We’ve had questions about the “quote stuffing,” article last week in the Wall Street Journal. In essence, gobs of immediate-or-cancel (IOC) trades gumming up markets might have contributed to the Flash Crash. It’s equity whack-a-mole, where trades pop up to draw fire, then disappear.

No form of equity order randomly appears in the markets, crafted by conniving traders. All must be submitted via rule filing to the SEC, and approved. So the orders being questioned by regulators now were earlier approved by the same regulators.

IOCs are not the choice of committed, rational money. These orders suit intermediaries, whose aggressive bids and offers keep spreads tight and markets liquid – which is what regulators and market centers seek. But there is an unintended consequence to managing, manipulating, and incentivizing behaviors – which is what crafting orders that fit certain participants best does. The markets may not do with the incentives what was hoped and expected. And notice, too, that issuers, whose shares are the blood of markets, rendered no opinion on IOCs. We should.

Remember, our market system is a “maker/taker” model that relies on manufactured volume. Buying and selling is incentivized – induced with payments and types of orders that encourage middle men with no interest in owning shares to be aggressive. Why? People fighting to outbid each other should mean low spreads and competitive prices for consumers, regulators reason.

The problem? Consumers aren’t setting prices. The forces being incentivized are. We have no real idea what value buyers and sellers place on stocks, because the entire model is unwittingly obfuscating prices. Every time someone has an interest in buying shares, a fast intermediary may run ahead and re-price the market. This is couched as “price improvement.”

So, it should be no surprise that there were clouds of IOCs around the Flash Crash. This is exactly how the system is designed to function. It’s sort of like looking at the vortex in your bath tub after you pull the plug and wondering if the vortex is responsible for water leaving, or vice versa.

Think about it. Rather than the causal link between IOCs and the Flash Crash, we might ask instead why these IOCs drew out zero, zilch, nada “natural” liquidity. That’s market lingo for “real buyers and sellers.”

A mad scramble by intermediary systems failed to induce buying and selling. So those systems pulled out. So the answer to our question is that real buyers and sellers were uncertain of prices and unwilling to commit. Real money did not, and still does not, know the price or value of stocks. That should be a huge red flag fluttering in the market breeze like Old Glory on Labor Day.

Which brings us to trading today, the first after Labor Day. Why was the market down? Because the dollar strengthened. The DXY rose $0.85, or 1%, the reverse of the market. Last week it dropped sharply and markets climbed 250 points in one day.

This is precisely the same thing that is wrong with trading markets. Governments around the globe are manipulating, managing and incentivizing behaviors. The result is not a recuperated economy but instead that manipulation becomes an end unto itself. I hope we stop before we’ve been incentivized right back down to warring city-states.

Speaking of warring city-states, it’s that season when the sellside tries to out-schedule each other with industry conferences. Do you know how host firms of conferences trade your stock? What’s their order flow like? What do they do around expirations? Do they list the derivatives trader at the top (don’t laugh, many do) of research notes?

The nature of a firm’s order flow can tell you about the money consuming your liquidity (on those occasions when it’s real). If you need more growth-style money but don’t have lots of market cap, you might attend conferences hosted by major structured products purveyors.

Committed buy-and-hold money? Focus on firms differentiating with soft-dollar programs built around research, rather than ones with multi-asset-class trading capabilities. Sometimes small conferences are better. One committed investor can change the speculative and risk-management behaviors in your trading – because someone runs ahead and re-prices.

These ideas must now be in the modern IRO’s arsenal. And with that, have a blast out there on the road. We will – spandex, spokes, sunglasses and all!

While you ponder, a confession: We’re guilty of a bait and switch. If I’d written “implementation shortfall,” which is what I mean, rather than “missing the mark” above, which is what I said, I might be responsible for a chain-reaction narcoleptic catastrophe, people randomly falling asleep mid-word and banging heads on laptops, iPads, desks, afternoon pub beverages.

“Implementation Shortfall” is some software engineer’s term for not meeting your target in a trading scheme. By analogy, say you want to sell your house for $500,000 and you get $480,000. That’s implementation shortfall. In trading, it’s the difference between what the client wants and what you deliver. Say you’re tasked with selling 200,000 shares within a price range of $0.25, and with set trading costs. The degree to which you don’t meet that target is implementation shortfall.

