Showing posts with label Financial Model. Show all posts
Showing posts with label Financial Model. Show all posts

Friday, January 10, 2014

Financial Statement Flow

Having a strong understanding of the “flow” through financial statements is essential in the valuation process. One must create forecasts and make assumptions that will impact pro-forma financials and should be able to identify how these will flow through the three primary financials. I thought it would be worthwhile to create a post covering the basic flow between each of the primary financials. As with many of my posts, this will have an emphasis on valuation uses and therefore will include certain details that are of particular concern to valuation modeling. Enjoy.

To help guide our conversations, I have created a simple graphic that outlines the most important flows between statements.  I will reference these flows and their colors through the post to help the reader gain a better understanding.


 
Due to the web of flows that is created here, I will start at the top of the income statement and work my way through these in what will hopefully be a coherent manner. Let’s get started.

The income statement starts with revenue less Cost of Goods Sold (COGS) to get gross income and then Sales, General and administrative (SG&A) along with Depreciation and Amortization (D&A) expenses are subtracted to get earnings before interest and tax (EBIT). In some financials D&A in consolidated within SG&A so be on the lookout for this. D&A (purple line) has two primary flows, first of which is to the balance sheet into the Accumulated Depreciation account. The amount of D&A expense will be added to the accumulated depreciation account to calculate Net PP&E. Remember too that only the “D” portion will flow into accumulated depreciation account, not the amortization. If a firm has no intangible assets to amortize, this is easy; however if they consolidate this you might have to dig into the footnotes to determine what amount is actually attributable to depreciation. The second flow for D&A is into the Statement of Cash Flows as an add-back to operating cash flow. Since D&A is a non-cash expense, it must be added back to net income.

Now let’s look at Interest Expense and Income (orange and brown lines). Interest Expense/Income can be found as a line item on historical financials, thus this commentary only applies to forecasting future financials. The general rule of thumb is to calculate interest expense as the average debt—(beginning balance+endining balance)/2—multiplied by the interest expense for the given debt. The same calculation is used for interest income but based on the average cash balance. You can also see the dark orange flow line from payments and issuance of Long-Term Debt (LTD), this will impact the balance and thus the interest expense.

Net Income (NI) is arguable the most important flow to understand. NI is represented by the light-red line and flows into two primary areas. First, NI is used as the starting basis for the indirect cash flow statement creation. The second flow is one that is most often forgotten, NI flows into the Retained Earnings on the balance sheet. Jumping over to the statement of cash flows, we can also see the flow between dividends under the cash flow from financing section to retained earnings (dark red line). Dividends paid will reduce the retained earnings balance while net income will increase it.

Let’s now turn out attention to some balance sheet accounts that have yet to be addressed. The Accounts Receivable (A/R), Inventory, and Accounts Payable (A/P) are all considered working capital (W/C). There may be other items such as accruals, however this is a simplified example. The change in these account balance (light blue) will flow into the statement of cash flows under the cash flow from operations section. I used the term “delta in W/C” to indicate that the change in these could either be an increase in cash flow or a decrease in cash flow. If there is an increase in net working capital (current assets less current liabilities) then this will be a use of cash and therefore a subtraction from net income; the opposite applies if it was a decrease in net working capital. We must also remember that in this instance the net working capital calculation does not include cash.

Next let’s look at the Property, Plant and Equipment (PP&E) account on the balance sheet. We can see the flow between the investing section of the statement of cash flows and the PP&E account on the balance sheet (yellow). If a firm has CapEx it will be an outflow of cash on the statement of cash flow but will be capitalized as an asset and added to PP&E on the balance sheet. Conversely, if a firm sells a piece of equipment it will be a cash inflow on the statement of cash flows while it will reduce the PP&E account on the balance sheet (both the PP&E and accumulated depreciation will be reduced as they relate to the asset being sold).

Lastly, we take a look at the bottom of the statement of cash flows to see that the ending cash balance (green line) will flow back to the balance sheet for the respective period ending. The beginning cash balance comes from the cash balance on the opening balance sheet (not shown in the image).


While this is a very simplified explanation of the flow between the statements, I do hope it puts its all in prospective and helps you better understand the process. Again, I did not list every single flow, only those most important to creating pro-forma forecasted financials. If you have questions or need clarifications, feel free to ask. 

