Like many computer programmers, human being who construct financial models can obtain quite opinionated about the “right way” to carry out it.

You are watching: A company or department may standardize with a specific

In fact, over there is surprisingly small consistency across wall Street around the structure of gaue won models. One reason is that models deserve to vary extensively in purpose. Because that example, if your job was to build a discounted cash flow (DCF) design to be offered in a preliminary pitch book as a valuation for one of 5 potential acquisition targets, it would likely be a rubbish of time to develop a highly complex and feature-rich model. The time forced to develop a super complex DCF design isn’t justified given the model’s purpose.

On the various other hand, a leveraged finance version used to make thousands of loan approval decisions for a range of loan types under a variety of scenarios necessitates a great deal that complexity.

Understanding the objective of the version is vital to identify its optimal structure. There space two primary factors of a model’s appropriate structure: granularity and also flexibility. Let’s take into consideration the complying with 5 common financial models:

One page DCFUsed in a buy side pitch publication to carry out a valuation variety for among several potential acquisition targets.Low. Ball-park valuation variety is sufficient) / Small. Entire analysis can to the right on one worksheet

Financial design granularity

A crucial determinant the the model’s framework is granularity. Granularity describes how thorough a version needs come be. For example, imagine you space tasked v performing an LBO evaluation for Disney. If the purpose is to carry out a back-of-the-envelope floor valuation range to be offered in a preliminary key book, it might be perfectly ideal to perform a “high level” LBO analysis, using consolidated data and also making very basic assumptions for financing.


If, however, your model is a vital decision making device for financing demands in a potential recapitalization the Disney, a far higher degree the accuracy is incredibly important. The distinctions in these 2 examples can involve things like:

Forecasting revenue and cost of products segment through segment and also using price-per-unit and #-units-sold drivers instead of accumulation forecastsForecasting financials throughout different company units together opposed come looking just at consolidated financialsAnalyzing assets and also liabilities in much more detail (i.e. Leases, pensions, PP&E, etc.)Breaking out financing right into various tranches with much more realistic pricingLooking in ~ quarterly or monthly results rather of annual results

Practically speaking, the much more granular a model, the longer and more difficult it will certainly be come understand. In addition, the likelihood of errors grows tremendously by virtue that having more data. Therefore, thinking about the model’s structure — native the layout the the worksheets come the layout of separation, personal, instance sections, formulas, rows and columns — is an important for granular models. In addition, integrating formal error and “integrity” checks have the right to mitigate errors.

Financial version flexibility

The other main determinant for how to framework a financial version is its forced flexibility. A model’s flexibility stems from how often it will be used, through how many users, and also for how plenty of different uses. A design designed because that a certain transaction or for a certain company requires far less adaptability than one designed for heavy reuse (often dubbed a template).

As you can imagine, a template have to be far an ext flexible 보다 a company specific or “transaction particular model. For example, say that you are tasked with building a mergers model. If the objective of the model is to analysis the potential salvation of Disney by Apple, girlfriend would develop in far less use than if its purpose was to develop a merger model that have the right to handle any type of two companies. Specifically, a merger model template can require the following items that space not required in the deal-specific model:

Adjustments to acquirer currencyDynamic calendarization (to set target’s financials to acquirer’s fiscal year)Placeholders because that a selection of revenue statement, balance sheet and also cash flow statement line items that don’t appear on Disney or apologize financialsNet operation loss analysis (neither Disney or Apple have actually NOLs)

Together, granularity and flexibility largely recognize the structural needs of a model. Structural needs for models with low granularity and also a restricted user base are quite low. Remember, there is a trade-off to structure a extremely structured model: time. If you don’t require to construct in bells and also whistles, don’t. Together you include granularity and also flexibility, structure and also error proofing becomes critical.

The table below shows the granularity/flexibility levels of typical investment banking models.

High flexibilityLow flexibilityHigh granularityLow granularity
Leveraged finance credit transaction modelMerger model template “one dimension fits all”Integrated LBO modelIntegrated DCF modelIntegrated mergers ModelIntegrated operation model
Trading comps templateTransaction comps template“Back of the envelope” accretion/dilution modelDCF “one pager”LBO “one pager”Simple operating model

Financial version present-ability

Regardless of granularity and flexibility, a financial design is a device designed to aid decision making. Therefore, all models have to have clearly gift outputs and conclusions. Since virtually every financial models will aid in decision-making within a range of assumptions and forecasts, an reliable model will allow individuals to quickly modify and also sensitize a range of scenarios and present details in a variety of ways.