In the IR chair, you don’t need to know all that stuff. But you should understand how implementation shortfall can impact how your stock trades. Maybe you can’t target the institutions you thought you could because at the trading desk, the implementation shortfall risk keeps trades from occurring. Plus, it’ll show up in your stock price. I’ve got a story to tell to illustrate it.

But before that, a word on trading since options expirations 8/18-20. The Dow Jones Industrial Average is off 440 points since. Data for clients show the chief cause not to be a rout from equities by informed money, but a shifting of the balance of resources. An institution at expirations decides to swap $500 million of tech stocks for a basket of bonds and Treasuries. The transaction does not hit the open market, but because the investor had been trading around his position before expirations and now has ceased, the effect is a gradual decline in the whole sector, because each algorithmic trade causes a ripple into the behaviors of other algorithms, many of which are there to match up trades now occurring at a lower level. The sector slides 10%.

It relates to algorithmic (mathematically managed) execution. If the placing of trades is less than random, machines identify an absence of randomness and game the order flow. What we have at the moment instead is a widespread effort to randomize so others cannot front-run orders and cause implementation shortfall. The result is chaos, combined with small shifts that produce big changes in price.

In markets where investment behavior, or rational thought, is principal price setter, value money would be at work, seeking value. We don’t have that. Instead, money seeks alpha or reacts to change. That’s why you see randomness everyday in trading.

Which brings us to our story. A particular basic materials small cap stock showed miniscule nudges in algorithmic trading on but two of ten program desks. Yet this smallest lack of randomness between overall buying and overall selling caused slippage of nearly 20% in the price. No value money tried to buy shares until the whole implementation shortfall had run its course by August 26. Perhaps because it too had been randomized. Unless you see these features in your own trading, you can’t truly say if your stock trades well or not (it varies, by the way, which is why IR must learn to be tactically nimble).

One answer to this problem is for IR professionals to color a broader palette of institutional relationships, not just buy-and-hold sorts, who have largely gone random. I was speaking with Jim MacGregor at IR/PR consultancy MacGregor Abernathy, and I agree with Jim that market structure almost demands that IROs court a coterie of aggressive hedge funds.

In a sense, hedge funds are the last institutional investors standing whose actions haven’t been randomized and ionized into a form of managed, program-driven behavior incapable of responding to value opportunities. I’m talking of course about active hedge fund portfolios, and not, say, DE Shaw’s Oculus portfolio. DE Shaw runs active money too. Their ability to act can alter the randomness in your market structure with one small hedgy step.

And now if you’ll excuse me, my schedule is experiencing an implementation shortfall.

Before we answer, we enjoyed New Orleans last week, despite humidity that had us struggling to distinguish the surrounding atmosphere from Lake Pontchartrain.

The NIRI Southwest Regional Conference concluded with brisk canvassing of key issues, wrapping on “would you choose an IR career again?” (Unanimous yes from panelists)

Bourbon Street hopped as usual, tourists with beer in cups labeled “giant donkey,” in so many words. We heard from the bartender at Pierre Maspero’s that the Lower 9th Ward and Chalmette still aren’t the same, folks picking up and moving across the lake to Covington. Many for-sale signs in the Quarter. We strolled by Brad and Angelina’s, who’ve done their part and taken one sign down. They didn’t look to be home.

So here’s your New Orleans Analogy about market structure. When the levees broke, water spread out, and equalized. The law of diffusion spreads molecules to fill available space. Physics. There are spreads, and there are spreads. Imagine how handy it would have been if at the spots where levees ruptured, the water just stayed in place, a sort of Moses effect. Alas.

The Game column in today’s Wall Street Journal by Dennis Berman notes how Senator Ted Kaufman thinks the SEC should revisit whether narrow spreads help investors. Good article, we recommend it. It brings us to our opening question. Often, a percentage of our client base moves in intraday aggregate by more than 5%. Size doesn’t matter. I can think of a client who reported a couple weeks ago and missed expectations widely that’s up 18% from after the call. Another client in the same timeframe beat, and is down 19%.

How? Did the minds of investors radically shift in days, such that intrinsic value, without one update to a metric, has shrunk or inflated by factors? What accounts for monumental value gaps from minute market spreads?

