The age-old question in investing: What investment should I buy? This question gets asked more often than I care to think about. The problem with such a question is that, if you have to ask it, you probably shouldn’t be investing in whatever gets recommended to you.
Think about it for a moment. If you don’t know what represents a good investment, then you don’t know what represents a good investment. You don’t know when to buy in, when to sell. Most importantly, you don’t know how to repeat any success you have with the recommendation and you don’t know how to avoid any future failures if the investment turns out to be a dud.
In short, you become a helpless dependent upon the advice-giver. Now, I’m not saying that some guidance isn’t helpful if you know nothing about investing. We all have to start somewhere. However, if you’ve no interest in learning how to invest, then you shouldn’t be investing.
I have no interest in learning how to sew, therefore I don’t own a sewing machine and don’t intend to do any sewing. Why a person with no interest in learning how to invest bothers with getting himself involved with investments is beyond me. Money? How much money does ignorance make? In my experience, none.
Even when you do want to learn how to invest, there are a few problems you have to overcome. Most ways of analyzing investments are mathematical. Technical analysis is all about analyzing patterns and charts of past performance of the investment in question. Fundamental, quantitative, analysis is all about analyzing numbers on a financial statement of a company.
In both cases, some assumptions have to be made. Assumptions about the business that may or may not be true. Those assumptions, which you don’t know to be true, guide your investment decision. To me, that’s problematic.
Financial Models & Modeling Software
What’s a financial model, you say? No it’s not some bikini-clad woman with money tucked under her garter belt. Finance is more quirky, and less kinky. A financial model is an abstract representation of some kind of financial decision making process. Yeah, I know. Not very sexy.
In the context of investing, it’s a mathematical representation of the investment in question. Usually, modeling tries to show how an asset or investment will behave under different circumstances. A financial model may try to predict investment risk, thereby allowing you to reduce such risk and buy assets which represent a better value or are considered “undervalued”.
There are many different ways to build a financial model. In the old days, before sophisticated computers, investors would gather data together and track price movements or try to spot business cycles where businesses would experience a “boom” and then a “bust” phase in their operations. After combing through pages of data, they would buy or sell investments accordingly with the hope that they would be profitable.
In 1928, very bright man (Benjamin Graham) began teaching mathematical formulas he had devised to calculate the risk of an investment and determine its value. Some pretty famous people use his method, at least in part, including Warren Buffet.
Today, software exists to make both technical analysis and Graham’s financial modeling methods easier by gathering all of the data and arranging it for you. To add to this, modeling software exists that performs complicated “what if” scenarios in an attempt to predict the probability of you being successful in your investment endeavors over the long-term. Does any of this stuff work?
Well, the software you use is only as good as the inputs given to it. So, it’s really just as good as doing it long-hand in a purely mathematical sense. The software merely automates the process. But, even the long-hand method has one major flaw: interpretation. There’s nothing wrong with the math done in all of these calculations. The problem is this: what does the math mean?
Many a math whiz and financial professor trained to do these mathematical calculations will tell you that you can make investment decisions based on these equations. My response is, like Inigo Montoya, “I do not think it means what you think it means.”
Deduction And Financial Models
Fundamentally, I think the problem is philosophical. Yes, philosophical. What does philosophy have to do with investing? Plenty.
Deduction is the process of developing new instances of already known information. For example, a deductive argument might go something like this:
Premise 1: All men are mortal.
Premise 2: Socrates was a man.
Deductive conclusion: Therefore, Socrates was mortal.
You see, we didn’t really come up with anything new or exciting here in our deductive conclusion. We concluded that Socrates was a mortal because we already said he was a man and that all men were mortal. But, how did we know that Socrates was a man and how did we know that all men were mortal? Based on our deductive reasoning, we just assumed the first two premises were correct without questioning them.
It’s the same way with these mathematical modeling formulas. All of those mathematical equations start with assumptions. If those assumptions are wrong, then the equation doesn’t tell you anything meaningful. Even if the numbers are correct, you can’t know what the equation means just by looking at the equation.
Let me return to my Socrates example. We say that all men are mortal. If we wanted to translate this into a mathematical equation, we could assign this statement a letter or number. Let’s do some algebra, though, and use letters. So:
All men are mortal = a
Now, on to the next one:
Socrates was a man = b
Now, for our conclusion:
Socrates was mortal = c
Now, let’s eliminate the phrases and just use our equation:
a + b = c
That mathematical formula is true, and will always be true. However, one question becomes clear when trying to use this equation in the real world:
What do I do with this equation?