Now that us have created a an easy framework for structuring models, it’s time to discuss details features of model architecture, error proofing, flexibility and also presentation.

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Financial model structure

Below, we lay the end the crucial elements that an effectively structured model, most of i m sorry will go a lengthy to method to improve the model’s transparency. As a model becomes more complicated (due to higher granularity and flexibility), it naturally becomes much less transparent. The best practices below will help to resolve this.


Color coding

Just about everyone agrees that color coding cells based on whether it hold a tough coded number or a formula is critical. Without color coding, that is extremely challenging to visually distinguish between cells that have to be modified and cells that need to not ( i.e. Formulas). Well built models will more distinguish in between formulas that attach to various other worksheets and also workbooks as well as cells that link to data services.

While different investment financial institutions have various house styles, blue is typically used to color inputs and also black is used for formulas. The table below shows ours recommended shade coding scheme.

Type of cellsExcel formulaColor
Hard-coded numbers (inputs)=1234Blue
Formulas (calculations)=A1*A2Black
Links to various other worksheets=Sheet2!A1Green
Links to various other files=Sheet1!$A$1Red
Links come data carriers (i.e. CIQ, Factset)=CIQ(IQ_TOTAL_REV)Dark Red

While everyone agrees that color coding is very important, maintaining up v it have the right to be a pains in indigenous Excel. It’s not easy to format cells based upon whether they are inputs or formulas, yet it can it is in done. One option is come use Excel’s “Go to Special” (covered in ours Excel Crash Course, i beg your pardon you have the right to enroll in here). Alternatively, shade coding is significantly simplified with a third party Excel add-in prefer Macabacus (which is go together with wall Street prep self-study products and also boot camp enrollments), funding IQ or Factset. This tools allow you come “autocolor” whole worksheet in one click.


Inserting comment (Shortcut Shift F2, see our vital Excel Shortcuts List) in cell is crucial for footnoting resources and including clarity to data in a model.


For example, a cell containing an assumption on revenue growth that came from an equity study report should include a comment with a recommendation to the research study report. So exactly how much commenting execute you need? Always err on the next of end commenting. No managing director will ever complain that a model has actually too plenty of comments. Additionally, if you’re top top a conference call and also someone asks how you come up with the number in cabinet AC1238 and also you blank, you’ll regret not commenting.

Sign convention

The decision on whether to use positive or an unfavorable sign conventions must be made before the version is built. Models in exercise are everywhere the location on this one. The modeler should choose from and clearly identify one of the following 3 approaches:

Convention 1: All income positive, all expenses negative.

Advantage: logical, consistent, renders subtotal calculations less error-proneDisadvantage: Doesn’t align v conventions used by publicly filings, % margin calculations appear negative

Convention 2: All expenses positive; non-operating revenue negative.

Advantage: consistent with publicly filings, % margin calculations show up positiveDisadvantage: an adverse non-operating income is confusing, subtotal calculations room error-prone, ideal labeling is critical

Convention 3: All prices positive except non-operating expenses.

Advantage: Avoids negative non-operating revenue presentation; margins evaluate to positiveDisadvantage: Presentation not internally consistent. Suitable labeling is critical.

Our recommendation is Convention 1. The reduced likelihood that error from less complicated subtotaling alone renders this our clear choice. In addition, among the most typical mistakes in modeling is forget to switch the authorize from positive to negative or evil versa when linking data across financial statements. Convention 1, by virtue of being the most visibly transparent approach, renders it much easier to track down sign-related mistakes.


Avoid partial entry (all models)

Hard coded numbers (constants) should never be installed into a cell reference. The danger below is the you’ll most likely forget there is an presumption inside a formula. Inputs must be plainly separated from calculations (see below).

One row, one calculation

Most investment banking models, choose the 3-statement model, depend on historical data to drive forecasts. Data need to be presented from left to right. The appropriate of the historic columns space the projection columns. The formulas in the projection columns need to be consistent across the row.

