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This is the second part of a three-part series on the "plus-tick rule," which requires that any person selling a stock short must do so only at the price which is the higher of the last two discrete transactions. Part I looked at how the rule addresses imbalances in the market, and we began to make the case for why the rule should be restored.

Today, in Part II, we will discuss certain obscure but significant risks built into certain market practices such as basket trading and the use of leverage, and examine some of the unintended consequences of having eliminated the rule to the detriment of the original purpose of capital markets.

In Part III we will describe how the rule has been strengthened and weakened at different times over the past two decades, show how the market acted during those times, and describe the process whereby the rule was eliminated in July of 2007.

Why We Need the Plus-Tick Rule, Part II

Technology has demonstrated time and again that it is possible to increase productivity, which can sometimes be viewed, in a way, as increasing the amount of reward for a given level of risk. Often, however, what looks like a great reduction in risk can be seen as more modest as we learn more about unintended consequences -- think of suitcase-sized nukes, for example.

Quantitative investing has been around for so long that the term has lost almost as much descriptive usefulness as the term "hedge fund." I will use it to describe the practice of looking for patterns of information which can be predictive of the price movements of securities to an extent where it is possible to take advantage, usually using computer power.

Typically, predictive models are applied across groups, or baskets, of securities that share the characteristics found to have the predictive ability. These patterns of information might be as simple as adding "top company in industry" and "154 representative industry groups," limiting the basket to 500 names, and predicting that over long periods of time, the basket has a good shot at going up.

(You could even put a label on it, like " S&P 500," and market it as an index. Then you'd predict only that that index will more or less do the same or a little better than the rest of the market in the hopes of making it the standard by which all others are judged -- you get the picture.)

Uneven Execution

To make any money by actually investing in the basket rather than selling access to the names in it, it is not enough to simply predict its movements, which may be accomplished by analyzing large and constantly improving databases, you must also profit when your predictions turn out to be accurate. This means that you have to have capital committed, long or short, to a very accurate representation of your basket. This requires efficient trade-execution systems so you can get all of your capital committed, or released, from the basket, within a short enough period of time so that market movement "noise" doesn't wreak havoc with the price assumptions built into your predictive model.

Moving money in and out of baskets, of course, was a logistical pain in the neck until the advent of decent basket-trading software. This has been has been available for less than a generation, and for most of that time its main utility has been the ability to get a whole bunch of trades done simultaneously, if not well. The issue of best execution on each individual security was, and is, more complex.

The most ubiquitous conclusion has been that the diversification of positions within the basket, and the resultant variety of individual trade outcomes, will lead to the apparent experience that some trades will be executed really well, and others not so well, and that the overall effect will be that the average execution level will be pretty good. This theory reduces the concern facing those who are trying to figure out whether the best price obtainable was achieved when they are working a single order, rather than a basket.

Why do I refer to the "apparent experience" of best execution? There is a glaring problem with the measurement of "best execution" as it applies to buy and sell orders in securities, which is shared with all kinds of scientific measurements, which need an effective "control" group for accurate measurement.

The basic measurement tool of best execution is called the volume-weighted average price, or something derived from it, which kind of means what it says. If you are a big part of the volume, the price you get is going to materially affect the benchmark by which your skill in execution will be judged. In this way, when your order is big enough to affect the market, "best execution" is kind of up to you -- and whomever you can convince to be the other side of your trade.

As with any transaction, and with all other things being equal, you might be expected to get a better price if you can be patient, and remain relatively anonymous with respect to source and size, but in any case there is no real way to determine that. The price you get is the price available for your size at the time, and if you are a large part of the volume, the VWAP -- your standard of measurement -- will simply reflect that truth.

The Influence of Big Trades

It is impossible to derive the "best execution" level for a given trade when the trade itself influences what that level might be. This is a common and intractable problem found in many fields of science -- how to observe the behavior of what you study without affecting the way it works. It is exceptionally difficult, and eventually impossible, to compare yourself with absolute accuracy against a market in which you are a large player.