At the thought of what answer may come, you may grope for your monolithic moke of a brew (labeled otherwise in the Quarter) to gulp some down. Relax. No complicated constructs here. The answer is simple: by controlling both prices and volatility at the point of entry through the national best bid or offer and penny pricing increments, we create giant pricing wrinkles that move not according to fundamentals – fundamentals don’t set entry and exit points – but according to the levees.

Put another way, if the levees direct the flood away from equities to, say, US Treasuries, then all the business acumen on the planet will not keep your price frozen there at your rational price, Moses at the Red Sea, while the waters rush on.

You will be re-priced by everything else in the market. Is that fair? According to current rules, it is. We’re improving competition, so say those crafting them. If you like that, then be prepared to suffer market slings and arrows in spite of fine fortune.

Something to consider diffusing into that letter we suggested last week you pen for your C-suite on market structure: why not a test market that does the opposite of what we’re doing? No intermediaries. If you buy it, you own it. No price controls. You may bid or offer what you wish, and if someone agrees, more power to the both of you. No circuit breakers – let caveat emptor do its cleansing thing when or if it must. Voluntary membership by public companies, who get to offer a set number of shares there.

Why not? The levees didn’t work in New Orleans and constricting prices and behavior isn’t working in the markets. Sure, it might take the spirit of Andrew Jackson from 1812 in the Big Easy. But that worked out pretty well.

Recently Kate Welling at Weeden & Co. interviewed Prudential’s vice-chairman, Mark Grier about being public in 2010. I read it and asked if we could highlight it here. It’s critical knowledge for IROs and public-company execs now.

Prudential (NYSE:PRU) has market capitalization of $26 billion, 38,000 employees, some $700 billion of assets under management. Before the May 6 Flash Crash, Vice-Chairman Grier had lamented to the SEC about the lack of fundamental content in stock prices.

In the interview, Grier said: “What happens when the market’s fundamentals are algorithms and signals and pings and all the stuff that goes on between the machines? What happens when the machine doesn’t know whether it’s buying Prudential or McDonald’s or Continental Airlines? What happens when that is really the way in which stock prices are being determined?”

Grier said, “I believe that this disconnect between company fundamentals and stock prices is a much more serious source of systemic risks than anybody is giving it credit for. The systemic risk – if the markets are materially wrong, if they are broken down, if they are not reflecting fundamentals, and if, as a result, real investors are hunkering down and not participating – could be devastating.”

“Stock prices,” Grier said, “are reflected in corporate accounting statements, in the financials, in earnings, in capital, in mark-to-market valuations, in regulatory capital. Then we have the rating agencies that use them. We have all the headline risks that go along with the market volatility as they affect employees and as they affect clients.”

And what if the whole underpinning construct isn’t fundamentally priced? Grier said, “There’s a basic conflict between using the stock price as our report card and the way in which that price gets set.”

Grier talks about the financial crisis of the past two years. “Instead of reflecting fundamentals,” Grier says, “the market itself became the fundamental. And that’s not the way it’s supposed to work…everybody is scratching their heads trying to figure out what’s going on, and that gets translated into expectations and plans and spending and pretty soon into real behavior. So pretty soon the economy was going through a cycle that was driven by the market itself.”

These are but a few nuggets from Kate Welling’s treasure-trove interview. Read it. Pass it on to your CFOs and CEOs.

We can’t solve the problem until we first understand it. The problem is that the market only marginally reflects what we do every day. Changing it starts with IR professionals getting a grasp on how markets work.

Second, companies need to be involved in setting rules for stock markets. Public companies are the life blood. Yet rules are made by traders, for traders, and companies are silent. Imagine if supply and demand were irrelevant in the grocery store and price-setting power belonged to a cartel selling groceries. And then suppose that economists considered prices to have been set by supply and demand. Could you trust their predictions?

Here’s a challenge, IR professionals: Educate yourself about markets. This interview is a great starting point. Write a letter for your CEO to submit to the SEC, a position statement on our capital markets.

The first step toward change is forming an opinion and expressing it. These are our capital markets, after all.

It’s about time for a Sazerac.

It’s a decent name for a rock band, yes. But it means “what stuff can you do with this?”

Traders want actionable data – something to drive opportunity for profit. Investor-relations professionals want actionable tools – something that’ll improve stock ownership, share price, results of IR effort.