Sunday, December 22, 2013

Simple Consolidated Financial Statement Model

 
The consolidated financial statement (CFS) model serves as the basis for creating pro-forma projected financial statements. It also is the foundation to both a discounted cash flow (DCF) and leveraged buyout (LBO) valuation model. These can vary in complexity depending on the needs of the end user and while most contain key elements, the actual design will vary. After a class discussion about CFS in my graduate program, I decided to create a simple example starting with a blank sheet and using the figures from the class as a foundation for model. 


To begin with, I will provide a summary of each seven sections created. Following this, I will offer some advice for creating models such as these, including errors to watch out for. Lastly, a short list of design features and their basic explanations has been included to assist the user in their understanding of the model.


The Seven Sections

Within this consolidated financial statement model, I have included seven sections. These include not only the three primary financial statements, but also supporting schedules. The first statement is a key ratio summary for the entire model. This was included as the first section to allow the user to quickly review the financial health of the firm over the modeled period.

The next section is the consolidated income statement. This section creates a pro-forma income statement that includes two historical years and seven projected years. The total revenue is forecasted based on an annual expected growth rate and COGS is based on a percentage of sales remaining constant from 2015E through 2021E. R&D and SG&A expense are calculated as a percentage of sales with independent calculations for each year. The tax rate is entered in the left side of the tax column; however, there is an annual tax override line which allows users to change the effective tax rate for any year. In the absence of this metric, the model uses the stated rate from the left column. Dividends are calculated on an annual per share basis and shares outstanding are expected to remain constant from 2013A.

The balance sheet is very standard with inputs feeding in from other supporting sections and does not warrant any detailed explanation. One noteworthy area is the inflow from the working capital section into the current assets and current liability section. Also the short-term and long-term debt flows in from the debt schedule. The cash flow statement is very much the same. The primary details that should be noted is the inflow from the debt schedule for the financing section of cash flow statement along with the inflow of CapEx from the deprecation schedule.

The Working capital schedule outlines the expected days sales outstanding (DSO), inventory turnover days and days payables outstanding (DPO) for each of the forecasted periods. From these metrics, the forecasted account balances can be calculated. The change in net working capital then flows back into the cash flow statement under changes in cash flow from operations.

The depreciation schedule begin with the forecasted CapEx for each period along with the expected useful life of the asset. The first portion of the schedule calculated book depreciation based on straight-line over the asset’s respective useful life and assumes zero salvage value. The second portion gives the accelerated deprecation values for each asset of each period. These are fictitious number created for illustrative purposes only, but would be representative of accelerated deprecation offered under tax purposes. The third portion computes the depreciation under the accelerated tax method for each respective period. Finally the difference is calculated. The tax rate is fed in from the income statement to calculate the deferred taxes. These are then fed into the balance sheet for either a deferred tax asset or liability.

Lastly the debt schedule. This section begin with the cash at the beginning of the year and then adds cash inflow available for debt repayment from the cash flow statement. There is a line item for the desired minimum cash, which is assumed to remain constant through the entire period; the end of this portion shows the excess cash available for debt repayment. For both the short-term and long-term debt portions the beginning balance is shown first.

Next the mandatory payment and optional payment is calculated. The mandatory payment is expected to remain constant through the model. The option payment is the maximum possible while still maintaining the minimum cash balance. In the event that the firm has less than the desired minimum cash balance, the additional cash is drawn from debt. The short-term debt is either paid or draw from first then any remaining transaction occurs in the long-term debt. The short-term debt also has a celling figure that limits the maximum draw on the credit line. For both the short-term debt and the long-term debt, there is a toggle figure for additional payments/draws; 0 = no additional, 1 = additional.

Interest expense for both short-term and long-term debt is calculated based on average balance based on the interested rate entered in the left column for each respectively. Lastly, the cash balance at the end of the year is calculated and interest income is calculated based on average cash balance. All of these figures flow back into the income statement, balance sheet and statement of cash flows.


