FINANCIAL MODELING

Financial modeling

Financial modeling is the task of building an abstract representation (a

model) of a financial decision making situation. This is a mathematical model,

such as a computer simulation, designed to represent (a simplified version of) the

performance of a financial asset or a portfolio, of a business, a project, or any other

form of financial investment. Many financial models are inherently stochastic.

Financial modeling is a general term that means different things to different users.

In the US and particularly in business schools it means the development of a

mathematical model, often using complex algorithms, and the associated computer

implementation to simulate scenarios of financial events, such as asset prices,

market movements, portfolio returns and the like. Or it might mean the

development of optimization models for managing and controlling the risk of a

financial investment. In Europe and in the accounting profession financial

modelling is defined as cash flow forecasting, involving the preparation of large,

detailed spreadsheets for management decision making purposes.

While there has been some debate in the industry as to the nature of financial

modeling : whether it is a tradecraft, such as welding, or a science, such as

metallurgy, the task of financial modeling has been gaining acceptance and rigor

over the years.

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Selected areas of financial modeling application

Business valuation, especially discounted cash flow

Cost of capital or WACC

Financial statement analysis

Modeling and analysis of financial markets

Modeling the term structure of interest rate and credit spread

Portfolio problems

Project finance

Real options

Risk modeling

Valuation (finance)

Option pricing

Mathematical representation of key financial and operational relationships.

Comprising of one or several sets of equations, it is used in analyzing how a

business will react to different economic situations or events, and in

estimating the outcome of financial decisions before committing any funds.

A financial model generally includes cash flow projections, depreciation

schedules, debt service, inventory levels, rate of inflation, etc.

It may also quantify the financial impact of the firm's policies, and of

restrictions or covenants imposed by investors and/or lenders. A cash budget

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(whether computed by hand or with a spreadsheet program) is a basic

financial model.

Financial Modeling

What is a financial model?

A simple, practical answer is that a financial model is designed to represent

in mathematical terms the relationships among the variables of a financial problem

so that it can be used to answer “what if” questions or make projections. In

creating financial models, you always have to keep in mind that you want to

capture as many of the interdependencies among the variables of the model as

possible. In addition, you want to structure your models in such a way that it is

easy to ask “what if” questions, that is, change the values of the independent

variables and observe how they affect the values of the key dependent variables.

You also should recognize that some of the relationships, as in the case of taxes,

are easy to establish and exact; but many others will be approximate or even

unknown. You will have to come up with them based on financial theory, analysis

of data, and so on, and coming up with these relationships is one of the major

challenges of financial modeling. Generally, the more of these relationships you

can come up with and incorporate into your model, the more useful your model

will be.

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Independent and Dependent Variables

We can say that the purpose of a model is to calculate the values of certain

dependent variables for the values provided for its independent variables. It is

therefore important to understand the difference between independent and

dependent variables.

Independent variables are also called the input or external variables. The

model’s user or creator inputs the values of these variables—they are not

calculated by the model. These are the variables you change to ask “what if”

questions.

Dependent variables are the ones whose values we want to project or determine

when we ask “what if” questions.

STEPS IN CREATING A MODEL

Whether you are creating a financial model using Excel or VBA, you must take a

systematic approach. A systematic approach always involves planning ahead and

this takes some time. Most people do not like to plan and think they can save time

by starting to build a model right away without spending time on planning.

However, for all but the simplest models, not taking the time upfront to do some

planning and not taking a systematic approach ends up being both frustrating and a

waste of time.SAMRITI GOEL

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Here are the key steps you should follow in creating both Excel and VBA

models.

You should keep two other things in mind.

First, in practice, you do not have to follow the steps strictly in this order, nor do

you have to finish one completely before going onto the next one. Most of the

time you will have to go back and forth to some extent. It will depend on the

circumstances.

Second, over time, you should try to create your own variation on this basic

approach and learn to adapt it to different situations.

Excel and VBA are flexible tools and you can usually make changes almost

at any stage without a great deal of difficulty. But this still will take more time

than if you do it right the first time, and making changes later increases the

chances of missing some of the other changes that have to go with them.

Step 1: Define and Structure the Problem

In real life, problems rarely come neatly defined and structured. Unless you take

the time upfront to define and structure the problem and agree on them with the

user (your boss, for example), you may end up having to extensively change the

model you first create.