Knowing who owns your stock is good. But what actions can you take? Talk to sellers? That’s uncomfortable. Plus, unless you’re screwing up, selling is a compliment, an investment objective. The sellers should well buy again, when the time’s right.

How do you know the time’s right? Ownership and targeting data are fine but limited if you don’t know who or what is controlling your liquidity. Without knowing your trading behavior, it’s difficult to accurately measure actions, plot outreach, and target investors.

Money won’t simply take a flyer because you run a good business and your IR team is suave and debonair. Today, institutions cannot afford to buy stocks in a vacuum, without respect to how the first 1,000 shares alter baskets, ETFs, derivative trading tactics and all the rest swirling around your liquidity. Institutions mind risk-management obsessively now, which is about market structure.

We track data for a living. For clients, we graph volume from prop traders like RGM Advisors, against, say, executed order flow for Credit Suisse. We observe how the behaviors of the two are eerily similar in some issues (and not in others). RGM is a scientific, machine-learning trader.

Say you’re using Credit Suisse for support on a non-deal road show, but most of their volume is trend-driven. That knowledge should inform what investors you ask Credit Suisse to bring from its client ranks. You’ll want high-turnover GARP or growth money, because that’s the kind likely to wade into a mathematical market. It can be a win-win – Credit Suisse likes those customers, too.

Market structure can shape who you choose for support. Some firms have high-turnover clients because their trading products facilitate high-speed trading. If you’re after a different investor-class than what a sellside firm tends to serve, you might use a different firm with a lesser trading operation – and thus more dependence on its research. Great story isn’t enough. If your market structure doesn’t suit the money you’re targeting, you’ll waste a road trip.

IR professionals should become more tactical. Use the big picture to do it – beyond story, to structure. The final frontier for IR effectiveness rests on the actionable quality of market-structure data. Do you know how much of your daily volume is speculation? What kind of investor should you target tactically, in context of your IR strategy, if more than 50% of your volume is arbitrage? These are important things to know now.

Here’s a product announcement from Direct Edge yesterday:

ACK – SPX Accelerated Return Notes due September 30, 2011

CDK – SPX Capped Leveraged Index Return Note due July 27, 2010

ELD – WisdomTree Emerging Markets Local Debt Fund

MHM – SPX Market Index Target Term Securities due July 31, 2015

As products like these roll out each day, there’s something else for that money you’re meeting in Chicago to choose besides you. Kick it up a notch. Target more tactically. Sometimes you’re right for high-turnover hedge funds. That alone is a new notion. Then, be ready, using market structure as guide, to get on the radar of conventional fund investors before hedge funds rotate.

It’s not an exact science. But these are tools with abundant actions. If you’re expert in your own market structure, your results are going to be different from those of other IROs, because you’ll think differently about what actions you need to take.

You’ll be the IRO for the 21st century.

The DXY, the spot market for the US dollar, declined 7% in July. Stocks were up 7%. May was a good month for the DXY, which rose from 81 to 87, roughly. May crucified equities and gave us the Flash Crash on the heels of a surge in the value of the dollar.

Is it six of one, half a dozen of the other? The dollar in your pocket loses 7% of its purchasing power versus other currencies in July. Stocks appreciate 7%. Call me simple, but it seems that when a thing you buy is worth more because the thing you buy it with is worth less, that these sort of cancel each other out.

Which brings us to making and taking liquidity, the main method by which traded shares move today. In this “maker-taker” model, market centers pay participants to provide shares that attract customers, and charge customers to consume these offered shares. The spread is profit. At BATS Exchange the cost gap between consuming and providing shares is one penny per hundred shares. On the Nasdaq and the NYSE it’s about five or six cents, but narrows if you offer tens of millions of shares daily.

This is crucial to understand. If you conclude that your volume is buying and selling meeting up, that’s true only sometimes. Most of the time, buyers are consuming shares offered by other market participants whose principal job is to keep the liquidity flowing, for pay. This is why high-frequency trading exists, really. Technology and human ingenuity adapted to market structure built around incentives. So now, there are systems doing both the providing and consuming, and if the spread between the two prices is a penny, and your stock moves two pennies, why that’s riskless profit. Mind, that’s harder to do than it seems!