Errors to Watch Out For

If you have ever created a financial model from scratch you know there are many little nuances that you must be on the look-out for. While I will not name all of these, I would like to point out a few that are key to success. First and foremost, you balance sheet must BALANCE! This can be a daunting task, but make sure it balances with primarily all formula driven figures (ie: do not go and change a number to “make it work”). Be very careful in your cash flows and debt schedule. These two are very interrelated and you must have them feeding from each other properly or you will never have a functional model. While I am not going to outline the exact process I used for this, I can recommend that you follow my formulas and see how the model is calculating. Lastly, use formula in every place possible. The more formula driven figures the easier it is to ensure a properly functioning model.


Key Feature of the Model

Just a few features to point out. I have created the entire model in a single sheet and used grouping to allow the user to collapse/expand the sections for ease of viewing. Having the entire model in a single sheet makes it significantly easier to both audit and write your formulas. If at all possible, I recommend keeping your model to a single sheet.

There is an “ERROR” checker embedded in the heading of each section. In the upper right hand corner is a formula that looks to see if the balance sheet balances for every period in the model. If it doesn’t, “ERROR” will appear in red font. In doing this, it will allow the user to be well aware of issues in the before making a decision using the model.

The date is entered for the first actual period under the “Key Financial Ratios” section and the next either period’s dates are calculated based on end of 12 months forward. The rest of the dates in the entire sheet are fed from this first set of inputs. This will ensure uniformity within the model.

Some formatting issues. Color coding is essential. Black font represents text or formula driven cells while blue font indicates a user input. This allows the user to easily distinguish between these two. Also, the only cell that was merged was the top heading, all other cells were simply centered. The cell width and height was left the same for each cell in the model, this is great for uniformity. Sum bars were used to indicate sums and a thick black boarder is at the bottom of each section. After the model was completed, the cell outlines were removed. Doing these simple formatting processes can really make your model look great and provide ease of use.


I hope you enjoyed this short narrative of my consolidate financial model. A link to this model can be found at the bottom of this post and under the Excel Files section of my blog. 

Wednesday, December 11, 2013

DCF Model #1

The Discounted Cash Flow model is a staple in any valuation tool kit. While these tend to vary from model to model depending on the user’s specific needs, there are a few common aspects. A DCF generally includes as assumptions section that is used to model the forecasted pro-forma financials. It is also common to include a sensitivity analysis for certain key metrics; these are Weighted Average Cost of Capital (WACC) and Discount Rate for most DCF models. Despite difference between models, at heart all DCFs are intended to estimate intrinsic value of an asset based on expected future cash flows discounted to present value.

To help me gain a better understanding of DCF models and to improve my Excel skills, I started with a blank spread sheet and went to work. I used sample DCF models that I have seen elsewhere for some of the formatting ideas, however I did fully create every aspect of this model. 


At this time, I am simply going to post the model for review. However, I do plan to have future posts that explain specific parts of this model. As a note, I used rough inputs for Microsoft to help better demonstrate the functionality of the model; however, there was no rigor put into the assumptions, they are for illustrative purposes only. 

Sunday, December 8, 2013

Simple Deferred Tax Asset & Liability Explanation

If you have ever taken a look at the balance sheet of almost any publicly traded firm, you will probably notice either a deferred tax asset or a deferred tax liability. While these are relatively simple to understand, I wanted to take a few moments to talk about how these are created and how they will impact not only the GAAP financials, but also the valuation process.

To begin with, what is a deferred tax account? In the U.S. all public companies are required to follow U.S. Generally Accepted Accounting Principles (GAAP) for financial reporting. However, for tax purposes, they follow a slightly different system of accounting. The difference in treatment for certain items can leave a firm actually having different amount of taxable income for accounting books purposes than for tax. Some of these differences are permeate other are simply temporary. Let’s discuss the differences and see some examples.

Permanent Differences
Certain expense are never taxable or are never tax deductible under U.S. Tax law. Take for example the investment in a municipal bond; the coupon stream for muni bonds is never taxable at the Federal level. If a firm is invested in a muni bond, they will show a higher book income versus a taxable income. Now let’s look at a federal fine for pollution. While the firm will use this as an expense for accounting purposes (hopefully extraordinary) they are not allowed to write it off on their tax income and therefore will have a higher tax income than book income. Since issues like these are never reversed, the income tax expense associated with these is factored in on the tax expense for the respective period.