Unfortunately, this basic problem may be used as an excuse to stop trying, in the interest of enabling other outcomes. Because there is no simple way to resolve the issue, the best-effort solution is adopted, and after a while it becomes the standard. The original defect remains lurking in the background, if somewhat forgotten if not ignored completely. The fact remains, however, that big orders have so much of an effect on the VWAP calculation that the original argument for making the calculation at all becomes less relevant for that big order.

But how does this affect the market? There are two main types of traders executing baskets: those who are trying to make money by being right in about some outcome they have predicted, and those who are facilitating -- that is, they have promised, for a management fee, to provide a match between a vehicle, such as an ETF, and some underlying basket of securities. Both must be "in it to win it," or get in and out of their carefully crafted baskets simultaneously, without failures to buy or sell portions of the basket diminishing the application of their strategy.

However, the trader who is trying to make money on the trade has a natural limit on the overall price he or she will be willing to pay for the basket, while the facilitator may not be so constrained. As long as the facilitation trade is small enough so that it doesn't much affect the larger index, there might be little difference in market effect between the two. The scenario changes rapidly when the "tail" of large capital allocations coming into the index by way of the vehicle operated by the facilitator begins to wag the "dog" of the underlying index.

When it is a known fact that measuring best execution is a specious game to begin with, the measurements are not very effective at promoting careful attention to it. All the king's horses of data that participants are able to collect will not change the basic problem with the measurement. Unfortunately, all that data can be made to look pretty sexy, while really only providing false illusions. And these false illusions can be very powerful.

Further Distortions From the Fee Side

The profit-oriented trader, at least, might only cause sloppy pricing in a subset of the securities in a basket, in cases where the rest of the securities were executed well, so that the overall price objective be still obtained. Unfortunately, the fee-driven trader knows no such limitations, has no incentive to consider the relative level of prices received, and further, is under mandate to execute. When a significant portion of the capital being invested in the underlying index comes through such facilitators, the notion of comparative valuations between individual enterprises gets lost in the sea of broad-market trading, while correlations go to 1.

How many people, running how much money, were really aware of how ineffective the levered ETFs were (when used in their promoted direction) over multiday holding periods until Eric Oberg wrote that beautiful piece on them a few weeks ago? It may not be a coincidence that you could borrow the short ones such as the UltraShort Financials ProShares ( SKF) all day long until just recently.

Anecdotally, my wife was at a conference last fall when a speaker, the CEO of a $10 billion-plus fund of funds who was clearly uncomfortable with the proliferation of those instruments, posed such a question about them to the 100-person audience, and received no response. When I emailed him the answer to his question, he was appreciative enough that I don't think he had received many others.

The good part is that as long as the capital committed to such strategies is a minor part of the overall capital employed in the market, the tail won't wag the dog; the market picture in any given security will not be affected much by the execution characteristics of the individual order in that security which is part of basket trades entered.

The problem, of course, is that quantitative strategies proved out pretty well for a long time, so they have attracted lots of capital. Go back, for example, to the granddaddy quant model of them all, the S&P 500. Since someone made the claim that only a small percentage of active asset managers actually outperform the S&P 500 over long periods of time, many investors have given up trying. This giant exercise in exalting mediocrity (guess where I stand on the issue) has all kinds of things to recommend it. It's cheap, because you don't have to pay managers to work hard to discover which companies might actually do better than their peers, you don't have to explain why you underperformed by picking your own portfolio, and it's diversified.

The success of index investing spawned lots of index investing, and in turn, index-based ETFs, and now levered index-based ETFs. You can buy a 3x index ETF using Reg T margin now -- so you get what, 6x leverage on your dollar? Let's leave aside whether it's a good idea to let anyone with a dollar use that much leverage on a product with a theta the size of Montana and an inspiring name. We will just trust that the regulators who restrict individual stock margin accounts to 2x, and who limit naked short option leverage to 3x, have thoroughly investigated the merits of giving cash-account investors the same or more leverage without having to fill out all that silly disclosure paperwork. Instead, consider how many underlying shares of stock are affected whenever one of these things get traded.