Where do shares come from that liquidity providers offer for sale? Somebody always has inventory. Sometimes it’s coming from major broker-dealers whose millions of retail and institutional account holders don’t realize that their positions are used to generate profits for market-making operations. This is the main reason why Citadel invested in E*Trade. In many other cases, shares simply move from place to place at high speed.

To do that, traders can arbitrage different structures. Most market centers now, like BATS, Nasdaq, Direct Edge, and so on, are “time-priority” models, where the first to show up at the best bid or offer gets to complete the trade. On the NYSE floor, it’s a “parity” model that gets apportioned to all parties priced at market. So if you’re fast enough, you can move shares from parity to time priority and back and forth. This constant replenishment generates revenues for the firms doing it and looks like massive volume. It’s often the same liquidity appearing again in different places.

What’s good about this? It keeps price spreads tight, and it ensures that vast numbers of securities, regardless of appeal, offer anyone wanting to transact in them an easy, ready market. If you’re asset allocation managers, these are great conditions. Think of it like swiping your credit card through a reader rather than needing the exact cash price each time you buy.

What’s bad about it? Number one, market centers are motivated to entice volume that isn’t real. They make money through transactions. More transactions, more data to monetize too. This is not the fault of exchanges. They are businesses producing returns for shareholders. But if parties matching your product with buyers and sellers are financially incented to attract middle men, in time your market is most appealing to intermediaries and least appealing to real buyers and sellers.

That’s what maker-taker models encourage. Transient intermediation. It’s the most reliable way to make money. If 80% of volume is moving from place to place, and you’re in the 20% buying and holding, what form of activity is more likely to produce a return on investment? Clearly, making and taking liquidity, not owning things.

But the biggest problem is the same one afflicting the US dollar. In stock markets now, the maker-taker model has removed the focus of market participants from the value of businesses to the supply or demand of shares. The study, manipulation, and maximization of liquidity movement have come dangerously near to disconnecting underlying business fundamentals from stock markets. Intermediaries trade stuff for spreads. They don’t own investments for their intrinsic value.

This is true of the dollar too. Its value bears no connection to underlying national productivity or assets. That’s the essence of “fiat” currencies, and we’re near now to having “fiat stocks” too. Movement of the dollar from place to place alters the value of all the goods and services denominated by it. In time, no one knows the value of either the goods and services or the currency in which these things are valued. Then, the data derived from transactions in it are incorrect or distorted, too.

Think about this: does the same thing happen in the global economy that we described with the DXY and stocks? What if it’s just yin and yang of currencies and goods and services, with no real change in economic output? That path would lead almost ineluctably to large national debts.

Oh. Hm.

Passing through last weekend, we had to concede that Iowa was in fact a place of surpassing and bucolic beauty, with its rolling corn-planted hills and manicured farms. The heartland at Independence Day reminded us that this land of ours and yours is jeweled.

Anyway, we’re a day late this week because it’s a long way from Bratenahl on Erie to the banks of the Platte.

Speaking of eerie, your management teams must be wondering what caused stocks to cross chasms today to the upside. Do you think investors suddenly decided stocks were cheap? To paraphrase Saturday Night Live…really?

No, today is why every corporate IR professional should develop a rudimentary grasp of market structure. The way of the world now in trading markets is more like the movement of tides than the patient fashioning of edifices. To do your job with purpose and ease of mind, it’s helpful to know when the tide turns. We said last week that stocks should benefit from a return of capital after the 4th of July. We saw surging proprietary trading by liquidity providers July 1-2, indicating that software systems expected money to arrive this week.

How do software systems find bargains where investors don’t? They look at different data. To explain, let me tell you a story. Yesterday, we traversed the plains in Kansas from Fort Riley to the Colorado border and west to Denver. Once, that area belonged to the southern Cheyenne tribe. For history buffs like me, it’s living history, crossing that grassy canvas. The Sand Creek massacre site is southward. Battles were fought with the legends of the Cheyenne people at Beecher’s Island and Summit Springs just north of I-70.

The plains people had a narrow, rational worldview. Life revolved by seasons on a finite patch of earth. It worked in predictable fashion. It wasn’t possible for most of them to study different data and reach new conclusions. Now suppose you could sweep up and away in Google Earth fashion from the trace remains of Fort Sedgwick, west of Julesburg township (which the Cheyenne twice looted and burned), and observe continents and hemispheres. What’s happening on the Smoky Hill River isn’t quite so important now.

