The woods are lovely, dark, and deep,
But I have promises to keep,
And miles to go before I sleep,
And miles to go before I sleep.
The Wall Street "woods" is full of stories. They're so thick it's usually hard to see the "forest" for the "trees".
Every stock has to have a story. How else can a new company go public to have a currency (stock) to attract skilled workers, and get banks to lend them development capital, perhaps even raise more equity capital by secondary offerings? Established companies have to have stories to keep their skilled people motivated and their customers excited about products and services.
Trouble is, how can an investor tell when a story is real and prophetic, or just a "story"?
Answer: Follow the money.
Find out who's "buying" the story by who's buying the stock.
It's easy enough to find out who has bought the stock. But the real task is in finding what the current, active buyers and prospective ones are doing, and how far they may reach to get positions they want.
For that, we turn to a completely different form of analysis, one that is peculiarly well-suited to the investment scene. One that is uniquely centered about the activities of market-makers. That analysis does not dissect potential product markets, competitive tactics and countermeasures, technological developments, or financial reports and earnings projections.
Those things are all important, but to be competitive in gathering and assimilating all that information is usually far beyond the skills and resources of the average investor. Instead, we rely on experts who have support teams that get all those things predigested and kept up to date for them. Experts who need that perspective, so they can make fine judgments about what is likely to happen in the future to the most important investment dimension - the stock's price.
What happens behind the scene in market transactions
The role those experts play, day in and day out, when their employing firm has been given an order to buy or sell a large number of a specific stock's shares (in one transaction, at one price, as a block), is the bringing together of all the available participants necessary to make up the "other side of the trade" and get the transaction completed at an agreed-upon price for the lot.
Often (maybe 90% of the time) there are not enough buyers or sellers of the stock on hand to satisfy the big-fund originator of the trade order, within the time limits (usually minutes to hours) set by that client fund.
When this is the case, the experts seek to find out what it would cost to be held risk-free if their employer firm should decide to take on, temporarily, part of the order on its own books. They typically check with their listed options desk folks to see what is involved in hedging that stub-end of the block transaction order that cannot be filled from readily-available and interested public parties.
Such insurance has a cost, and the larger the stub to be covered, as a percentage of the whole block, the greater will be the cost per share for the entire block. That cost is part of the negotiation between the experts on the block trade desk and the firm's fund client, as to the price at which the whole block can be traded. If the cost is too high for the trade order originator to swallow, the deal fails, and the stock's last-trade price remains the last trade quote.
The influence of competition
Of course, the client fund is not restricted to whom they may deal with in this market-making role, so they may "shop the trade" with other facilitator firms that they trust, or seek to place it directly in some of the automated "dark pool" markets that exist. The market-making firms are keenly aware of this competition, so they make every effort to not lose any deal of the thousand or more they are offered every day. But there are always sound business judgment limits as to how little profit spread between the client's bid or offer and the market-making firm's trade completion cost may be acceptable.
The cost of the risk-protection insurance regarded as necessary by the trade facilitator is a potential deal-breaker, so it becomes a carefully examined element in each deal's case. Who sets that cost, and how do they come up with it?
The insurance for most block trades comes through listed options. The prices of those options are the product of market negotiations very much like those of stocks, except the only re-insurance available in the market for options on stocks is in options on the stock market as a whole, often where the underlier to the option is an index-tracking ETF, like SPY, IWW, QQQ, or even broader world-incorporating market ETFs.
Is this getting complicated? It is for most folks. And, in reality, it necessarily is complex because so many interests are involved. The impressive thing is that, for the most part, and almost all of the time, it works pretty effectively. So let's finish the story.
Who sells this price-risk insurance, and why?
The "why" question is easily answered - to make money. Not so easily answered is "how do they price the insurance to make it likely that money can be made on all (or most) contracts sold"? The answer to the first question of "who sells it?" starts to make clearer how they price contracts appropriately.
The sellers of the options contracts (not shares, please note) usually are the proprietary trading desks of many market-making firms. The very same firms involved as block-trade facilitators in the discussion above. Good management principles suggest that their top-organization folks should make rules that avoid having block-desk people within a firm be involved with the firm's own prop-desk troops in negotiations over risk-insurance costs on the same deal. So most of this traffic gets done with another firm's prop desk.
The question of what is an appropriate price to be charged, for any strike price of any expiration-date contract of any underlying stock's options, comes back to what market prices for that stock are likely to be encountered between now and the option's expiration. That question gets answered by the principal mission of any market-place: Price Discovery.
Any market-place provides the opportunity for buyers and sellers to put their money where their mouths (and brains and convictions) are. And here in the options market, the professional buyers and sellers of contracts in widely-held, actively-traded stocks, dominate the price discovery process, due to their sheer volume, and aided by favorable margin rules made possible by close exchange surveillance and regulation.
Is the public getting hammered by this?
This condition does not bring harm to the public. It provides a great benefit of keen analysis and immediate information collection from the worldwide systems of competing market-making firms whose block and prop desks are on opposite negotiating sides of most active options trading. Each firm has a good sense both of what is likely and what is possible in the near-future realm of the stocks in question. And they price the insurance accordingly. The public gets the benefit to the extent that it chooses to participate in that activity.
