Passed CFA Level I

I just checked my CFA results this morning. I passed! Pass rate this year was higher, 46%.

Now that I've passed, I'd like to recommend the prep service I used. While Stalla and Schweser boasts tough questions etc. I thought they were too expensive (more expensive than the exam itself) and unnecessarily difficult.

Krikor, a professor from York, is the coach for Passmax, a Toronto based CFA prep course. His style is very to the point and wasted no time (not just doing "the toughest questions" but doing the questions where you have a higher chance of improving). His day-of services were a god send for stressed out candidates like myself. I had failed the exam once in December 2008 and his coaching really made the difference for passing the second time around.

I am not being paid or solicited for a recommendation for his service, but think that the finance industry as a whole would benefit from having more CFA candidates as well as proper assistance in learning financial concepts as taught by Krikor.

Analyst Exchange Financial Modeling

For those of you who don't already know, I'm currently in NYC and have recently finished my financial modeling course with the Analyst Exchange.

While taking an Engineering and Management degree exposed me to all the core business courses (finance, accounting, marketing, HR etc) and the CFA focused even more so on finance, it was refreshing and confidence inspiring to be able to take a class where the principles we learn move us away from the strictly academic and theoretical into the real and practical.

I'd recommend this program to anyone who was interested in making active use of their finance knowledge and who wanted to have an edge making their entrance into the world of finance.

As I'm quite happy with my experience, I thought I'd pass it along for anyone else who was looking into similar training programs.

[DISCLAIMER] This advertisement was unsolicited and non-compensated.

Chapters Indigo - Model with LBO Module

I've been learning a lot in my courses, but I haven't had a chance to post any good lessons lately because I've been so busy.

However, last night, I took some time off to complete a model using everything we've learned so far. Although the model isn't "complete" (synergies from the LBO are not currently included), this model includes projections, debt schedules, working capital schedules, depreciation schedules, and even a model for leveraged buyouts and valuation.

There are plenty of comments outlining major assumptions in how these numbers were derived. I would encourage you to play with the numbers to understand the relationships in the model work for valuation purposes.

[DISCLAIMER]
While the numbers look "good" (valuations are in the 20's and IDG:Indigo is trading at around $19) this information is provided without warranty as a strictly academic exercise only. Trading on this information is risky (beyond the standard business risk) as well as foolish and reckless.

I am not responsible for you using the model for the purposes of trading or other investment decisions. Consult a qualified financial adviser before making any investment decisions.

Chapters Model with LBO Module

Information for this model is based on the 2009 Chapters / Indigo Annual Report.

[Note] This spreadsheet contains circular references in order to calculate exact interest expense iteratively (using real cash gains from reduced interest expense to further reduce interest expense). Excel is usually configured to allow you to do this, however, you may have to change your settings to allow circular references.

Teaching at the Analyst Exchange

We were doing our training earlier last week when we approached terminal values. Although we were shown the formula, I mentioned that I could prove how the formula was derived from first principles (as well as outline the fundamental assumptions for when this formula works ... and falls apart). It's a very elegant solution that explains terminal value as well as enterprise value multiples.

The math used was based on my post about geometric sequences and series and extended to encompass finance discounted cash flows.

I'm requesting a copy of the video so I can post it on Youtube and this blog. Please excuse my attire. It was casual Friday.

The Wall Street MBA, by Reuben Advani

As part of the training program, we've been given a copy of Reuben Advani's The Wall Street MBA. It's a really good primer for material in the MBA and good casual reading for people who want to stay a bit sharper on the subway.

Advani uses colorful examples from current events to describe accounting and corporate finance concepts, including a chapter dedicated to fraud and manipulation (some topics of which are covered in this blog including profit smoothing).

More advanced readers would probably still benefit from the second half of the book, covering more complicated topics such as derivatives, arbitrage, hedge funds and M&A.

While Advani's book covers a broad and comprehensive range of topics, it's depth is good enough to get a feel without feeling overwhelmed (although some topics like inventory control, LIFO, FIFO etc could use a bit more 'time').

EPS Accretion (Dilution) in Acquisitions

There are two major ways to fund acquisitions. Either raise debt (borrow money) or raise equity (get owners to contribute more capital or find more investors).

In each case, there are major factors which affect the ending EPS.

In debt, the largest effect on the EPS through the income statement is the interest expense. For a large enough debt issuance, the interest expense can rise to a level which adversely affects EPS (dilution).

In equity, the largest dilution effect on EPS is from the dilution through the number of outstanding stocks (equity raised divided by the market value of the stock).