Trading software sees continents and hemispheres. If it’s summer in Patagonia, it’s time to ski Aspen. By the same token, the movement of money and trading liquidity isn’t limited by individual financial performance, but by where the sun shines and where the skiing’s good – so to speak.

How long will it last? No one knows these days, but the tides move fast. We suspect we could hang ten till July 21. The cool, contemporary IRO won’t try to control the seasons or tides. But it’s good to know about them so you can prepare, enjoy the autumn colors, and abide with a sense of purpose and ease. It beats the agitated uncertainty that can linger when you don’t know what’s over the next knoll. And it certainly beats becoming an archaeological curiosity.

All analogies break down. So let’s finish with a more mechanical explanation. Trading systems can incorporate multi-dimensional data, including the supply and demand of currency, derivatives and stocks. That data is often quicker to imbalances than are rational bottom-up investors looking for intrinsic disconnects between market valuations and financial metrics.

We are not in Iowa, or Kansas, or Fort Sedgwick, anymore.

That’s the essence of conversations I had yesterday with two investor-relations officers. It’s tempting to suggest asking Al Gore about why things that should be up are instead down. But that’s an old joke. And it won’t make you more valuable in the IR chair.

What will enhance your value is knowing what to tell the CFO and how best to do it. Whether you provide a daily, weekly or quarterly update to management about factors behind your stock price, you should incorporate comments on your market structure. Not just the old conventional stuff.

Think of market structure this way. If you operated a retail store, and each week you summarized the state of things in your store for headquarters, you’d talk about financial performance, products moving off shelves, the traffic driving sales, and trends. Something like that, anyway.

Same with your stock’s “market structure.” There’s only one product, your shares. But otherwise, you’re assessing behaviors and measuring them to understand how your store serves its market. If you measure only one behavior or one group of customers, that’s not an accurate picture of what’s happening, and it’s bound to lead to head-scratching and questions like, “How come our stock is down when it should be up?”

What do you tell your management team about market structure? Well, say you’re providing a weekly brief on trading activity. First define your metrics – the things you’ll track. For a weekly report, you don’t want to bury them in mind-numbing data. You want a small set of consistent measures. Begin with things like the percentage premium or discount in your closing price for the week versus the trailing 20-day average price. Volume versus 20-day average. Daily average trades and shares per trade, and daily dollar flow – that is, average daily price multiplied by average daily volume.

In time, you can provide a forward-looking expectation from data – but you must accumulate metrics first. As your management team becomes accustomed to market structure information, move to simpler but more compelling information, derived from your data: What’s setting our price? What do investors think? What are traders and risk managers doing, as opposed to what investors think? What’s likely to happen to our price next? These conclusions are extrapolated from data.

Before you know it, you’ll own your market structure. You’ll be the expert on matters related to your trading. This is the first step in a larger process of making a home for market structure in the IR department just like corporate governance has become an IR bailiwick.

Why must you own your market structure? Because roughly 90% of volume today BEHAVES either according to market risk or in response to speculative opportunity, and only a small amount is rational, or seeking long-term returns. If IR spends 90% of its effort on 10% of the market, well, at least something should be known about the rest. Or else, how can you draw accurate conclusions about stock performance, or even investor sentiment?

It’s up to IR to set that agenda and drag management kicking and screaming into the 21st century of how trading markets work.

To conclude, a challenge for you IR readers: Look up the DXY – the dollar index futures contract – and compare it to the Dow Jones Industrial Average, over, say, the past year, or the three months around the May 6 Flash Crash. What does it show you?

Snot Mark is also a tempting description for what’s happening behind share prices and volume, at least at times. But Global Statistical Arbitrage is more accurate, and widespread.

It’s a term that can induce instant narcolepsy too, so we’ll make it interesting. The Nasdaq can be up, the Dow down. Your stock is up, your nearest peer, down. Overnight the Asian markets are up on “renewed enthusiasm,” while by mid-afternoon the following day Europe is down on “rising pessimism.”

It’s statistical arbitrage on a global scale. It can be confused for other things, such as investing, which it is not. Suppose you were buying and selling Robert Graham shirts and doing the same with off-the-rack Macy’s brand clearance shirts. Most times, the price difference between the two asset classes is constant, but slight differences in shirts, fabrics, times of day, and customer interest produce little gaps. It’s on those that you make your money.

