AIE-Tool-Quick-Reference

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The AIE Monte Carlo Tool
• The AIE Monte Carlo tool is an Excel spreadsheet and a
set of supporting macros.
• It is the main tool used in AIE analysis of a risky decision
and includes the following worksheets:
– Decision Model
– Risk Report
– Investment Boundary
• Other worksheets are typically added to maintain a
central location for data sources or other calculation
tools created for the organization (such as portfolio
classification tools, statistical analysis tools, etc.)
Copyright HDR 2006
dwhubbard@hubbardresearch.com
1
The Decision Model
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The “Decision Model” worksheet is where the decision model is created,
data is input, the Monte Carlo is run, and the Information Values are
computed.
The variables in your model are stacked vertically. Each variable or such as
“productivity improvement” or “revenue” has its own row.
The left side is the input area and the right side is the analysis area.
Input Area
Analysis Area
Copyright HDR 2006
dwhubbard@hubbardresearch.com
2
Decision Model Input
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The variables in your model are stacked vertically. Each variable such as
“productivity improvement” or “revenue” has its own row.
The left six columns of the “Decision Model” worksheet is the primary area
for data input for your models.
– Variable Name: This is where you enter the names of variables and the titles
you might want to add to organize major parts of your spreadsheet
– The range of values for estimates and the type of distribution used
– Notes about sources of the estimate or the formula used to compute the value
– If a row is a formula (not an estimate), the button “Show Formula Text” pastes
the text of a formula in the Source References column
Copyright HDR 2006
dwhubbard@hubbardresearch.com
3
Basic Monte Carlo Values
• The rows in a Decision Model has three basic purposes
• Each use the columns in the input area differently
• A row may also be blank or contain only a title or
heading for a section of the model
Value Type
Distribution
Type
Overview
Source Reference
A Distribution
Values 1-5
These are the uncertain variables in the
model. The HDR tool uses 5 basic
distribution types
Specifies source of the
measurement
Fixed Value
Blank
Represents the fixed value of a number
Specifies the source of the
standard that requires the
fixed value
Calculation
Blank
Contains the formula for the cell (all
calculations refer only to other Best
estimate values)
Shows the text for the
formula
Copyright HDR 2007 4
dwhubbard@hubbardresearch.com
Basic Distribution Types
If a row does contain an estimate with a distribution, the columns are used
differently depending on the distribution type. The AIE Monte Carlo Wizard has
five basic types of distributions
What each column contains
Distributions*
Upper & Lower Bound
Best Estimate
Dist.
Type
Normal distribution
Represents the "90% confidence
interval"
Test value only, not used in the
distribution calculations
1
Lognormal distribution
Represents the "90% confidence
interval"; the absolute lower bound
of a lognormal is always 0
Test value only, not used in the
distribution calculations
Uniform distribution
Represents the absolute (100%
certain) upper and lower bounds
Test value only, not used in the
distribution calculations
3
Represents the absolute (100%
certain) upper and lower bounds
Represents the median; the point
where there is equal chance of the
quantity being higher or lower
4
Not applicable; should be empty
Represents the % chance of the event
occurring
Split Triangle distribution
Binary distribution
2
5
35%
65%
*A “” means a “hard” stop, an “” arrow means unbounded
Copyright HDR 2007
dwhubbard@hubbardresearch.com
5
AIE Calculation Columns
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Random Scenarios: This is the column that generates random numbers
Mean: This column computes the mean based on the distribution type
Scenario w/Information: This shows the “expected” result given perfect
information about a particular variable or set of variables while the others are
held at their mean. This is used in the information value calculation
VIA Flag: The macro uses this column to “turn on” individual variables as the
one being analyzed for information value. It can also be used manually. By
setting it as a “1” during a Monte Carlo simulation of the NPV row in the same
column, you can compute EOL given perfect information in those variables.
Copyright HDR 2007
dwhubbard@hubbardresearch.com
6
AIE Calculation Columns
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EOL Notes & Calculation: Use this column to place results of selected Monte Carlos
for EOL results or for calculations that use them
Individual EVPI: This is where the EVPI for a single variable is computed by the
“Compute VIA’s” button
Individual Threshold: This is the threshold of that value – the point at which this value
would begin to make a difference in the decision
Threshold probability: This is the probability that a threshold in a range is “violated” –
that is, the chance the value could be different enough to affect the decision.
Copyright HDR 2007
dwhubbard@hubbardresearch.com
7
AIE Calculation Columns
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Countdown: This shows the number of scenarios remaining when running a Monte
Carlo simulation. When the number of scenarios gets to 0, then the Monte Carlo
simulation is finished.
Opp. Loss: This is the Opportunity Loss for a given scenario (i.e. “the cost of being
wrong”) for each scenario run.
EOL: The “Expected Opportunity Loss” is the average of all of the values in the Opp.
Loss cell in all of the scenarios run in the Monte Carlo. This does not have a formula
but is simply a place holder to record the value. When Monte Carlo is run, the
choice to compute the average of any value and have it put in a given cell. When this
is done for the Opp. Loss cell, the EOL cell is the place to put that value.
Copyright HDR 2007
dwhubbard@hubbardresearch.com
8
Decision Model Buttons
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In every row which is a calculation, this
automatically pastes the actual texts of formulas in
the “Source Notes” column
Create Monte Carlo
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This sets up the random scenario, mean, scenario
w/information, and VIA flag columns
Run Monte Carlo
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This opens the Monte Carlo Wizard dialog
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This clears all columns to the right of the VIA Flag
(the VIA calculation columns)
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This computes the Value of Information Analysis –
it places values in the Individual EVPI, Individual
Threshold, and Threshold probability columns
Show Formula Text
Clear VIA’s
Compute VIA’s
Copyright HDR 2007
dwhubbard@hubbardresearch.com
9
MC Wizard Dialog
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When the “Run Monte Carlo” button is clicked, the AIE Monte Carlo Wizard
dialog box appears
Choose whether you want
the output of the MC to be
an average in a single cell
or a histogram showing the
distribution of all the values
Choose which cell in the
model you want to track
while the Monte Carlo runs.
You can choose from a
given list of cells like “NPV”
or you can set it to any
other cell you like
Check this box if you want the
model to run faster. Uncheck it
if you want see the cells
change as the MC runs
Enter the number of scenarios you
want to run for the MC. Most MC run
for actual analysis should be >5,000
Copyright HDR 2006
dwhubbard@hubbardresearch.com
10
Risk Report
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When the user chooses “Histogram to Risk Report page” as the
output for the Monte Carlo Wizard, the output is shown on the
separate worksheet named Risk Report
The header box shows an average of all the values generated, the
percentage of them that are negative, the standard deviation and the
number of scenarios in this run
The histogram table below the header data shows the number of
times the value showed up in each of the given “bins” of the histogram
Chart titles and axis must be set manually
Copyright HDR 2006
dwhubbard@hubbardresearch.com
11
Investment Boundary Page
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The plotted point comes from the values
in the “Risk Report” page
The thinner investment boundaries
represent three benchmark investment
sizes
The thick investment boundary is
interpolated from the other three
The “compute CME” calculates a
“Certain Monetary Equivalent” based on
the relative position of the investment to
its boundary
Investments sorted by the “CME Ratio”
is a very good estimator of much more
elaborate methods in MPT
Copyright HDR 2007
dwhubbard@hubbardresearch.com
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