Use roll-forward (“BASE” or “cork-screw”) calculations

Roll-forwards refers to a forecasting technique that connects the current period forecast come the former period.

This strategy is really useful in including transparency to how schedules room constructed. Preserving strict follow to the roll-forward approach improves a user’s capability to audit the model and also reduces the likelihood of linking errors.

Write good (and simple) formulas

There is a temptation once working in Excel to create facility formulas. If it might feel good to handmade a super facility formula, the obvious disadvantage is the no one (including the author after being away from the design for a bit) will understand it. Because transparency have to drive structure, facility formulas should be avoided at all cost. A facility formula can often be broken down into multiple cells and simplified. Remember, Microsoft doesn’t charge you extra for using an ext cells! therefore take advantage of that. Listed below are some typical traps come avoid:

Simplify IF statements and avoid nested IFsConsider making use of flagsSimplify IF statements

IF statements, while intuitive and well taken by many Excel users, can become long and daunting to audit. Over there are several excellent choices to IF that top-notch modelers typically use. They include using Boolean logic together with a range of reference functions, consisting of MAX, MIN, AND, OR, VLOOKUP, HLOOKUP, OFFSET.

Below is a real-world instance of how an IF statement can be simplified. Cabinet F298 uses any surplus cash generated throughout the year come pay down the revolver, up till the revolver is completely paid down. However, if deficits are generated during the year, we desire the revolver come grow. While an IF statement perfect this, a MIN duty does it much more elegantly:

Revolver formula using IF statement

Revolver formula utilizing MIN

The revolver formula using MIN together an alternate to IF also holds up much better when additional complexity is required. Imagine the there’s a border on yearly revolver attract of $50,000. Look at exactly how we have to modify both formulas to accommodate this:

Revolver formula making use of IF statement

Revolver formula utilizing MIN

While both recipe are an overwhelming to audit, the formula making use of IF statements is more an overwhelming to audit and is more delicate to getting fully out that hand through additional modifications. That uses nested (or embedded) IF statements, which our feeble human being brains have a hard time with once there’s more than one or two.

Fortunately, Excel has made this a bit simpler in 2016 through the development of the IFS function, however our preference for relying on an ext elegant attributes remains. We invest a the majority of time in our Excel Crash course going end the many ways “IF alternative” attributes can be supplied to power-charge Excel.

Reduce date-related formula intricacy using flags

Flags describe a modeling an approach most beneficial for modeling transitions across phases that a company, job or transaction in time without violating the “one row/one calculation” consistency rule. Imagine you’re structure a design for a firm that’s contemplating bankruptcy. Every phase that the restructuring process has that own unique borrowing and also operating characteristics.

In our example below, the company’s revolver “freezes” when it goes right into bankruptcy and a new kind of take out loan (“DIP”) acts together the brand-new revolver till the firm emerges native bankruptcy. Additionally, a brand-new “Exit” basic replaces the DIP. Us insert 3 “flags” in rows 8-10 to output “TRUE/FALSE” based on the phase we’re in. This allows us come build really simple, continual formulas for each revolver without having to embed IF statements into each calculation.

In cell F16 the formula is =F13*F8. At any time you use an operator (like multiplication) on a TRUE, the TRUE is treated choose a “1” if a FALSE is treated favor a “0.” This way that the pre-bankruptcy revolver is the de facto revolver as soon as the pre-bankruptcy flag evaluate to TRUE and also becomes 0 once the flag evaluates to FALSE (starting in tower I in our example below).

The main benefit is that with the usage of just an extra 3 rows, we’ve avoided having to insert any sort the conditional tests in ~ the calculations. The same uses to the formulas in rows 20 and 204 — the flags have prevented a the majority of extra code.

Names and also named ranges

Another method many modelers alleviate formula intricacy is by making use of names and named ranges. We strongly caution against using names and also named ranges. Together you’re probably beginning to sense, over there is constantly some kind of tradeoff through Excel. In the instance of names, the tradeoff is that as soon as you surname a cell, friend no much longer know exactly where it is without going come the name manager. In addition, unless you room proactively deleting surname (you aren’t), Excel will certainly retain these names even when you delete the called cell. The result is that a record you’re using this particular day to develop a DCF has dozens that phantom names indigenous prior versions of the model, causing warning messages and confusion.

