Quick, important introduction
This analysis is the product of over 50 years of professional investment experience as a buy-side investment researcher (both of fundamentals and quantitative perspectives), portfolio manager for major institutions, upstairs arbitrageur for a NYSE specialist firm, hedge fund proprietor-manager, non-profit endowment funds advisor, and multi-year publisher of proprietary equity forecast information.
The most important message of this article is that Beauty, Value, and Risk are all in the eye of the beholder, and regarding investments, that is the only appropriate place for it to be. They are all intensely personal conclusions.
The difficulty created by that notion in regard to investments is that for choices between alternatives to be productively assisted, the decision factors must be comparable and understandable, ones that many individuals can quickly comprehend and relate to.
A useful preface to this discussion can be found here.
How did the investment industry get so screwed up about risk?
My perspective of the problem only goes back to the late 1950s. It certainly existed in less critical circumstances for decades, perhaps centuries, before. Blame its increasing intensity on the evolution of advances in computer and information technologies as tools to improve corporate productivity and profitability.
The late-'50s was a time of growing corporate international competitive strength and profitability. Russia's Sputnik launch initiated the space race and intensified the cold war. Emphasis on science and technology and the tools to accomplish the same pushed IBM (NYSE:IBM) into a dominant position. The best minds were drawn to corporate management.
Corporations competed for talent both by current salary compensation and by deferred retirement income compensation. Retirement plan funding became a major influence in the demand for investment management. Previously, most investment management was aimed at individuals or financial organizations of bank trust departments and insurance companies. Loan investment instruments had been more prevalent and more respected than equity investments in many fields.
Now the successes of corporate achievements created in the investing world the spectacle of "growth stocks" as prized investment vehicles. Retirement funds sought their usage in order to achieve coverage of future-promise liabilities at least cost. This was because virtually all such plans were "defined-liability" or DB plans, with the corporation responsible for the ultimate fulfillment of contractual promises initially made to pensioners.
Under these legal pressures, pension fund corporate managers began to press their hired outside investment managers for forecasts of expected investment returns. This development was greeted with near-horror in many investment management organizations, since most individual investors had been sufficiently cowed by the posturing of managers that they would not dream of having the temerity to question someone that could earn them money on their money.
Many managers did not even calculate returns on investment. It was held to be enough simply to report a recent market value of what was in the investor's portfolio. Now the investors wanted to know how fast they were being enriched!
Investing's dominant determinant duo: Return and Risk
Fortunately, the commercial bankers knew how to make those return calculations properly, and the Bank Administration Institute [BAI] procedure was adopted. Modestly embellished to deal with the intricacies of capital additions and withdrawals, it has largely been the basis for calculating investment portfolio performance - the GIPS standard of the CFA institute.
So we do know how to count the beans. Why don't we properly deal with measuring risk?
Well, investment managers knew that investors didn't like to do unpleasant things, like buy life insurance, or talk about losses. So it was an avoided subject. Until the Pension Fund clients insisted. Since they were the source of the big fees, they had to be appeased.
Remember the times. Computers were being assembled and improved as fast as was possible, but the business opportunities to enlarge profits and EPS were where the computers were first put to work. The payoff tasks were largely just automating keeping records and getting things done faster with fewer employees. Or the computers were being provided to government to aid in fighting the cold war and the space race, supporting those folks capable of demanding, involved computations.
Just to complicate things, along comes a serious IBM researcher, Harry Markowitz, who had thought intently about investment risk. The fact that IBM's pension funds were significant participants on the scene was not entirely coincidental, although he was not part of that corporate function.
Markowitz had done enough thinking and exploring to come to the conclusion that investment portfolios should be looked at not piecemeal, one holding at a time, but as a coordinated package. Done that way, the combined values of the holdings were what really mattered, and by building combinations of holdings that tended to not march in price lockstep with one another, the inevitable troubling moments encountered by each holding might be tempered by happier price times of others. Systematic, or programmed diversification thus became the logical choice of risk managers (long before anyone had such a title).
Now the search for which stocks had the best lack of coordination with others was at the forefront. With thousands of stocks (and mutual funds) to compare, quantitative analysts ("Quants") had their hands full, and tool cupboards were often empty or under-equipped. The obvious way to answer the pressing question was correlation analysis, using multi-year daily histories of price changes for all of the holdings (often hundreds) in a portfolio.