Start by discussing and defining why the model is needed and what decisions,

if any, will be made based on its output—that is, what questions the model is

supposed to answer. Then establish how accurate or realistic the outputs need to SAMRITI GOEL

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be. As we discussed, all models have to capture the relationships among their

variables, and discovering and quantifying these can take a lot of time. How much

effort you put into doing this should depend on how important the project is and

how accurate or realistic the outputs need to be.

Step 2: Define the Input and Output Variables of the Model

Make a list of all the inputs the model will need and decide who will provide

them or where they will come from. This is crucial. For example, if you are

creating a model to do the business plan for your company, the inputs must come

from the business managers. You cannot just guess what sales growth rates they

will be able to achieve, how much they will have to spend on plants and equipment

to support those sales growths, and so forth. You may not need the actual numbers

upfront, but the list of inputs should be established based on your discussions with

the business managers so that you can make them independent variables in your

model. Otherwise you may have go back later on and change a lot of things in the

model.

Make a list of the tabular, graphical, and other outputs the model needs to

create. To some extent, these should be driven by the decisions that will be made

based on them.

Step 3: Decide Who Will Use the Model and How Often

Who will use the model and how often it will be used make a lot of difference.

In this, I am assuming that you are developing the models either for your

own use or for use by others who are familiar with Excel and understand the

model, at least to some extent. When you create models for others’ use, it

involves much more work. You have to make sure that these people cannot enter

data that do not make sense, they cannot accidentally damage parts of the model,

and they can get the necessary outputs automatically and so forth. These are SAMRITI GOEL

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collectively called the user interface, and the more elegant, more easy to use, and

more robust you want to make a model, the more work it is. You also have to plan

for many of these features ahead of time.

How frequently a model will be used is another important issue. If a model

is going to be used only once in a while, then it does not matter if it takes a long

time to run or if it takes some extra work every time to create the outputs. A

model that will be used frequently, however, should be designed differently.

Step 4: Understand the Financial and Mathematical Aspects of the Model

It is important to remember that the computer cannot do any thinking; you have

to tell it exactly how all the calculations in the model will have to be done. In

most situations, if you do not know how you would do the calculations by hand,

you are not going to be able to write the necessary formulas or instructions for

the computer to do it. It does not pay to start building the model until you are

sure you could solve the problem by hand.

It usually takes beginners a lot of time to create a model and they often think

that it is their Excel or VBA skills that are slowing things down. This may be

partly true, but at least as often the problem is in their understanding of the

finance and mathematics of the model they are trying to create. You will save lot

of time if you do not even sit down in front of the computer to create a model until

you are sure that you know how to solve the problem.

Step 5: Design the Model

There are two aspects to designing a model. One is to sketch the steps that Excel or

VBA will have to follow to solve the problem. For simple models, you may want

to write down only the broad steps or perhaps even do it in your head. For more SAMRITI GOEL

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FINANCIAL MODELING

complex problems, however, you should work on paper and use a degree of detail

that suits your level of experience and the complexity of the problem.

The less experience you have, the more detailed the sketch should be. Once again,

remember that this may seem like a waste of time, but ultimately it will save you

time compared to plunging into your spreadsheet or VBA program without such a

sketch of the model.

The other aspect of design is planning how the model will be laid out in Excel

or VBA. Are you going to do the entire model in one spreadsheet (or VBA

module) or split it into several spreadsheets (or VBA modules or procedures)?

Editing an Excel or VBA model is easy. So you do not have to decide every detail

ahead of time, but you need to have an overall design in mind or on paper

depending on the complexity of the problem and your level of experience.

Step 6: Create the Spreadsheets or Write the VBA Codes

For most models, this is the big step.

Step 7: Test the Model

Almost no model works correctly the first time it is used; you have to find the

problems (bugs) and fix them. The bugs that prevent the model from working at

all or produce obviously wrong answers are generally easier to find and fix.

However, models often include hidden bugs that create problems only for certain

values or certain combinations of values for the input variables. To find them, you

have to test a model extensively with a wide range of input variables.

You have to take somewhat different approaches to testing and debugging aSAMRITI GOEL

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model depending on whether you are working with Excel or VBA. Both Excel

and VBA provide some special tools for this purpose.

Here are a few helpful hints that apply to both:

■ There is no standard approach to testing and debugging a model. You almost

always have to use your ingenuity to figure out what will be the best way to

test and debug a particular model. Your ability to do so will improve with

experience.

■ The better you understand a problem and a model, the easier it will be to

debug it. If you understand how changes in certain independent variables

affect the values of certain dependent variables, then you can change the values

of the independent variables to see if the dependent variables are changing

in the right direction and by the right orders of magnitude.