Don’t calculate on the balance sheet — link from sustaining schedules.

In investment banking, your financial models will typically involve jae won statements. Ideally, her calculations room done in schedules separate from the output you’re functioning towards. Because that example, it’s preferable the you don’t perform any calculations on the model’s balance sheet. Instead, balance paper forecasts have to be determined in separate schedules and linked right into the balance sheet as shown below. This consistency help in the transparency and also auditing the a model.

How to reference cells

Never re-enter the very same input in different places

For example, if you’ve inputted a company name in the an initial worksheet that the model, referral that worksheet name — don’t re-type it into the other worksheets. The very same goes because that years and dates gone into into a column header or a discount rate assumption used in a range of various places in the model. A much more subtle instance of this is difficult coding subtotals or EPS when you can calculate it. In various other words, calculation whenever possible.

Always link directly come a source cell as it is more an overwhelming to audit “daisy chained” data

The one major exception to this is as soon as “straight-lining” base period assumptions. Because that this, go ahead and also daisy chain. The factor is that straight-lining base period assumptions is an implicitly assumption, which can change, thus making it feasible for certain years in the projection to ultimately finish of through different assumptions than various other years.

Avoid formulas that contain referrals to lot of worksheets

Compare the two photos below. The is more difficult to audit the formula in the first image since you’ll should bounce approximately to various worksheets to see the precedent cells. At any time possible, carry the data from various other worksheets right into the active worksheet where the calculate is made.

Link presumptions into standalone cell in the calculation and also output sheets

If you’re working with bigger models and also you have assumptions that should be referenced from a different worksheet, consider linking assumptions directly into the worksheet where you’re using them, and color code them as a distinct worksheet recommendation link. In other words, don’t have an entry reference installed into a calculate (i.e. =D13*input!C7). Instead, use a clean referral =input!C7 and a different cell for the calculation. While this creates a redundant cell reference, it preserves the visual audit-ability of the model tab and reduces the likelihood that error.

Avoid linking files

Excel enables you to link to various other Excel files, but others can not have accessibility to the linked-to files, or these documents may get inadvertently moved. Therefore, protect against linking come other files whenever possible. If linking come other documents is a must, be vigilant about color coding all cell recommendations to various other files.


One lengthy sheet beats many brief sheets

A lengthy worksheet way a most scrolling and less intuitive compartmentalizing the sections. On the various other hand, many worksheets substantially increases the likelihood the linking errors. There’s no hard and fast rule around this, yet the general bias should it is in toward a longer sheet over multiple, shorter worksheets. The dangers of mis-linking across worksheets is rather real and hard to mitigate, if the worries of cumbersome scrolling and also lack that compartmentalization associated with long worksheets deserve to be substantially mitigated through Excel’s separation screen functionality, clean headers and links native a cover sheet or table of contents.

Don’t ‘hide’ rows — ‘group’ them (and carry out it sparingly)

A model often has rows v data and also calculations that you carry out not want to show when the model is published or once you dough the data into a presentation. In this situation, it’s often tempting to hide rows and also columns for a “cleaner” presentation that results. The risk is that once the design is passed around, it is very easy to miss (and potentially paste over) the hidden data.

Keeping input (assumptions) together (for high-granularity models)

Nearly every financial modeling skilled recommends a standard that isolates every one of the model’s hard-coded presumptions (things favor revenue growth, WACC, operating margin, interest rates, etc…) in one plainly defined ar of a model — typically on a specialized tab dubbed ‘inputs.’ These should never be commingled through the model’s calculations (i.e. Balance sheet schedules, the jae won statements) or outputs (i.e. Credit and also financial ratios, charts and summary tables). In other words, think of a version as made up of three clearly identified and also physically be separate components:

Assumptions → Calculations → Output 


Consistent, trusted architecture: Once a version is built, the user has only one location they need to go to change any assumptions. This creates a consistent distinction between locations in the design that the user works in vs. Areas the computer works in.Error mitigation: Storing all presumptions in one location makes it far less likely that you’ll forget to remove old presumptions from a prior evaluation and inadvertently bring them right into a new analysis.

Yet regardless of these advantages, this practice has never to be widely embraced in investment banking.