A Check on Undue Leverage

The plus-tick rule, of course, throws a monkey wrench into the works, as the ability to sell short instantly is complicated by the necessity of waiting for someone to come along and buy the stock from you.

This is not the only hindrance created for basket players by the rule. Think for a moment what might happen when a basket order is entered near the close, and only 85% of the stocks in it get executed. Which is better, taking the overnight risk, or executing the rest of the stocks in the aftermarket, where there is less liquidity? It all depends on how wedded you are to your basket -- very, if you are an index ETF, of course. If you did well on the first 85% of your positions, how much will you care about the execution levels on the rest, especially when all you have really promised is that you will deliver the basket at the index level, which your trade, of course, will help determine?

The question is whether all the banging and lifting enabled by this basket activity in the absence of the rule is actually bad. I think it is. I've already argued that without the counterweight of a plus-tick rule, there will be more banging than lifting. Even in an imaginary world where there is a natural balance between the two, volatility would be elevated by the execution behavior I just described, and volatility is expensive for the whole global economy.

The absence of the rule enables all kinds of other trading as well. Take the following example, lovingly referred to on many desks as the "Taliban trade" or by Jim Cramer as kesselschlact: You might get short some common stock, then go out and buy credit default swaps, or CDS, on some tranche of the company's debt, boosting the premium so much that people start to wonder whether there's a problem at the company. As the stock falls, you could help it along, if you like, by hitting bids indiscriminately -- there's no plus-tick rule, after all.

One of the powerful things about this trade is all the leverage you might have available to apply to it, not at all limited to that determined by Fed or house margin rules, either.

When you buy CDS, you get not only the normal option leverage but also the de facto leverage that comes from the fact that even though the swaps cover one series of security, the prices of all of the company's securities depend on the company's credit standing. If someone starts to pay a whole lot for protection against the default of one security, the "cockroach theory" would indicate that holders of the company's other securities might wonder about the merits of holding those, too, and start selling, or buying swaps themselves, abetting the cycle of uncertainty.

So you may need only goose the premium on one tranche or series of security to infect all the rest. If there are five different securities outstanding, how much leverage have you brought to bear? What if the tranche on which the CDS you bought was only $100 million in size, and the others were all in excess of $400 million?

Investors might look at the common while you were sloppily banging bids on it, adding to your previously positioned (maybe larger) existing short. You could even do the whole thing on a bunch of names, then use levered ETFs to slam the bids (buying other names to hedge that part of the position, or not - heck, the whole thing might be going the way you want anyway). Sound manipulative?

You might successfully argue that it's not: If the company can't do a better job of protecting its competitive advantage in financing its business via the capital markets, it deserves a lower valuation, you could argue, if you could keep a straight face. Unfortunately, there might be no good alternative to the capital markets for the company ... unless you count the U.S. taxpayer. However, the government elected by those taxpayers, believing whole-heartedly in the rationality of free markets, might even help you along, ratifying your position by forcing a "take-under" of the company you've shorted.

Eric Oberg and Doug Kass have argued eloquently against levered ETFs and certain practices employed by quantitative traders. The plus-tick rule should be reinstated on its own merits, but it would be no surprise if doing so were to choke off the negative effects of those as well.


Know What You Own:Other ProShares funds include the ProShares Ultra Real Estate ETF ( URE), the ProShares UltraShort Real Estate ETF ( SRS), the ProShares Ultra Financial ETF ( UYG), the ProShares UltraShort FTSE/Xinhua China 25 ( FXP), the ProShares UltraShort QQQ ( QID), the ProShares UltraShort Oil & Gas ( DUG) and the ProShares UltraShort Industrials ( SIJ).

At the time of publication, Furber had no positions in stocks mentioned.

William Furber is the founder of High Street Advisors in Manchester, Mass.

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