But the public needs to reflect on the fate of Barings, Ltd., a 136-year-old British market firm that became destroyed when it committed to positions it did not fully understand in a complicated options proposition. Options can, and often do, provide enormous leverage in regard to prices of the underlier being optioned. As insurance contracts they involve fulfillment responsibilities that the options exchanges (through the Options Clearing Corporation) require to be secured with real capital at the end of every trading day.
It is one thing to buy insurance, but a completely different set of responsibilities are involved when insurance is sold. If playing this game, be sure you know whether you are a buyer or a seller of insurance. It turned out Barings did not know.
Like most market decisions, value is a matter of perceptions and perspectives. Embedded in the risk-insurance options prices are impressions (by both the insurance buyers and sellers) of what their firm's big fund clients are likely to do that will move the prices of the stocks in question.
Money moves markets. Poker-players keep their cards close to the vest. So do professional money-managers. Though they adroitly try to conceal their intentions, the fund managers and their internal trading desks have to define what they are willing to do, at least on a trade-by-trade basis, if they are to get any help from the market-making trade facilitators. Dozens of daily phone conversations between the traders at each end build both a confidence bridge, and an understanding of strategy and tactics between the parties that gets personal and intimate. Many such relationships are several years old.
And the market-making trade desks are in constant communication with each other to learn what the "order flow" looks like and how it may be trending in terms of direction and forcefulness. This is a very sophisticated, ultra-competitive community.
How this can help the individual investor
The dominant presence of volume market-making activity in widely-held stocks and ETFs provides an insight into the thinking of the big-money fund clients, and into the market-maker reactions to that thinking. Those insights are embedded in the prices of the risk insurance that makes possible getting block trades (that move stock prices) filled.
So an analysis of what at-risk market-makers will pay to keep themselves whole can tell just how far they think prices might go, both up and down. This kind of analysis is neither fundamental nor technical, but is behavioral in nature. Much of what is to be found in the literature about "Behavioral Finance" unfortunately dwells on the errors that humans make for a variety of reasons. Very little of it looks at what credible, qualified practitioners do that is right. So a negative aura surrounds much of behavioral analysis because the misdirected academics toying with the idea have yet to find any way to capitalize in the investment world on their studies to date.
Instead, a rational, logical analysis of what market-makers soundly do to protect themselves when they must take on risk to be competitive in their daily tasks, does give useful guidance as to what is likely to happen in the future to the price of many stocks.
Here is a current examination of how their near-future price range projections have been borne out:
This table looks at the prices of all 30 Dow-Jones Index stocks during the past 4-5 years, day by day. It sees how those prices have changed over the following 80 market days (16 weeks or nearly 4 months) and of each lengthening interim period at 5 day intervals. The average of all those changes (33,795 of them) is shown in the blue central row. The numbers shown are in terms of annual rates of change to make it easier to compare periods of differing lengths of time.
The rows above and below the blue line show the average price changes of only those day's instances of those stocks, where the attitudes of the market-making community, as determined by behavioral analysis, were no less extreme in their perceived balance between the potential future price change possibilities of upside change to downside change.
That balance is indicated in the colored left-hand column. As an example, the green 10:1 row contains the averages of 56 instances where the community attitude was that a likely possibility of a percentage price change upwards could be ten times as large as the likely drawdown for that stock from the day's close when the measurement was begun. To make it more specific, suppose a $50 stock was being appraised as having a price range of 49½ to 55. Its upside of +$5 is a +10% change, and its downside of -$.50 is a change of -1%.
The upside-to-downside, or reward-to-risk ratio is ten-to-one.
The red rows show where the perceptions of future likely price changes had a larger risk component than reward. Gratifyingly, market-makers' block trade desks seem to have a pretty good understanding of when stocks of these market leaders are headed for trouble instead of proceeding at trendline double-digit average gains.
The next column to the right of those colored ratios counts the number of times such a balance was encountered. In the example used just above, the rarity of a ten-to-one bet in these closely-followed stocks can be illustrated by the mere 56 such occasions that occurred among 30 stocks in over 1130+ market days (actually 33,795 instances), or only 1/6th of 1% of the time. The odds of finding a 5 to 1 bet are about three times as great (163 events) but are still only about ½ of 1%.
But if those 163 events could be identified - in advance, as they were - then buying the stocks and holding them for the next 80 market days would have given the active investor an annual price return at a rate of +31%, nearly double the +17% rate of all the DJIA stocks. Even more interesting, the table shows that (maybe just in this instance of time and only 30 stocks) a "sweet-spot" of holding for only 50-55 days would have elevated that rate of return to about +40%.
"Would-a, could-a, should-a" reasoning after the fact is fantasizing. That is why once the prospects for a stock's future price are indicated, it is important to know, from prior such experiences, how well the market-making community has pegged its targets. By setting up a disciplined investment strategy to measure the after-the-fact results (what statisticians refer to as out-of-sample testing) this can be done.