One factor is simply poor practice. part models would clearly benefit indigenous an input/calculation/output separation, however are often constructed with no forethought provided to structure. Imagine building a house without any pre-planning. Sure, you’ll prevent the ache of all that planning, yet you’ll encounter unexpected problems and also end up redoing work or adding complexity by working around what’s currently been done. This problem is rampant in invest banking models.

Another factor is that many invest banking models are merely not granular enough to merit the added audit trail and legwork. The analyses bankers carry out are often broader than they space deep. Because that example, a pitch book might existing a valuation making use of 4 different valuation models, however none the them will be overly granular. Typical investment banking analyses like accretion dilution models, LBO models, operating models and DCF models typically don’t delve into detail beyond the limits of windy filings and straightforward forecasting. In this case, moving ago and forth from input come calculation to output tabs is unnecessarily cumbersome. As lengthy as you’re diligent around color coding, placing presumptions on the very same sheet and right below calculations is preferable in smaller models since your assumptions are visually right alongside the output, making it easy to check out what’s driving what.

The other consideration is the number of a model’s users. The advantages of the “inputs together” strategy grow v the variety of a model’s plan users. When girlfriend have countless users, your design will inevitably be supplied by human being with a wide selection of modeling proficiency. In this case, a consistent and also reliable framework that stays clear of users from obtaining into the offal of the version will alleviate error. In addition, it will also reduce the amount of time a user needs to spend in the version — a user can simply situate the area for inputs, to fill them in, and also the version (in theory) will work. That said, regardless of attempts by IB groups to standardize models, numerous investment bank models are basically “one-offs” that get materially modified because that each new use. As well as comps models which lend themselves to becoming templates, most models space used mainly by their initial authors (usually an analyst and also associate) who know the design well.

The bottom line on maintaining inputs every together

Unfortunately, there’s no developed benchmark for when it provides sense to different out assumptions. The ideal approach depends ~ above the scope and also goal that the model. Because that a an easy 1-page discounted cash flow analysis not plan for constant reuse, it is preferable to embed inputs throughout the page. However, because that a big fully-integrated LBO version with many debt tranches to be used a group-wide template, the services of maintaining all inputs with each other will outweigh the costs.

No spacer columns between data

Elevator jumps

In lengthy worksheets, dedicating the leftmost column for put an “x” or another character in ~ the start of schedules will make it easy to quickly navigate from section to section.

Annual vs quarterly data (periodicity)

Most investment banking models room either quarterly or annual. For example, a U.S. Same research income model will always be a quarterly model since one of its vital purposes is to projection upcoming earnings, which are reported by this firm quarterly. Similarly, a restructuring model is typically a quarterly version (or even a monthly or weekly model) since a crucial purpose that this model is to know the cash flow affect of operational and financing alters over the next 1-2 years. On the other hand, a DCF valuation is a long term analysis, with at the very least 4-5 year of explicit forecasts required. In this case, an yearly model is appropriate.

There are likewise models for which both quarterly and annual durations are useful. For example, a merger version usually requirements a quarterly period because a key goal is to understand the influence of the acquisition on the acquirer’s jae won statements end the next 2 years. However, attaching a DCF valuation to the combined merged companies may additionally be desired. In this case, a feasible solution is to roll up the quarters right into an yearly model and also extend those annual forecasts more out.

When identify a model’s periodicity, keep in mental the following:

The version must be set up v the the smallest unit of time desired, with longer time periods being aggregated (rolled up) indigenous those shorter time periods. If you’re building an integrated financial statement model in which you desire to check out quarterly and annual data, projection the quarterly data first.Keep the quarterly and annual data in separate worksheets. It is simpler to audit what’s walk on when periods aren’t commingled. Additionally, commingling quarterly and also annual data in one worksheet will certainly either A) pressure you to violate the one row/one formula consistency ideal practice or B) girlfriend will need to jump through some stunner hoops to keep the consistency.


Circularity describes a cabinet referring to chin (directly or indirectly). Usually, this is an unintended mistake. In the simple example below, the user has accidentally included the sum total (D5) in the sum formula. Notification how Excel becomes confused:

But occasionally a circularity is intentional. For example, if a version calculates a company’s interest expense based on a cell the calculates the company’s revolving debt balance, yet that revolving debt balance is itself established by (among various other things) the company’s costs (including attention expense), then we have a circularity:

The reasonable of together a calculation is sound: A company’s take out loan needs should take into account the interest expense. As such, many investment banking models save intentional circularities favor these.