■ Checking a model’s output against hand-calculated answers is a common and

effective approach to debugging. In some situations, doing hand calculations

may not be practical, but you may be able to use Excel itself to do some side

calculations to test individual parts of the model.

Step 8: Protect the Model

Once you have completed a model, and especially if you are going to give it to

others to use, you should consider protecting it against accidental or unauthorized

changes. In addition, you may also want to hide parts of the model so that

others cannot see certain formulas, data, and so on. Excel provides several flexible

tools that you can use to hide and protect parts or all of your model.

There is less need to protect VBA modules because most users do not even

know how to open them. Nonetheless, if you think it is necessary, you can protect

parts of your VBA models as well.

Step 9: Document the ModelSAMRITI GOEL

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Documenting a model means putting in writing, diagrams, flowcharts, and so on,

the information that someone else (or you yourself in the future) will need to figure

out what it does, how it is structured, and what assumptions are built into it. One

can then efficiently and effectively make changes to (update) the model if

necessary.

For large systems (for example, the reservation systems for airlines), the amount of

necessary documentation can be enormous; it is often put on CDs for easy access

and use. Professional system development organizations have elaborate standards

for documentation, because different pieces of large systems are developed by

different people—many of whom may not be around for very long.

Also, it is almost certain that the systems will have to be constantly updated. Over

time, anyone who creates models develops his own system of documentation.

Step 10: Update the Model as Necessary

This is not a part of the initial model development, but almost all models require

updating at some point, either because some things have changed or because you

want to adapt it to do something else. This is where the documentation becomes

useful. Depending on how much updating is involved, you may want to go through

all of the above steps again. You should also thoroughly update the documentation

and include in it the information on who updated it, when and why, and what

changes were made.

Overview

Financial models need to be:

Useful – they need to assist the user in solving the business problem. This

needs good business analysis and design skills.SAMRITI GOEL

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Accurate – they must do exactly what they say they do. This needs correct

logic, accurate calculations & relevant results.

Flexible, so they can evolve throughout the analytical process and beyond.

Provable – the inputs, calculations and results can all be verified. This needs

clear layout, good documentation, data validation & results testing.

A good guiding rule is to keep things as simple and as clear as possible, for

example:

using common functions rather than complex or rarely used functions

keeping formulae short

not being "clever", which may just confuse other people

Specifying a model

Find out first –

what exactly it is for, & what it needs to do

what inputs it needs and where the data & assumptions will come from

what business logic is required

what level of detail it needs to provide

what flexibility is required – i.e. what needs to be able to change

who will use it & how, & what are their skills

how often it will be used, & for how longSAMRITI GOEL

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FINANCIAL MODELING

how soon it is needed

For anything except a small model with a clear cut specification and design, it is a

good idea - and essential in many cases - to document the specification clearly,

It is extremely important to fully understand and document the business logic, i.e.

all the business rules that need to go into the model. For example, most business

models involve tax, so you’d expect some rules on how tax affects the model. As

you will see, errors in logic – and especially omissions – are among the hardest to

find – and they can be extremely dangerous.

You should always ensure you have copies of all relevant correspondence or

documents, and anything that will help you understand the business. For example,

if you are modelling a workers’ compensation portfolio, you would need

documentation on the benefits that are paid, previous actuaries’ reports,

publications that might indicate recent trends or issues, etc.

Writing a specification

A specification is a written description of your model. It should cover

what your model will and won’t do

what data and other information it needs

what results it will produce

documentation and support (if applicable)

maintenance (if applicable)

timingSAMRITI GOEL

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cost

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Design patterns

Design patterns are used where the same set of needs comes up over and over

again. They are standard and well-tested approaches to designing models, and

you can build up a library of patterns to make it easier to design professional

solutions.

Contents

Tabular pattern : The tabular pattern below is one all spreadsheet users are

familiar with. This is the simplest and most obvious way to build models, and it is

used for most business spreadsheets. It has two main problems:

1. the formulae must be copied down correctly in each column – this is a common

error,

2. it can be hard to check formulae, when they are crammed into successive

columns. There is little room for any explanation, users can only see one formula at

a time (unless they turn on the formula view, and then you can't see the values), and

users can only see a few columns at a time. This means that as a model gets more

complex, this pattern can become very difficult to follow, and even unworkable.

