MBAD/F 619: Risk Analysis
and Financial Modeling
Instructor: Linda Leon
Fall 2014
http://myweb.lmu.edu/lleon/mbaf619/
Overview of Financial Modeling

Financial statements report what happened to
the firm in the past (Accounting)
 Financial models look forward to the future:

Financial planning models (pro forma models)
predict future financial statements results

Cash models project short term cash balances

Portfolio models predict the return/risk of portfolios

Option models anticipate future stock prices
Financial Modeling: An Overview of
Relationships Between Inputs and Outputs
Special
Analysis
Fund Flow
Analysis
Pro forma
Statements
Ratio
Analysis
Investment
Data
Financial Model
(computer program)
Financial
Data
Operating History and Future
Assumptions
Staff
Inputs
Manufacturing or
Service Inputs
Sales
Inputs
Defining Risk

Two ingredients are present when risk exists
(Holton, “Defining Risk”, Financial Analysis Journal, 60(6), pp 19-25, 2004):
Uncertainty about outcomes
 Different outcomes provide different utility
 Standard deviations s and betas b used to
measure uncertainty



Distribution assumptions measure probability of an
outcome
A comprehensive definition incorporates the
probability and the consequence of outcome
Dealing with Risk

Hedging risk:

Reducing risk exposures to undesirable
outcomes
Insurance
 Options
 Reject investment: “No-go” decision


Managing risk:

Hedging some risks while also taking
advantage of upside potential through
strategic risk taking
Risk Management Applications

Investment Decisions

Portfolio Strategies:




Asset Allocations
Asset Selection
Performance Evaluation
Financing Decisions



Project Investment Decisions
Financing Decisions
Dividend Decisions:


Working Capital Management
Cash Budgeting
Valuation

The value of a business underlies the
decision-making for all investment and
financing decisions:



Want to identify companies that trade at below “fair”
value for investments
Want to make decisions that increase firm value
Value is determined by expected cash flows
and discount rate

Good models will allow risk to be incorporated into
its cash flows, growth rates and discount rates
Decision Support Models require
the developer to

Be explicit about the objectives of the model
and the assumptions being made

Identify decision parameters that influence
objectives

Think carefully about which variables to
include and their relationships to other
variables

Consider what data is needed
Two Prescriptive Analytical
Approaches for Financial Modeling

Simulation


Process of imitating the firm so that the
possible consequences of alternative
decisions and strategies can be analyzed
prior to implementation
Optimization

Identifies which decision alternative leads to
a desired objective given a specified set of
fixed assumptions
Financial Modeling

Many financial models which use advanced
modeling and analytical techniques are
spreadsheet based

There is a market demand for more
sophisticated models and analysis by financial
end-users

Most end-users prefer to develop their own
models (cost,flexibility)
Advantages of End-User Modeling

End-users get closer to the raw data and the
assumptions being made

End-users can customize the models to
generate information that fits their needs

End-users can see results easily and
immediately, which enhances strategy
generation and encourages risk analysis
Disadvantages of End-User Modeling

Incorrect information is generated by inappropriate or
inaccurate models (20 to 40% contain significant
errors)

End-users are overconfident about the quality of their
own spreadsheets

Poorly designed models can discourage strategy
generation and risk analysis

End-users may not always employ the most productive
methods for generating insights or may misinterpret
the generated information
Recent spreadsheet research
shows…

End users typically do not plan their
spreadsheets

End users rarely spend time debugging their
models

End users almost never let another person
review their spreadsheets

Many end users do not consistently use tools
that can make modeling productive and
insightful
Course Objectives: Students
should be able to

Identify, assess and quantify business risks
and recommend strategies to manage risk

Develop and use appropriate financial
planning spreadsheet models to analyze
various financial applications involving
uncertainty
As well as….

Apply advanced analytical skills in modeling
and decision-making with an emphasis on
Monte Carlo simulation and optimization

Integrate the information provided by the use
of simulation and optimization into the
decision-making process and be aware of the
limitations of the information provided