If I can’t answer that question, I’ll end up doing a lot of math and ultimately end up with an answer which isn’t useful to me at all. In these math formulas that try to forecast future investment returns, and try to value a company’s “intrinsic value”, we don’t know that the premises are true. Math, alone, won’t tell us this. We may make many assumptions about what a company’s earnings actually tell us, but how do we know that our assumptions are true? We don’t.
Part of the problem is that these math models assume that the investment (i.e. a company you’re investing in) has an “intrinsic value”. An intrinsic value is a value which is allegedly “in” the investment, somehow. How? We’re never told. We’re only told that it’s there. That’s why the math model “works”. It uncovers the “intrinsic value” in the investment. That’s the formula’s job: to solve a quantitative problem, and it does that incredibly well.
What if the problem isn’t purely quantitative? Then, math is of little or no use depending on the nature of the problem. As long as you know the premise of your argument is correct, then math is an immense value. So, if we knew that the assumptions in the math equation were true, and we knew that the assumption that math models were the correct way to determine a good investment, then we would know what to do with answers to these math problems. But, we don’t know that any of these assumptions are true.
For example, a P/E ratio is a “price to earnings” ratio of a company. Investopedia’s entry for P/E ratio reads:
A valuation ratio of a company’s current share price compared to its per-share earnings.
The equation is:
P/E = Market value per share / earnings per share (EPS)
Investopedia goes on to explain:
…if a company is currently trading at $43 a share and earnings over the last 12 months were $1.95 per share, the P/E ratio for the stock would be 22.05 ($43/$1.95).
That’s all fine and dandy. Just one thing: what do I do with this equation?
We’re looking at past performance to determine future value of the company. Is that a good idea? Does history repeat itself? Is the value of the company somehow embedded into financial statements? I submit that the answers here are no it’s not a good idea, no history doesn’t not necessarily repeat itself, and no the value of a company is not intrinsic. This is why deductive formulas only provide you with contextual answers.
In other words, all of these math formulas will tell you “if….then”. In other words, “if the market value per share is this, and the earnings per share is that, then the P/E ratio is this”. Using the P/E formula is, itself, conditional: “if P/E ratios are a good measure of a company’s value, then you should invest in a company based on its P/E ratio”.
Some investors and investment professionals will tell you that you should invest based on the answer to the equation. When the P/E ratio is low, some investors say you should buy the company, because the company’s current value is low, relative to the income it is earning. This is supposed to be a “cheap” company, and represents a good long-term value (i.e. it’s undervalued). When the P/E ratio is high, you’re supposed to stay away from that investment or only view it as a short-term investment because the company’s current value is high, relative to the income it is earning, making it an “expensive” company to own (i.e. it’s overvalued). This all ties into the whole “intrinsic value” theory of investing proposed by fundamental analysts who are obsessed with finding the intrinsic value of a company.
Supposedly, there is a “right price” for the stock. Your job is to use math to figure out whether the price is “correct” or “incorrect”. If the price is “incorrect”, then it will be either “undervalued” or “overvalued”.
For example, if a stock’s price is trading at $20 per share, the math formula would tell you whether this is a good or bad price for the stock. The price to earnings formula implies that there is an “intrinsic value” to the stock price. This intrinsic theory of value is explained by philosopher Ayn Rand:
There are, in essence, three schools of thought on the nature of the good: the intrinsic, the subjective, and the objective. The intrinsic theory holds that the good is inherent in certain things or actions as such, regardless of their context and consequences, regardless of any benefit or injury they may cause to the actors and subjects involved. It is a theory that divorces the concept of “good” from beneficiaries, and the concept of “value” from valuer and purpose—claiming that the good is good in, by, and of itself.
At one time in history, the intrinsic theory was considered “objective” because it divorced value from consciousness. In other words, value was determined devoid of any context. But, “value” naturally presupposes a valuer. This is partially why I reject making decisions using only these mathematical formulas.
Another issue with using math models for forecasting purposes is that you don’t know what you should do with the information. Remember, there’s no valuer in the equation. Company, and thus stock, values are allegedly “intrinsic”. Therefore, you’ll never know whether the equation is saying that the company currently has a low value because it has a good management, but is still growing and will be a good long-term value or whether it’s currently a low value because it has crappy management and is only surviving because of the efforts of past (good) management, which won’t keep it afloat for too much longer.
Because there are no valuers in the equation, you’re not looking at whether the company is working for your best interest, whether the management is taking actions which are rational, or whether the company offers a product which has a socially objective value versus a philosophically objective value. All you’re doing is math.
September 10th, 2011 | by David | No Comments