In each case, it requires M&A analysts to do sensitivity tests to find the effect on dilution based on different premium values above the stock value as well as the amount of leverage applied (how much capital should be raised by debt versus equity).

Assuming rational investors, the sensitivity analysis should provide a fairly definitive decision criteria for the acquisition decision as well as guidance for the amount of leverage to be applied.

Acquisitions Basics

There are two major types of acquisitions, acquisitions of assets and acquisitions of equity.

Acquisitions of assets involved purchasing the property (like buying the parts of a company), whereas acquisitions of equity includes intangibles such as brands, management teams, IP and customers lists, however you are subject to hidden liabilities (buying the company whole as is).

Acquisitions of Assets bolster your PP&E. It can often make sense if a company's value is mostly derived from the physical assets (example: a power company composed of power plants), but Acquisitions of Equity can provide management value added (especially in service companies such as consulting firms etc).

Acquisitions usually result in either an accretion or dilution of earnings which is of paramount importance in the proforma analysis.

In planning for M&A activity, there are some fundamental questions which must be looked at:

1. What should we pay? What model will we use to determine a value? Valuation Multiple? Premium on share price?
   
2. Where will we get the money? LBO?
3. What will we look like after the merger is complete? What are we getting? Proforma analysis with a focus on PP&E, WC and Def Taxes and other operational accounts of value as well as strategic synergies.

Using Operating and Activity Ratios as a basis for Extrapolation

They say that Financial Modeling is one part science and one part art. While the physics of finance is fairly well known (formulas to calculate DCF's, NPV's, IRRs, and ratios), it can sometimes be difficult to project or determine operating levels in the future (which is critical to determining the present value that an asset is worth.

Extrapolation is a risky but rewarding game (and a necessary evil). But how can it be done appropriately? Unlike pure math in which derivatives (in the sense of functions dx/dy and not in the finance sense of value 'derived' from another asset) can be used with various regression analysis models, the human component of business makes pure mathematical extrapolation trickier to say the least. By 'human component' what do I mean? Although we create budgets, how will things change? Will people like and buy our new product lines? Will we have major changes in our HR due to various forms of attrition? It is therefore critical to include assumptions in the math of our model (as previously mentioned) to understand the senstivities of our model.

For instance, how can you predict where your sales numbers will be next year? There are some option.

• The standard assumption would be to grow sales by the average of the past 3 years (SEC regulation states last 3 years annual reports, 10k's, must be published.) - Arithmetic or Geometric (conservative) average
• Use last year's growth if previous years were unstable or volatile and not reflective of current environment
• Other projected number (aggressive) for a new product line expected to drive sales

Or how about operating and working capital? Well, using our CFA formulas for turnover and days on hand, if you assume that your operational efficiencies remain stable (or use one of the above methods to extrapolate a value), you can project out your budget based on that.

Check out my consulting post on operating efficiencies and cash cycle.

[Example] For the year finished, say 2008, if the AR is 1,000, Revenue is 10,000. If your sales grows at 10% per year, what should your budget reflect for sales targets in terms of Revenue and AR?

[Solution] Your DSO would be ($1,000/$10,000) * 360 days or 36 days. If you assume that your revenue grows at 10%, next year's Revenue will be 11k and if your DSO remains the same, your target AR should be $1,100. This method can be used to project out into future years.

By extension, assume that you expect to collect most of your AR within 30 days (DSO = 30), for the same revenue, your new target AR would be DSO = (AR / REV) * 360

so AR would be DSO * REV / 360 or 30 * 11k / 360 = $916.67
Note it has gone down from $1,100 because if you are collecting faster, your AR account should be smaller.

Similarities Betwen Financial Modeling and Software Development

Our training program has started and we've been going over the basics of financial modeling.

One thing I've noticed with financial modeling (which should actually come as no big surprise) is the similarity with developing software.

Software development concepts that are portable (and important) for financial modeling:

• Modularity - Portability of code. Being able to use one formula in another area and putting pieces together
• Functions and variables - No hard coding. Having computed values feed into each other so that changes are immediately propagated throughout the model (without having to tediously consume time readjusting calculations - a huge waste of time)
• Memory addressing and pointers - Cell references and pointer arithmetic, arrays and vectors

Good programming practices such as adding comments to describe assumptions, keeping documentation and understanding the underlying fundamentals of the math (and what can break the formulas and models) is critical to understanding how robust your model is. People who have studied computer science will probably be familiar with many of the above terms and concepts.