Several approaches can be taken, depending upon the investment strategy preferences of the investor. One recipe that appeals to us is to use the upper end of the price range being forecast as the unchangeable sell target, for that forecast only. Whenever the end-of-day closing price reaches or exceeds that target, close the position out at the next day's open.
If that has not happened within 63 market days (3 months), close it out regardless, and take the gain or loss, as may be. Repeat the process individually for each instance of that level of forecast imbalance during the period of concern (or data availability). In each case, divide the closeout price [cp] by the end of day price the day after the forecast (it being the assumed cost of investment) [ic]. Set the result [r] aside.
When all instances of interest have been measured, add up all of the calendar days [d] it took to reach all of the closeouts. Count the number of instances that have been measured [n]. Multiply any one result by all of the others, one at a time, and take the [n]th root of the product to get what is known as their geometric mean [gm]. Then divide the total number of days [d] by the number of instances to get an average holding period [hp] for each instance.
Now take the [gm] and raise it to a power of (1 divided by the [hp]) to get an average rate of change per day [dc]. Then raise the [dc] to the power of the number of calendar days in a year to get the annual rate of change [ar], which is what is wanted when comparing things with different natures over different periods of time.
For those with an algebra fetish, here is that process in letters rather than numbers:
[r] = [cp] / [ic]
[gm] = (r*r*r*r…)^ (1/[n])
[hp] = [d]/[n]
[ar] = ( ( [gm]^ (1/[hp]) ) )^365)-1
Rate of return purists may find reasons to nitpick this calculation, but its output will come closer to theirs than anything that warrants starting an inter-family feud.
Where the DJIA stocks are (in MM eyes) at present
Viewed by market-makers now, here is a map of what the upside to downside trade-off looks like. Attractive long positions are towards the lower right, scary ones towards the upper left, and those with perfectly balanced prospects are on the diagonal.
(used with permission)
The two most attractive from an upside to downside prospect are International Business Machines (NYSE:IBM) and Chevron (NYSE:CVX). The least appealing on this basis are JPMorgan Chase (NYSE:JPM) and Bank of America (NYSE:BAC). This is but one dimension of several investment considerations. Some others are outlined in the tables below, resulting from the employment of a disciplined, time-efficient procedure discussed in an earlier article.
In practical portfolio management terms, keeping the portfolio's total capital fully committed at all times to investments with the largest available annual rates of return should provide the greatest possible accumulation of wealth.
The only exception to this rule is if some catastrophic circumstance involves one or more negative returns able to eliminate all of the positive ones. The customary way to avoid such an event is to diversify capital commitments into a large enough number of parts to make any one event's demise be a manageable size for the whole portfolio. This issue of risk and odds may be discussed at length in another article.
Market-makers have always been in a privileged position, because for markets to function there needs to be an acceptable degree of trust between buyers and sellers that agreed-upon transactions will be carried out faithfully. In times past, market-makers provided this and had the advantage of "order-book" knowledge. There they knew the prices at which buyers and sellers would be willing to become active participants, at both higher and lower than the last trade price, and how many shares they would commit to at such prices. In "auction" markets like the NYSE, "specialists" maintained the order books and were charged with the responsibility of "maintaining orderly markets" where changes in price from one trade to the next were expected to be relatively small and continuously available.
Advances in information-handling technology, coupled with the competitive advantages in commanding capital by publicly-owned corporations acting as market-makers, drove the old-school specialists out of business.
Further, the exchanges themselves found it next to impossible to compete with automated exchanges because of information technology advances. Once owned by the specialists in a business form like a partnership, they became public investor-owned corporations rather than private self-regulating organizations.
Regarding public confidence about trustworthy functioning, this latter evolution has highly questionable aspects. Over centuries of time old-style exchanges have had moments when bad actions by individuals shook the public's trust. But typically quick, effective actions were taken to restore confidence. The exchanges knew they had to behave or government could legislate them out of business and eliminate their functional advantages.
But now, as publicly-owned corporations, the exchanges have two masters to answer to - both government (supposedly protecting the public) and the investing "public" who seek to maximize their investment returns from the exchange's activities.
In the 1930's the Federal Securities and Exchange Commission (SEC) was created to provide the regulatory machinery presumed to provide protection for the public. Most recently the whole "Madoff Affair" made it clear that the SEC was totally ineffective in playing its public guardian role. Madoff, a former Chairman of an Exchange, ran a fraudulent "Ponzi Scheme" for over a dozen years that stole more than $60 billion of investors' capital, both in the U.S. and abroad. Documented complaints were made by investment professionals to several offices of the SEC over a ten-year period without any response by the SEC. Ultimately the scheme collapsed of its own weight, without any action being initiated by the SEC until it was all over.
Indeed, during a fifty-plus career in investment markets, the true regulatory disciplines and protective actions were seen coming not from the SEC, but from the exchanges themselves. Now even that is severely weakened. What remains is a dangerous situation, not helped by a growing sense of public disbelief in the Federal Government's ability, perhaps even in its desire, to serve those who continue to vote instead of those who simply ride for free.