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Portfolio Allocation Model

This guide offers insights into effective portfolio allocation, emphasizing how different investors have unique objectives and how to account for uncertain returns. It introduces a simple spreadsheet model to simulate annualized returns across various asset classes, including Money Market, Income, Growth & Income, and Aggressive Growth. By defining assumptions and setting simulation parameters, users can analyze results to make informed decisions. The guide also covers optimization techniques using OptQuest to find the best asset allocation tailored to individual goals, highlighting the balance between risk and return.

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Portfolio Allocation Model

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  1. Portfolio Allocation Model • How to invest in different asset classes? • Different people have different objectives/goals. • Returns from investments are inherently random. How can we take this uncertainty into account and still make a reasonable decision?

  2. Simple Spreadsheet Model

  3. Asset Return Uncertainty (annualized) • Money Market • Uniform(minimum 2%, maximum 4%) • Income • Normal(mean 5%, stdev 5%) • Growth & Income • Normal(mean 7%, stdev 12%) • Aggressive Growth • Normal(mean 11%, stdev 18%)

  4. Crystal Ball • Define Assumption Cells for the annual returns • Define Forecast Cell • Set Simulation Settings (Number trials = 1000) • Run Simulation • View & Analyze Results • Run other two scenarios, complete summary table • Compare alternatives • (If no disk) Upload model to Blackboard Drop Box (toolsdigital drop box).

  5. Results • Summary Statistics • Mean, standard deviation, minimum, maximum, standard error • Frequency Distribution • Graphical, table of percentiles • Interactive use of frequency chart • What is the probability that the dollar return will be worse than $X? • What are the quartiles of the return distribution? What do they mean? • If I invest this way, at least how much should I be prepared to lose about 5% of the time?

  6. Goals/Objectives • Performance is a function of asset returns as well as asset allocation. • We cannot control returns, but we can control the allocation. • What is the “best” allocation? • Depends on the performance measure!

  7. Constrained Optimization • Objective (maximizing or minimizing) • Constraints • Decision Variables • Basic Question: What are the values of the decision variables which 1) satisfy the constraints, and 2) maximize or minimize the objective? • We will be using Solver soon in the course; however, Crystal Ball has a tool called OptQuest built in. • OptQuest is good for models which incorporate uncertainty, but is much slower than Solver for deterministic models.

  8. OptQuest • Build simulation model: define assumptions, forecast cells, and decision cells • CBTools…OptQuest • Wizard takes you through the process of specifying the optimization model. • Defining the objective: What is it you want to maximize or minimize?

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