Computer time was a scarce commodity, and computing capacities were limited by technological advances of the time. The portfolio diversification problem was compounded by time pressure, since the necessary data for the computations was being expanded daily, and in order to be competitive, answers needed to be at hand for investment policy committee contemplations enough in advance of the stock market's opening so that strategies of buy and sell order tactics could be put in place for advantageous actions.
It turned out that even with the best computing hardware of the time completely devoted to this problem (which it rarely was), the needed answers could not be delivered in time when properly computed and assembled. Another method than exhaustive cross-correlations of holdings had to be found.
It was, by a cadre of academics, who were willing to distort reality enough to make it appear that a simple, apparently ingenious approach could solve the problem. Thus was "Modern Portfolio Theory" propounded. Its "breakthrough" was to perform correlations of each holding, not with all other holdings, but with the market average. Then by use of "normal statistics," comparisons between the holdings could be made in terms of their relationship to the market.
Further, the statistical approach permitted an appearance of sophistication and elegance, with labels of alpha and beta as algebraic equation terms that could be graced with undeserved (and unproven) qualities, such that to this day, 40+ years later of ineffective applications, the theory has been rejected by much of the investment management community, and significant portions of academia.
At the time, highly regarded academic mathematicians warned that the actual experience of stock price changes did not fit the shape of the "normal curve" being extensively relied upon by MPT. Further, the problem of normal statistics involving the beneficial side of investment experiences along with the hurtful side in the calculation of "standard deviations of return" were dismissively pooh-poohed by MPT proponents as if they did not exist, or that side of the distribution was risk for the "other side of the trade."
The fact that practically nobody was on both sides of the trade didn't seem to matter.
Nor did what now is well recognized as (fat) "tail risk" and "black swan events" or usual asymmetrical balances between upside and downside future price prospects.
But the presumed elegance and sophistication of MPT has managed to keep a couple of generations of academics, fund consultants, data compilers and investment managers gainfully employed, all at the expense of an investing community eager for self-deception.
But "where are the customers' yachts?" as Mr. Fred Schwed so long ago questioned?
So much for history, what to do now?
Risk has to do with getting hurt; having pleasant surprises is not a part of the issue. Further, investment risk is everyone's own private perception, living only in the present and the future. History may color those perceptions, but it is not a substitute for the actual concerns and present-day projections.
Investors must deal with risk, each on his/her own terms. The true challenge is how to provide information that can help the investor develop a productive perspective in the continual job of comparing action alternatives and deciding when and which way to adjust the existing mix of investment holdings.
The best approach we can identify is to find a set of highly motivated, well-equipped, and well-trained humans, operating in a function essential to the investing process, disciplined by group competition, and with skills evidenced by continued employment at envious levels of compensation. Market-makers fit the bill well.
Then, determine by the rational implications of their self-protecting behaviors what their future expectations must be, in clear, explicit price terms. That is followed up by rigorous careful examination of how well subsequent events prove out the profitability of the forecasts. Done under the disciplined implementation of an unchanging, standardized, clear-cut simple to follow and unambiguous strategy.
That will not guarantee how the future will unfold. But it does provide a perspective of how well the forecasters have been able to gauge the future, repeatedly, under varying conditions. How much evidence, and how persuasive it must be, has to be left to the investor.
We are comforted by the fact that our sources have, over a large number of years, and in thousands of specific instances, been shown able to provide guidance that under a disciplined follow-through has provided profit opportunities at multiples of gains recorded by major market averages.
In the process, the trade-off of risk and return plays an essential role. Risk is everywhere, thankfully, for without it there would be no, or only trivial return, except in rare cases. It is having the perspective to make appropriate choices between differing packages of risk and return that provides superior investment performance.
At the present, the prospective price range for DuPont (NYSE:DD), implied from the self-protective hedging behaviors of the Market-Making community, has proportions of potential gain and exposure to possible loss that in the past have proven to be extremely competitive with the experiences of most other (upwards of 2500) actively-traded and widely-held equity investment alternatives. It would appear that a buy of DD here is a good choice for an investor whose principal investment mission is wealth-building within this calendar year, having low acceptance tolerance for price drawdowns.
Attached is a behavioral analysis history of the market-making community's past price range forecasts for DD, and an analysis of the results of buy recommendations made under 49 similar forecast conditions, following our time-efficient standard entry and exit discipline.
In those conditions, DD's average MAXIMUM price drawdown experienced averaged -1.6%, while its actual net gains averaged +7.8% , or more than 4 times the worst-case price drawdowns. Only 2 of the 49 experiences resulted in losses, a 96% win rate.
Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.