I am not at all convinced as to whether MBA fin courses gives the correct/desired training for such careers. For starters they tend to be the over-simplified or the broad-overview kind. When I was at Stanford a bunch of my friends were in a Masters in management program and they had these required cross core-courses from the MBA program like corporate finance, DA, accounting and so on. And frankly, having a math heavy background I found those courses naive at best, due to the simplicity in the actual maths involved. Accounting is of course jargon heavy and once you get that straight, the rest is a walk in the park. DA which was probably the most feared course is also in reality a pretty simple one. One peculiar thing about DA though, is sometimes it doesn't exactly follow the probability laws (especially Bayes' Theorem) !!

And now I see my girlfriend doing her PhD in finance and the mathematics is extremely involved. A pretty decent grasp of real and complex analysis is almost mandatory. Theories developed on Mutual funds, ETFs and the varied kind of investing methodologies (value, growth, momentum) are very very math intensive. For example the starting point in the Stock market for fin/econ grads, the Black-Scholes model for option pricing, is stochastic to start with. It needs random walk kind of solutions (something like a Monte Carlo simulation for example) as it cannot be solved in a closed form deterministic manner. That makes me wonder whether MBAs going for their fin specialization actually have the expertise to deal with such sophisticated maths or do they stay more in the overview plane. If they do stay in the overview ball park, then how the heck do they perform their corporate jobs ?? Wouldn't an econ/fin PhD be a much superior analyst/trader simply because they have a much more thorough grasp of the subject matter.

And then I also hear of the numerous models that I-bank newbies/interns need to run on a daily basis. And curiously most of these models that they run are done with Excel. Now I have always believed (instilled by my co-advisor at Pennstate) that Excel is the stupidest black box that Bill Gates has ever designed (it is dumber that Windows, if you know what I mean). So what models do these I-bank whizzes run??? No sophisticated heavy duty modelling (especially stock price modeling which is a highly non-linear problem and notoriously unstable to solve) can be run on a single node PC on excel. All known computational and computing laws would be severely violated. I have exactly one friend in I-banking so I dont know the answer to these modeling thingy that they keep talking about. But I have some friends over at motley fool who are analysts for motley fool in their stock picking business, and they shared a model-running exercise of theirs.

I'll walk you through it since I presume that these are the typical Excel models that I keep on hearing about. The thing here is that one of their top equity holdings X has taken a severe beating, and they want to analyse whether buying more of this X at today's prices would yield a S&P 500 beating profitable return in the next 3-5 year time frame. So heres what they model in essence ( I highlight in red my comments from some feedback):

1. Trailing 12 Month (TTM) Revenue = $217.9M (from balance sheet)

2. Estimate 3 yr. Revenue Growth = 11% (Different bunch of numbers are plugged in for this based on their estimate/forecast depending on a myriad of macro-economic conditions, this is their estimate and not a hard data point)

3. TTM Revenue in 3 yrs. = $217.9M * (1.11^3) = $298.0M

4. Estimate Net Profit Margin =9.5% (Again Different bunch of numbers are plugged in for this based on their estimate/forecast depending on a myriad of macro-economic conditions, this is their estimate and not a hard data point )

5. Net Income in 3 yrs = $298.0M * 0.095 = $28.31M

6. Current Shares Outstanding = 6.4M

7. Estimate Share Dilution Rate = 2% (per historic levels)

8. Shares Outstanding in 3 yrs. = 6.4M * (1.02^3) = 6.8M

9. Estimate EPS (earning per share) in 3 Yrs. = $28.31M / 6.8M = $4.16

10. Estimate P/E ratio = 12 (This is reasonable for current growth level of 11% and 25% in favorable times. The P/E ratio might be higher, but let’s stay on the reasonable side, more different values to test here.)

11. Estimated Price in 3 Yrs. = $4.16 *12 = $49.92

Once they have a price target calculated they then go for potential return calculations based on current prices, essentially to identify favorable buying points:

Let’s look at buy target prices:

Expected Return Buy Target

--------------- ----------

15% $32.82

20% $28.89

25% $25.56

30% $22.72

And that in essence is a typical stock analysis. Not rocket-science level by any means is it, but almost wholly common-sense and logic driven. And then they add layers of complexity to this to come up with a ton of scenarios and potential outcomes/risk/profit analysis etc. I am beginning to think that this is what Excel modeling is all about. Correct me if somebody has more know-how on this.

Now hedge-fund traders though are a very different breed and I know for certain that they crank up huge computational power/time (statistically the biggest user of computational power in the US are : (1) defense (2) oil and gas industry (3) finance ) crunching sophisticated algorithms to come up with buy/sell triggers for equities/options etc. And again it is my feeling that the MBA wouldn't be a good fit here because of his over-view based background. But he might be a good interpretor of the numbers that hedge fund computers crunch out, but such interpretation skills can come from pure experience, why do an MBA for that?

While I was pretty excited about I-banking (particularly portfolio mgmt/Pvt Equity/Trading) some time ago, but I strongly feel that an MBA is not an adequate training enough to make someone a star fund manager, which is where I would have wanted to go to if I had opted for the fin route. As of now I am sticking to consulting where arm-waving has been made into an refined art.

## No comments:

Post a Comment