Temporary Differences
While permanent differences are relatively simply and straight forward, temporary differences can be much trickier. Take for example the differences in depreciation methods. Most firms will choose to depreciate an asset under the straight line method, however under U.S. Tax law a system of depreciation called MACRS is used. This is essentially and accelerated deprecation system. This will generally cause the firm to have higher book taxable income in the early years and lower book taxable income in the later years versus the tax accounting income.

If a firm has a book taxable income of $1,000 but a tax accounting taxable income of $800 with a 40% tax rate what will they expense and what will they pay? For accounting purposes they will have income tax expense of $400; however, they will actually only have a tax liability of $320. Now since the difference is temporary and will reverse at a later time, they must account for this. To do this they will create an account-either an asset or a liability. From a valuation stand point, we must remember that the cash flows will be effected due to the differences between actual tax expense and tax liabilities paid in cash.

Since I think some of this can be a bit hard to explain in writing, I have decided to create a short screen cast. I hope this helps make this issue a bit clear.




I do understand that this is not an extensive explanation of deferred tax assets or liability, but I do hope it lays the foundation for a better understanding. 


Wednesday, November 20, 2013

Goodbye Mouse, Hello Keyboard

This post is for all the Excel nerds out there; hope you enjoy.

Since the second semester of my undergraduate program, I have been a huge fan of Microsoft’s Excel. I enjoyed creating spreadsheets to track my grades and I even got really creative and made my own GPA calculator. At the time, I felt like I knew a lot about Excel; boy was I wrong.

Fast-forward a couple of years and I now in my graduate program. A lot has changed during this time, one thing being my knowledge of Excel. Through my undergraduate program I used Excel almost daily for class projects or to track something in my personal life. This left me with a great understanding of the program and some of its capabilities. However, I still had much more to learn.

Once of my goals for the first part of my graduate program was to teach myself advanced financial modeling on Excel. I have completed FactSet’s DealMaven financial modeling course and am in the early stages of working through Breaking into Wall Street’s modeling course. One common these to these programs is the reference to keyboard shortcuts, which makes sense to increase productivity. However, one comment really stood out—it was said that you should attempt to avoid using the mouse as much as possible.

This, at first, seemed near impossible; yet I still attempted it. After a few weeks of working through modeling, I find myself being able to complete more and more tasks without the need for a mouse. And let me tell you, this has drastically increased my productivity within Excel. It is amazing how much faster you can work through the creation of a model once you know the key strokes to complete common tasks.

One really great Excel add-in that helped not only increase my productivity, but also made it easy to reduce use of the mouse was Macabacus. At the time of this post, I have only used the free version add-in and it is truly amazing. They provide intuitive short-cut keys to complete common modeling tasks such as changing formatting, font floor cycle and increase/decrease decimal places. Another great feature is their advanced formula audit tools. If you have ever build or worked with an in-depth Excel model you know how important it can be to audit your formulas—Macabacus makes this daunting task seem a little bit easier.


Long story short, this add-in is amazing and well worth checking out if you are an avid Excel user. Here is the link to their site with the free download; did I mention they offer some great free models? Enjoy. 

Thursday, October 31, 2013

30-Year Return Probability Simulation


Ahh, the wonder of statistics; a great tool they can be while remaining a complete mystery to many. Now take basic statistical methods and couple them with the power of Excel and what do you get? An interesting simulation! Okay, some might really question my motives for completing this; however they are actually quite simple, I am seeking to improve my modeling and simulation skills within Excel and what a better way than to practice.

I began the process by determine what I wanted to simulate, in this case it was the expected return of five assets over a thirty year holding period. Why five assets over thirty years? In all honesty, they were arbitrary; essentially they served as a simple basis for the creation of my model. In addition, the inputs that found in the download file have also been arbitrarily chosen for illustrative purposes only.  

After getting my basic idea down, I outlined how the simulation would work. I wanted to use expected return and risk as the metrics for each individual investment. Expected return would be measured as a percent change on an annual basis. Risk would be measured as the standard deviation of the expected return. In addition to these two important asset specific measures, each asset would be assigned a weight based on their allocation in the portfolio as a whole. Lastly, to help better represent the expected return on a monetary basis, a starting portfolio balance would be necessary. While a monetary measure was not essential, I felt it would allow a better “feel” for the expected returns as opposed to solely a percentage change being displayed.

