Should investors flock to investments that have currently done well? The mutual fund industry has captured from neophyte investors billions of dollars of fee-paying capital by ads plumping recent price gain triumphs of funds rarely heard about in the past, or likely to appear frequently in the future.
The herd loves a big winner. It must seem like, "if they can do it once, they must be on a roll. I want to get aboard."
Regularly renewed analysis of subsequent fund performances tells the truth about such erroneous thinking. When there are more funds than there are stocks, by chance a few funds are almost certain to hit it big in each passing time period. And then to disappear into the fog of average-performance. Or worse yet, to mean-revert promptly with a similar-sized loss from their new, higher cost.
Then the herd hides its mistakes by ignoring them - and the continuing "management" fees being paid.
Thinking investors instead look to what is likely for the future. A daunting task, given all the noise of competing claims, conflicting economic trends, evolving technologies, emerging world competitors, swiftly moving fashions, and most importantly - changing market prices of stocks and ETFs.
But all those challenges have a positive side for investors pursuing an "active strategy" rather than the herd-like "buy, hold, and forget" indolent alternative. The constantly changing prices offer active investors ever-present opportunities for capital gains - and losses.
Remember, there's no free lunch in the near-zero-sum game of active investing. One person's incurred "risk" is another's achieved "reward." The constant task is trying to stay on the "right" side of that equation, while being realistic enough to recognize that no one does it perfectly. What counts is the balance of the win-loss ratio. It can bring big continuing payoffs.
But it takes work. Lots of it, if done well. For most of us there is not enough energy, time, or resources to do it just by ourselves. We need help. And "helpers" abound - at a cost, of course. A shopping trip into that cost jungle drives many back into the herd of accepting low, usually inadequate, single-digit annual returns, or worse, on their capital.
Some may get scammed into serious capital losses. If you can't trust a "Madoff," who can you trust? For the thinking investor, the answer is "only yourself."
So, find others like you that are accomplishing what you want, and are doing it well. See what you can learn from them and fit it to your needs and desires. Keep the initiative under your control, and "protect yourself at all times." It will be a fight, so pick your arena wisely, given your skills and circumstances.
One approach to consider is recognizing that stock investing is a serious "game" driven by millions of other thinking "players" upon whose subsequent actions your results will depend. If that sounds too scary for you, go join the herd.
The game approach requires the realization that the "rent" paid at this time for the use of capital is now too trivial to be very meaningful in building personal wealth. If all you want from your capital is some "outside income," go join the rent collectors and hope for better days.
Still want to be a player in the game? Being a serious one means finding a way to first, define the likely future prospects of eligible investments, and second, develop a means of comparing those prospects. Our best pursuit of these is: 1) find the best players in the game, and get them to let you know what they are really thinking, not just what they may say publicly, and 2) fact-check how well their guesses about the future worked out under the same past circumstances as those seen today.
Fortunately for this approach there exists a means of examination and a set of circumstances that fit together well to allow the first objective. The circumstances are that the best players, the big-money-fund portfolio managers (who won't talk much publicly) themselves have to get help in their necessary active investment pursuits of constantly adjusting their portfolio holdings. Those actions push more money through the markets than can easily be accommodated. Constant care needs to be taken to avoid moving prices to their disadvantage.
Their helpers in that process, the market-makers [MMs], over the years develop personal relationship understandings of how these clients typically operate. That allows the MMs to protect their firm's capital that temporarily has to be put at risk while getting done the volume trades required by the clients. So, here is how a forecast of future prices gets derived: What the MMs are willing to pay for price change protection, and how the hedging gets done, tells just how far - both up and down - the clients are likely to push prices. What is involved to do this is termed intelligent-behavior analysis.
The end product of this analysis is a range of prices believed to be so probable as to be worthy of spending real money on, money that the MMs could otherwise pocket as a trade spread profit. Thousands of trades verifying these implied forecasts occur every day, on hundreds or thousands of actively-traded stocks and ETFs, as they have for years.
That history enables the compilation of extensive records of price changes subsequent to forecasts. Forecasts that themselves range across a span of imbalances between the upside and downside price changes that are being implied. With such records it is possible to make comparisons today of how well the MMs were able to foretell the prices of many such yesterdays. That meets our second objective in the "game" approach.
Here is a current sample of what those comparisons look like among what many might consider the "best" current opportunities:
Screening a list of 2141 stocks and ETFs produced these 31 candidate investments. Their implied price range forecasts were derived by intelligent-behavior analysis of the self-protecting actions of the market-making community at large, as of the market close on Friday July 19, 2013.
All investment candidates were required to have prior forecast histories of at least five years (1261 market days) and from their current forecast, expected upside price changes of at least +5%. Samples of all prior-day forecasts with Range Indexes no greater than the current day's were used to calculate performance test results of: a) average of each sample experience's maximum price drawdown exposure (from cost), b) proportion of sample experiences producing a profit, c) average (by geomean) return of all sample experiences, d) average number of market days sample positions were held, and e) annual rates of return for the sample's experiences. Candidates were further screened for win/loss ratios of at least 9 out of 10 sample results.
Range Index values represent the percentage of the forecast range lying below the contemporary market quote. Performance test discipline requires position holdings from day-after-forecast e.o.d. (end of day) price to a closeout at first e.o.d. price equal to or greater than a top-of-forecast sell target. Or no later than 63 market days (3 months) beyond the forecast date, at which point all positions still open are closed out.
Candidates in the table are ranked arbitrarily for initial consideration by upside forecast price change potentials. Tradeoffs against drawdown risk exposures, or win-loss ratios, or minimum payoff or annual rates of return, should condition individual investor preferences among candidates, as may other personal or portfolio considerations, like diversification requirements. But there are enough attractive alternatives to allow considerable flexibility. And this is but one day's menu.
Of interest may be the differences between candidate averages and those excluded in the screening process. Notable are the differences in drawdowns, win ratios, and average payoff achievements. On the other hand, similarities in average upside prospects, Range Indexes, sample sizes, and holding periods of test positions are present.
It is possible to derive, on a day-by-day basis, forecasts of expected future prices for a large number of stocks and ETFs. Forecasts that are useful to investors in conjunction with disciplines that significantly outperform market-average, long-term buy & hold practices now in widespread use.
The example above illustrates a very large population average that in prior circumstances over several years, with specific issue outlooks similar to the present, have produced annual rates of return of 21%, when market averages have been significantly less, or at worst, near zero. Those attractive results are attributable to an investment discipline focused on efficient timing-of-capital-employment, aided by guidance from forecasts of prices for individual investments made by knowledgeable market professionals.
Further sharpening of selections from that large population provides substantial improvement of both payoff rates of return and the reward/risk tradeoff as expressed in the win-loss ratios experienced. In this case, not considered abnormal, it yields an annual return average some four times that of the population.