduction to Monte Carlo. Questions? Ask Money Tree s Support Team Toll free support@moneytree.com moneytree.com Toll free
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