To the observer, it would appear that a brisk business is being done. The Robert Graham shirts are really moving and that discount rack keeps clearing out. Ah, but little actual buying and selling is occurring since most times you’re procuring and dispensing the same shirts over and over, with little risk. I’m reminded of what a sharp Israeli client once said, no doubt borrowing it from a time-tested lexicon of smart observations: “We don’t confuse busy with productive.”

Arbitrage often gets people to mistake busy for productive. Arbitrage is the former. Traders weave currencies, futures and options, and global equities into an arbitrage model to capture small, quick price gaps. European banks are doing it. Classic institutional money managers are doing it. Broker portfolio trading schemes are doing it. The catalyst for the explosion of the high-frequency version is monetary intervention over the past two years. It distorts prices – creating a “Trader’s Paradise,” to borrow and twist that old rap song sung by Coolio and penned by Stevie Wonder.

By contrast, arbitrage is risky in markets without price controls or monetary intervention. If there’s no best bid or offer, no mandated one-penny spread between price points, how do you assess your arbitrage risk? You can’t. Yet the Synthetic Market Rip on May 6 is likely leading to more controls, more intervention. Arbitrage opportunity, and therefore risk of another synthetic rupture – if your market is dominated by intermediaries you don’t know its real value – increases. It’s going to happen again.

Solutions are simple. Remove price controls. Expand the supply of currency only when saved capital increases significantly, if at all. That way, the medium of exchange isn’t being used to correct gross failure but instead to match investment capital with opportunity.

And wait! There’s immediate good news beyond simple solutions. One upshot to arbitrage markets is that they winnow some wheat from chaff. We see stark market-structure differences between companies with tight messages and IR outreach adapted to market structure, and those doing the same old things the same old way.

Price is not the measure of solid IR. Sometimes great stories have extended gaps between the rational price and the noise from intermediaries. But real value returns as fulcrum. Knowing what’s productive in your trading and what’s just busy makes you cool in crowds of intermediaries. Alas, there’s a lot of busy right now, and not much productivity. Forewarned is forearmed.

The SEC last week sued Goldman Sachs for misleading investors about certain collateralized debt obligations during the subprime mortgage meltdown. We’re not a news rag so we won’t regurgitate the facts and accusations. We’d observe, as did a fine Wall Street Journal blog at Deal Journal yesterday, that the investors supposedly mislead were the world’s most sophisticated CDO investors, that Goldman lost money, and that the disclosures about these swaps that always require two parties with opposing expectations of outcomes were of monolithic proportion. Up to and including acts of God, everybody party to them knew the outcome could be good, bad or ugly.

Which leads to trading last week. Options expired April 15-16 when markets gyrated. Markets were up a hundred points the day before, April 14, then down a hundred points. Today, April 20, volatility futures expired, and short-term trades between stock and index options last week and volatility moves today could pay with little time decay or risk for the savvy trader. There was actually more fundamental buying on April 14, the up day, than fundamental selling on April 16, the down day, data indicated. It’s not always about the news. There is no better proof than what happens under the skin of the market with monthly expirations.

So what’s it mean? Market structure tells us that money thinks the Goldman accusation is hooey.  And speculators were taking advantage of disruption in the markets around expirations. It’s been a fantastic run in the markets since expirations in March when we told you that risk hedges were perhaps the largest we’ve seen. Traders bet big on equity gains from March 19 to April 16, and the move paid off. And the dip on April 16 had little to do with Goldman Sachs.

We promised examples about using market-structure analytics, so we’ll leave you with one. Before its analyst day recently, a large public company wanted to set expectations. We could see reticence on the part of active money to pay up for shares. Speculators were working hard to foster intraday trading ranges, which meant that investors had uncertain views (speculators often know). Thus, meeting expectations alone would be positive, despite high expectations this spring for outperformance.

The stock rose a dollar the following day. Real or Memorex? Often, traders create momentum around analyst days – not difficult in this age of anonymity and electronic trading. But data showed that real money indeed paid $0.75 cents more. Price held up even during the recent market pullback.

It’s darned cool in the IR chair not having to guess if your trading activity is real or noise. As is using that information to make management wonder how in the world you know the stuff you know.