The next step would be to create a random expected return for a single year, then repeat this over thirty years and compound the growth. In Excel I used the “=NORM.INV” function with requires the following syntax (probability,mean,standard_dev). The probability portion corresponds to the location on a normal distribution. The mean in this case would be the represented by the expected annual return for each respective asset. Standard_dev would be the assigned risk measure of standard deviation of return for each respective investment. By using the “=RAND()” functions, I was able to generate random numbers between 0 and 1 which represent probabilities. Now would be a great time for a quick Statistics-101 review.

A normal distribution is a commonly occurring continuous probability distribution in which data is equally distributed above and below the mean in a bell curve pattern. The central limit theorem states that under mild conditions the mean of randomly selected independent variables will be approximately normally distributed. For this model we assume the returns of each asset will be normally distributed. This essentially means that 99% of all returns will fall within plus or minus three standard deviations from the mean or expected return. This theory is widely used in practice with what is referred to as a normal distribution table. This table shows the relationship between the number of standard deviations above or below the mean and the cumulative probability of this occurring. For example, there is a 1% chance of experiencing a return that is three standard deviations below the mean. Since cumulative probability is used, a 99% probability would represent three standard deviations above the mean; this reflects that 99% of all occurrences fall below this level.

Back to the simulation. By using the excel functions as described above, a random probability will be drawn for each annual return for each individual asset. The Excel formula then takes this random probability and matches it with the respective location on the cumulative normal distribution table; this will yield the number of standard deviations above or below the mean the random sample will fall. Next, this randomly determined number of standard deviation is then multiplied by the standard deviation of returns for each respective asset and then added to the expected (mean) return to yield a random annual return for each asset.

To help better explain this, let us walk through an example. We will use “asset X” which has an expected return of 10% and a standard deviation of returns of 3%. Following the central limits theorem, 99% of all returns for this asset will fall between plus or minus three standard deviation or in this case 9%. Thus, it can be said with 99% confidence that the expected return will be between 1% and 19% (10-9=1, 10+9=19). Now if our random number generator in Excel returns .24 we will look this number up on a cumulative normal distribution table and find the corresponding standard deviations to be negative 0.0948. Next, we will take this number and multiply it by the standard deviation of 3% to get negative 0.284%. Lastly, we will add negative 0.284% to the expected return of 10% to get a random return of 9.7156%.

Clearly, this would be a dunging task if done with manual calculations, luckily we have Excel. This simulation completed the aforementioned process of determining a random return for each asset each year over thirty years. For each year, the respective return on each individual asset is weighted by its allocation within the portfolio to determine the total expected annual return based on the random returns. Finally, the ending value of the portfolio is determined based on the starting balance multiplied by one plus the annual return. This is completed over thirty years to determine the ending portfolio balance after thirty years of random returns calculated from the expected return of each asset and the respective standard deviations of return.

This process of 150 random returns based on expected return and risk for each respective asset yielded a possible outcome for the portfolio. While this would give us a single possible estimate, I wanted to allow for a deeper analysis of total possible outcomes. To do this, I used Excel’s Data Table function to create 1,000 replications of this process. This causes Excel to create the 150 random variables needed to calculate a possible outcome for a single set of thirty years and record the ending value as one data point then complete the process again to get a second data point, so on and so forth. Clearly, this would not be feasible to complete this process 1,000 times without the use of Excel; a total of 150,000 calculations were made.

After completing the simulation of 1,000 possible ending balances for the portfolio, I then calculated the mean value of the possible ending balanced of the portfolio, this served as the expected ending balance; the standard deviation was also measured off this sample. The compound annual growth rate (CAGR) was calculated by taking the expected ending portfolio balance and dividing by the beginning balance to determine the delta then taking the 30th root (for the number of years of returns being calculated).


Lastly, I wanted to also include a visual illustration of the return distributions using a histogram. I chose to use 201 bins with the expected return being the 101st bin. By using 201 bins, I was able to have 100 bins above and below the expected return. To determine width of each bin, I took the calculated standard deviation of the returns and multiplied it by two then divided it by 100. This allows the histogram to display return that fall within plus or minus two standard deviations of the mean; according to the empirical rule of normal distribution, two standard deviations will represent approximately 95% of all data points. 

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While this serves as a simple explanation of the process used to complete this simulation, I intend on creating a second post analyzing the results. I have included a link to download the simulation below. Enjoy.