Since unintended circularity is a mistake to avoid, the consumption of intentional circularity in gaue won models is controversial. The problem with knowingly circularity is the a special setup must it is in selected in ~ ‘Excel Options’ to avoid Excel from misbehaving when a circularity exists:

Even with these setups selected, Excel can become unstable when taking care of circularity and also often leader to a design “blowing up” (i.e. The model short-circuits and populates the spreadsheet through errors), requiring manual treatment to zero the end the cell containing the source of circularity:

While the basic logic because that wanting to incorporate a circularity right into a model may be valid, circularity troubles can lead to minutes, if not hours, the wasted auditing time do the efforts to find the source(s) of circularity to zero castle out. There are numerous things modelers can do to much better cope through circularity, many notably the creation of a basic circuit breaker, which creates a main place in the design that “resets” any type of cell include a circularity or wrapping an error-trap formula (IFERROR) roughly the formula the is the resource of the circularity.

Circuit breaker or one IFERROR error-trap

When building an intended circularity, girlfriend MUST build a circuit breaker and plainly identify every the circularities in your model. In our simple example, we placed a circuit breaker in D17 and altered the formula in D8 for this reason the circularity is zeroed out once the user switches the breaker to “ON”:

Approach 1: including a circuit breaker toggle 

An alternative approach is to merely wrap one IFERROR role around the source of the circuilarity. Once the model short circuits, the IFERROR function evaluates come the FALSE condition and also populates the design with 0s automatically. The main downside come this method is that they do finding unintended circularities harder. That’s since you have the right to never clearly turn the breaker ~ above or turn off – the IFERROR does the automatically. The said, as long as all circs room handled with an IFERROR function, the design will never blow up.

Approach 2: adding an error trap making use of the IFERROR function

Bottom line: come circ or not to circ?

Despite the circuit breaker and error trap solutions, many believe it is preferable to just outlaw all circularity indigenous financial models. Because that example, the means to altogether avoid the intentional circularity in the example above is to calculation interest expense using start debt balance. Because that quarterly and monthly models with minor debt fluctuations, this is desirable, but for an yearly model with a big forecasted change in debt, the “fix” deserve to lead come a materially different result. Therefore, we execute not believe in a blanket “ban.” Instead, we provide the following basic guideline:

A circularity is only OK if all the following conditions are met.

It is intentional: At danger of stating the obvious, you must understand exactly why, where, and how the circularity exists. The instance described above is the many common source of circularity in gaue won models.You have “enable iterative calculation” selected in your Excel settings: This tells Excel the circularity is intentional and ensures Excel doesn’t throw up one error and populate the whole model through random zeros everywhere.You have actually a circuit breaker or error trap formula: A circuit breaker or error trap formula ensures the if the document gets unstable and also #DIV/0!s begin populating the model, there is an easy and clear method to settle it.The version will not be shared with Excel novices: Circularities, even with a circuit breaker, can create confusion because that Excel individuals not acquainted with it. If the version you are structure will be mutual with clients (or a controlling director) that like to acquire into the model however are normally unfamiliar v Excel, prevent the circularity and save you yourself the headache.Don’t use macros

Keep macros to an pure minimum. Very couple of people know just how macros work, and some customers cannot open documents that use macros. Every extr macro is a action closer to making your design a “black box.” In invest banking, this is never a great thing. The only macros regularly tolerated in banking models are publish macros.

Error checking

Excel is an exceptional tool. Unlike software specifically design to execute a particular set of work (i.e. Genuine estate invest software, accounting software), Excel is a empty canvas, which makes it easy to carry out extremely complex analyses and also quickly construct invaluable tools to help in jae won decision making. The downside below is that Excel analyses are just as great as the design builder (i.e. “Garbage in = garbage”). Design error is for sure rampant and has serious consequences. Let’s rest up the most typical modeling errors:

Bad assumptions: If your presumptions are faulty, the model’s output will certainly be incorrect nevertheless of just how well it is structured.Bad structure: even if your model’s assumptions are great, failure in calculations and structure will lead to incorrect conclusions.