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Block pattern : In more complex models, it may be difficult to fit everything

into one sheet using the tabular pattern above. The model can be divided into

sections such as tax, depreciation, revenue cashflows, etc, and each of these

can be put into a separate "block", usually on a separate sheet. The results are

then consolidated in a summary sheet.

This is a pattern commonly used in large finance models, eg for toll roads, power

stations, etc, where a large number of cashflows are projected forward in time, and

where the model can be broken up into logical chunks. The models can get very

big, eg 15 meg, with 3,000-4,000 unique formulae.

The advantage is that each sheet can be checked independently, and each sheet is

on a particular topic. When a problem is complex, it helps if you can check it a

piece at a time.

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Merge pattern : The following approach is a powerful alternative to the

tabular pattern. It works well where you have to carry out a series of

calculations for many rows of data. You first build a calculation sheet based on

a single record of data, showing that data at the top of the sheet, listing any

assumptions you need (explaining as you go), and then setting out the calculations

down the sheet, as spread out as you like.

The result is that, given any one of the data records (ie rows), you can produce the

correct results clearly and accurately for that single row.

VBA pattern : VBA can be used to read in the data and assumptions, carry out

all the calculations, and then put the results back in the sheet. This is a very

powerful approach where there are large amounts of data, or where a

worksheet would be very slow, because

VBA can process data extremely quickly, and

it can read from and write to data files, databases and websites,

and it is very compact, because all its calculations are done in memory and

are discarded once the results are put back in a sheet

Generally, VBA should be used for complex models involving a lot of data, like a

simulation or a very large datafile.

Building for safety

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The more you work with spreadsheets, the more you will see how inventive people

can be in making mistakes, or in misunderstanding what was intended. You have to

assume that if it can be read the wrong way, someone will read it wrong.

The guidelines below are all aimed at making it harder to make mistakes.

Inputs and Data

Separate inputs & assumptions from calculations (this is crucial)

Label & colour input cells clearly

Protect & constrain inputs with data validation or user controls

If you are importing data, keep it separate from the calculations

Give important variables range names, and use them in formulae

Treat constants (eg tax rates) as (unchangeable) inputs – never hard code

them into formulae as numbers

Clearly explain anything that may be unfamiliar or confusing

Formulae & Calculations

Protect calculations – on a separate sheet, or protect the sheet

Flow calculations from left to right, top to bottom, to echo Excel's

calculation sequence, and also the way people will "read" the spreadsheet

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Highlight any cells with inconsistent formulae (ie different to neighbours) –

preferably don’t do this at all because these anomalies can be very hard to

find and may be overwritten if someone else makes a change and copies it

down a whole column!

Use colours carefully – keep bright colours for warnings

Use a consistent layout & design between sheets

Use consistent magnitudes/time intervals (eg months or years)

Show sources (references, links to source documents, extracts)

Include anomaly checks and self-tests (eg cross-totals) so that the model

checks itself as much as possible

Don’t be clever! eg don’t use obscure functions that no-one else understands

Don’t create incredibly long formulae – rather use more columns

Don’t distract or confuse the checker

Results

Set results out clearly and unambiguously

State all key assumptions, especially in printable results

Put date (and version number if any) on printouts

Testing

The most important thing to remember is that you are the last line of defense. You

aren’t just there to look for typos, and anything you miss could cost a lot of money

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or embarrassment, so be careful and don’t rush. In the notes that follow, we’ll

assume we are checking a model which is important enough to spend a day or two

checking, and that we definitely want no errors. We’ll also consider what can be

done to make a model easier to check. We’ll use the words “check”, “test” &

“review” a lot below. They all have the same objective – ensuring the model is

correct, or close enough to correct.

Analysis

Making sense of the results is crucial. The first test is that your results give you the

information you need to analyse the client problem. Then you need to play with the

model to test the effect of different inputs, to get a feel for the sensitivity to

change. Ideally, you want results which are robust (ie they are not too sensitive to

your inputs).

USES OR BENEFITS OF FINANCIAL MODELS

1. Increase the breadth of analysis leading to decision making.

2. Provides a framework for long- range planning.

3. Evaluating new forms and uses of financial information

4. Tools for special problems

5. Understand the inherent logic of the financial system

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ABUSES OF FINANCIAL MODELLING

1. Don’t meander into financial modeling

2. Problems of excessive evaluation of computer software

3. Beware of sophisticated statistical models

4. Recognize the “future stock” syndrome

5. Financial models are not for everyone

6. Financial models, budgets , and general ledgers are different

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