The key to mitigating #1 is to present results with plainly defined arrays of assumptions (scenarios and sensitivities) and make the assumptions plainly defined and also transparent. Break models out right into inputs→calculation→output help others conveniently identify and an obstacle your assumptions (Addressed in detail in the “Presentation” section above). The far more pernicious modeling error is #2 because it’s much more daunting to find. Together you can imagine, the problem grows exponentially as the model’s granularity increases. This is why building error checks into your model is a an essential part of model building.

Build in error checks

The most usual error inspect in a financial design is the balance examine — a formula experimentation that assets = liabilities + equity:

Anyone who has actually built an integrated financial statement version knows it is fairly easy to do a an easy mistake that avoids the model from balancing. The balance check clearly identifies come the user the a mistake has been made and also further investigation is required. However, over there are many other areas of models that room prone to error and thus could merit error checks. If every version will need its own checks, several of the an ext common ones include:

Ensuring resources of funds = provides of fundsEnsuring the quarterly results add up to annual resultsTotal projection depreciation cost does not exceed PP&EDebt pay-down does not exceed impressive principalFavor direct calculations end “plugs”

Below we show two typical ways the users collection up a sources & supplies of accumulation table in gaue won models. In both approaches, the user accidentally recommendations intangible assets. In approach 1, the not correct data is linked into D37. The model notices the sources do not equal uses and throws one error blog post in D41. The 2nd (and same common) strategy structurally set D52 equal to D47 and uses D49 as a plug to ensure resources and uses always equal. Which approach do girlfriend think is preferable? If you guessed the an initial approach, you are correct. The problem the 2nd (“plug”) technique is that due to the fact that of the mis-linking in D50, the model incorrectly calculates the amount of secured loans forced for the transaction, and no error is identified.

Whenever a direct calculation is possible, usage it, together with an error inspect (i.e. “do resources equal uses?”) rather of building plugs.

Aggregate error checks right into one area

Place error check close to where the pertinent calculation is acquisition place, but aggregate all error checks into a central easy to check out “error dashboard” that clearly show any errors in the model.

Error trapping

Models that call for a many of flexibility (templates) frequently contain areas the a user may not need now, however will need down the road. This contains extra line items, extra functionality, etc. This creates room because that error due to the fact that Excel is handle with empty values. Formulas choose IFERROR (and ISERROR), ISNUMBER, ISTEXT, ISBLANK space all beneficial functions because that trapping errors, specifically in templates.


Cover Page and TOC

When a model is design for use by much more than just the model builder, include a sheathe page. Cover page need to include:

Company and/or project nameDescription that the modelModeler and also team contact information

Include a table of materials when the model is sufficiently huge to merit it (a good dominion of thumb is more than 5 worksheets).

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Worksheet design

Label worksheets by the nature of the evaluation (i.e. DCF, LBO, FinStatements, etc…). Tabs should circulation logically indigenous left to right. When adhering to the inputs→calculations→output approach, shade the worksheet tabs based upon this division:

Include the company name on peak left that every sheetInclude the paper purpose, script selected (when relevant), scale and also currency prominently below the firm name on every sheetPage setup for printing: once a paper is too lengthy to right in one page, the height rows containing company name, objective of the page, currency and scale should be displayed on peak of each page (select “rows come repeat at top” (Page Layout>Page Setup>Sheet)Include document path, page number and date in footerScenarios and also sensitivities

The function of structure a version is to carry out actionable insight that wasn’t otherwise readily visible. Financial models melted light on range of vital business decisions:

How go an acquisition change the gaue won statements of an acquirer (accretion/dilution)?What is a company’s intrinsic value?How lot should an investor add to a project offered specified return requirements and risk tolerances?

Virtually all investment banking models depend on forecasting and assumptions to arrive at the outputs presented to clients. Because presumptions are by meaning uncertain, presenting the financial model’s calculation in ranges and based top top a variety of various scenarios and also sensitivities is critical. In this post about scenario evaluation and this post about using data tables because that sensitivity analysis, we deal with the 2 most effective ways to existing financial outputs in jae won models.

Conclusion and further reading

We created this overview to administer a frame applicable to investment bank models. Because that those that want to dive deeper right into building details investment bank models, think about enrolling in our flagship jae won modeling program. Because that those that desire to acquire into the weeds that modeling theory, i recommend the following texts: