I don’t mean gambling, but real cards. You’re engaged with some seriousness. You’re watching how you bet and when, reading the players ahead and after you.

Then The House starts doling out stacks of chips. Would you play more or less cautiously if you had free chips?

Apply this thinking to equity markets, IR folks. In trading data, we saw European money sweeping into US equities Nov 28. Why did markets trembling Nov 25 decide by the following Monday to up the ante in risk-taking? Primary dealers implementing policy for global central banks also drive most program-trading strategies.

Thus, European money surmised that central banks would intervene, and their behavior reflected it. The rest caught on, and markets soared Nov 30 on free chips from central banks. It was short-lived. By Dec 2, we saw institutions market-wide assaying portfolio risk and locking in higher derivatives insurance. The chips were gone.

Money sat back expectantly. On Dec 8, The House delivered chips as the European Central Bank lowered interest rates. That’s devaluing the euro. At first, cheapening the euro increases the value of the dollar – which lowers US stocks (a la Dec 8). But if you’d hedged with derivatives as most of the globe did, you bluffed The House. Plus, the Fed will likely have to follow Europe’s bet up with a see-and-raise to devalue the dollar back into line with the euro (expect it next week, but before options expirations).

In poker, having “the nuts” is holding the best cards, and knowing it. Central banks have given arbitragers the nuts.

Arbitrage is a buy-low/sell-high strategy that depends on gaps. Say you’re in rush-hour traffic and all the cars are packed together and then a little gap forms and somebody shifts over from another lane. That driver has just arbitraged lanes of traffic. Now suppose suddenly a new empty lane materialized?

That lane is a stack of free chips in poker, or monetary intervention. A windfall. Global statistical arbitrage is money in planetary slosh after gaps. Remember, money can trade your equity, your options and Treasury futures in one fell swoop, in seconds or less. Or any random collection of electronically tradable securities from here to Stockholm.

Gritty rational money has bought growth issues, too. If inflation in equities is likely because The House may wander through with more free chips, that’s “growth,” not value (but is inflation growth? Hm.).

Generally, arbitrage makes life difficult for thoughtful investors. Investment certainty requires a fair and simple game. You buy in, you play your best, you win or lose. No free chips from The House.

So expect arbitrage. Expect volatility.

Burstream, apparently. The firm claims it can serve up actionable, meaningful trading data, no matter what market mayhem, in 600 nanoseconds. That’s 600 billionths of a second. The catch? You have to trade at the Nasdaq.

Burstream’s system is being installed at the Nasdaq OMX market center in New Jersey so the exchange’s important proprietary-trading customers will have a split-second – taken to the extreme – advantage. Customers wanting to use these superfast capabilities will be able to load their algorithms onto Burstream servers parked next to boxes housing the Nasdaq’s trade-matching engines.

Burstream systems will go near the Chicago Mercantile Exchange too. The idea is to unify data streams on stocks, commodities and derivatives so decisions about trading on divergence can be made faster than ever before possible. This is, of course, arbitrage.

Burstream says at its website: “Enable your high frequency trading algorithms to hit liquidity when it is revealed. Trade through market bursts while competitors exit the market. Sustained nanosecond speeds, even during message bursts will give your latency-sensitive algorithms a performance advantage.”

What makes Burstream special is its use of field-programmable gate-array chips (FPGAs) that can perform multiple calculations simultaneously, thus delivering a speed advantage over conventional hardware-processing techniques.

We have clients in the FPGA design and manufacturing businesses whose shares are publicly traded on the Nasdaq. IR pros may appreciate the irony. Companies who use the public markets to raise capital and build growth enterprises are being arbitraged via nanosecond data at the exchange that lists their shares.

We don’t fault the exchange per se. Exchanges are for-profit businesses today. They earn money by capturing a share of the quote and trade data on the consolidated tape. The amount is determined by how often securities at their market centers (most have more than one) quote or trade close to the National Best Bid or Offer. Thus, liquidity providers like Merrill Lynch, Instinet and Morgan Stanley are paid to quote at the Nasdaq. Payments come in the form of trading rebates for posting shares at the Nasdaq that offset against fees for removing them.

If the Nasdaq can speed up trading and arbitrage, more data are generated, more trades and quotes. It’s a virtuous circle: pay liquidity providers like Merrrill and Morgan to make sure liquidity exists. Encourage arbitrage with the fastest data systems to hit it. Capture more quotes and trades. Monetize consolidated-tape data. Repeat.

This is how exchanges generally work today. While rational investment is one behavior, it’s small today (and it does not re-price shares in nanoseconds). For obvious reasons. If you think about it.

We were there, clanging bells and hooting our hearts out. Here is winner Levi Leipheimer readying for the time trial that put him in yellow. The peloton left Avon here for Steamboat, and Levi is visible midway in yellow. At the finish, some 250,000 jammed downtown Denver for the epic, lapping conclusion. We are proud of American cycling and our state’s awesome organizational effort.

Speaking of peloton, Wall Street Journal reporter John Jannarone wrote Monday in the Heard column called “Traders Seek Salvation from Correlation” about how stocks race in formation. It’s among the best pieces we’ve seen on modern trading. Jannarone says that S&P 500 stocks show 80% correlation in the past month, meaning eight in ten move synchronously.

This is a source of distress for IR folks trying to distinguish a strong company story from the herd. We’d argue that rather than slamming the collective IR noggin into the burgeoning brick wall of macro-focus investing that you instead track program trading and establish what level is acceptable – and use it as an IR success measure. We wrote about this last week, so we won’t retrace the trodden path.

Why a mirror image across so much of the market? One driver Jannarone posits is Exchange-Traded Fund investing. According to Credit Suisse, these drive some 30% of daily stock volume. Jannarone also notes that trading in S&P 500 E-mini futures contracts is more than four times the combined daily volume of the two biggest S&P 500 ETFs, the SPDR, and iShares S&P 500 Index ETF.

It’s a reasonable hypothesis. If institutions trade ETFs and indexes, and hedge them with futures and options, and try to increase yield by leveraging assets with yet more futures or options in, say, currencies and Treasuries, stocks will correlate in models, and markets will reflect high volatility due to continual adjustments to these layers of equities and derivatives.

We see it, measuring speculative and program-driven trading for clients. These two dominating behaviors are also increasingly correlated. More money is pursing short-term “investment” horizons designed to produce returns in days.

Jannarone worries as do many investors that correlation is likely to last because of currency concerns. We agree. So IR should quantify market activity and report on it regularly to management. Otherwise, we’re bystanders. It’s better turning lemons to lemonade than sourly wondering when rational investment will return.

We suggest you hop on that bike and ride it.

Debt chaos, sour economic data, sure. We’re not market prognosticators, we track behavioral data. Under the skin of the news at market level, institutions shifted to managing portfolio risk about July 21. These events were observable. Algorithmic execution changed, and we saw what started it and what followed.

Large diversified asset managers swapped out of equities. That means they assigned the risk in portfolios to others through agreements that traded risk for safety at a cost. Why not just say “investors sold to manage risk”? It’s not accurate and it won’t be reflected in settlement data.

Of course, hedging produces a range of consequences too. Those underwriting hedges themselves hedge the risk they assume. That prompts speculating in whatever instruments are being used to hedge the hedges. The idea is to offset every point of exposure – like double-entry accounting, a credit for every debit.

Consider the Treasurys market – the one in peril till today. Primary dealers ranging from Banc of America to Goldman Sachs make markets in Treasurys. Average daily trading volume in Treasurys is more than $500 billion. Bond trading in total in the US averages more than $950 billion daily and nearly 80% is government securities.

There is searing growth in Treasury futures and options trading, which increased by 48% in the March quarter at the Chicago Mercantile Exchange. The daily currency trading market averages nearly $4 trillion in notional value. The same firms that dominate equity program trading and the Treasury market – the biggest bulge-bracket firms – are kingpins in currency trading.

GETCO, which stands for Global Electronic Trading CO., says it focuses on “helping investors efficiently transfer risk.” GETCO is both a designated market maker on the NYSE floor and a global proprietary trader in multiple asset classes. GETCO is an example of the role intermediaries play now, whether liquidity providers or market makers. They move money fluidly from place to place so debits and credits offset in large institutional accounts, and risk diminishes.

This is what institutions were doing starting July 21. The effects of hedges to manage risk, and hedges to manage hedges, and speculation between, is now afflicting US equities. Daily dollar volume in US equities is about $100 billion, a fraction of some other asset classes. Reweighting portfolios to reduce risk by moving from assets to derivatives has a big effect on market value.

Which brings us to large traders like GETCO. The SEC issued Rule 13-h1 requiring large traders – those trading more than $20 million daily or $200 million monthly in NMS equities – to register. There is a fear that these large traders are culpable for market risk.

Yet large traders exist principally because SEC rules fragmented markets and turned them into automated, high-speed risk-transfer devices rather than places where capital is formed. The construct hinges on liquidity from large traders. And the SEC is now penalizing those participants, whose presence they encouraged.

And what about trading in currencies? Bonds? Treasurys? How about grey-market securities where NMS rules don’t apply? Imposing restrictions in one class without doing so in another will produce migration and regulatory arbitrage. And what’s to stop large traders from fragmenting operations into units that trade less than $19 million daily?

The rule is 179 pages long. There are exemptions. The SEC admits it lacks jurisdiction over certain foreign large traders whose countries’ laws prohibit disclosures the SEC seeks. They can apply for an exemption. In effect, the SEC will demand more disclosure from traders in the land of the free where privacy is sacrosanct than what many foreign jurisdictions allow. Take Brazil’s Latour – now #6 among program traders.

While not the intent, the effect may be that US firms are disadvantaged in their own markets by rules that don’t apply to international traders. What’s more, only firms that exercise discretion over funds can qualify as large traders. Large traders might contract with agency brokers and lease their algorithms to skirt the rule.

Rule of thumb: If your rule does not apply to everyone, scrap the rule.

And we will have accomplished exactly jack-zero in preventing nefarious behavior. We’ll have driven more competition from markets, created greater cross-asset-class risk, and stultified and constipated markets where rules are supposed to avoid impeding free function. And worst, we will have exacerbated the confusion, complexity and inconsistency crippling our capital markets.

We don’t embrace high-frequency trading. But another 179-page rule is no solution, and no help to public companies. The path to freedom and health is simple: junk the rule-structure that favors high-speed arbitrage. Reg NMS. We don’t need a national market system. Money could not arbitrage prices in multiple markets if the SEC didn’t demand that all the markets display their prices. I’ll be blunt: it’s crazy.

Imagine how markets would thrive if we blitzed this convoluted mess and started over with basic rules that everybody regardless of size or speed could follow.

Sentences like that are why alcoholism remains widespread. It’s also the reason IR folks don’t want to know how markets work. Too complicated.

Yet if we’re brutally honest, we know we should understand more. I mean, you can’t claim to be a great Yankees fan and not know the rules of baseball.

The sentence above from Nasdaq Reg NMS FAQs says: If I’ve chosen to fill my order up to the designated number of shares at a set price without leaving the Nasdaq to check for better prices elsewhere, suppose the time to complete the order is something besides “immediately or forget it.” Will that order be accepted at the Nasdaq?

This is how markets work. If you want homework, Google “Rule 611 Reg NMS.”

Buyers today are entitled by law to get the lowest price for a stock. In the 1970s, Congress got together and brooded at length about how to improve competition. As this forum of politicians deemed itself superior to thousands of years of unfettered human commercial interaction, it determined that forcing people to trade at the best price was an improvement over people figuring it out for themselves.

Before the rule was even in effect, exemptions flurried. Because obviously getting the best price begs a giant question: For What Quantity?

To address vast variances, the SEC decided on Rule 611, called the Order Protection Rule.

Remember (if you’re old enough) playing tag and getting to yell “Olly, Olly Oxen Free”?

ISOs are olly-olly-oxen-free orders. If you’ve got an ISO for 1,000 shares at the NYSE, it may only find 10 shares at the confluence of your specified price and the lowest one available. If the order is immediate or cancel (IOC), then it returns with 990 shares unfilled. If the Time in Force (TIF) is “Day,” then throughout the day the order is going to loiter at the exchange where it’s been routed, filling the rest if and when its price is hit.

But it doesn’t have to leave the NYSE for the better price at a “protected quote” elsewhere. Like other situations in which prophylactics offer a measure of security, a protected quote is one that, shall we say, comes with confidence. A protected quote is by definition immediately and automatically accessible. Therefore, no manual quote – somebody entering a trade – is protected.

Protected from what, you say? Somebody skirting it, like an ISO can. So if you want your price to be guaranteed to display, then it must be an automated order.

Do you see the problem? To comply with Reg NMS, machines and markets must automate orders. It’s the only way that they get protection. That means machines have been given an edge over humans.

At the same time, regulators have granted a bunch of exceptions to exchanges that let institutions work around those prices. What then do you suppose the displayed prices reflect?

Compliance.

Not the best value, or even the best price. Perhaps not even real intent. What happens when compliance requires that you do one thing and believe another? Deception, sleight of hand, arbitrage.

On the cattle ranch of my youth, when we brought cattle to market the auctioneer didn’t rattle off a bunch of prices to a set of shill bidders batting worthless and hollow trades back and forth while the real pricing was occurring somewhere else unknown to us and anyone else in the room.

The only thing required for a fair market is that buyers and sellers are satisfied that nobody is gaming the price they’re getting.

The equity markets today are the grand archetype of gamed prices. And that means, IR folks, that you need to do more to know the REAL price of your shares, and who’s setting price, be it investors, trend followers or arbitragers.

Further, the IR chair should be leading the campaign for issuer involvement in market rules. We’re doing our part to help with the IDI (and we’ll have an update soon – we are talking with folks at the very highest decision-making levels. But I guarantee that change will only happen if the household names trading on the Nasdaq and the NYSE demand it – so demand it!).

Oh, and the answer is: Yes. The ISO with a TIF of something other than IOC is accepted at the Nasdaq. You probably have thousands of those bouncing around in your volume, arbitraging spreads between protected quotes and undisplayed prices.

Traders have not to my knowledge named them “Charlie Sheen.” But alert reader Walt Schuplak at the Market Intelligence Group in New York sent an item about rogue algorithms. Our friend Joe Saluzzi at Themis Trading wrote on it yesterday.

Joe explains that certain trading practices create arbitrage opportunity. Profiting from divergence isn’t bad of itself, Joe notes. But if the chance to profit is fostered where divergence could not or would not occur on its own, it raises fundamental questions.

Bloomberg writer Nina Mehta wrote today about the Australian government’s initial rejection of the Singapore Exchange’s effort to buy the Oz stock market. Singapore is a shareholder-owned exchange. The Deutsche Bourse is public. Same with the InterContinental Exchange, throwing in with the Nasdaq on a bid for the NYSE, both of which are public too. The London and Toronto markets are run by public companies. BATS may IPO.

The shares of all these firms in theory compete for investment with your shares. For exchanges, the profit and growth drivers are data and transactions. In US markets, revenue from tape data is divided up according to “quote share,” or how often an exchange is quoting at or near the best bid or offer for a security. Revenues also come from market-access fees, data products, and trades. Growth comes from propagating these drivers through more asset classes. Listing is a small piece.

Stay with me here. This is a crucial concept to grasp in the IR chair. These are your marketplaces. How much money do exchanges make if your stock trades 500 shares daily? Exchanges don’t earn commissions; they generate fractions of pennies per share.

Exchanges need companies with billions of shares outstanding. They need options and swaptions, fixed income and wholesale counterparty clearing, commodities, carbon credits, contracts for difference, futures, swaps and complex derivatives – trading at high speed ideally, with vast webs of manufactured arbitrage, all producing data and transactions.

And there’s more. The exchanges write the rules filed with the SEC that determine what transactions will take place, in what fashion, and at what cost. Do you get to script the terms for how your customers buy or sell your products and have those rules turned into regulatory mandates? Do pharmaceutical companies pen the regs governing generic drugs or the approval process?

I am not criticizing the exchanges. They are dealing with the reality handed to them.

But I hope you grasp the monument to cognitive dissonance that has been erected in the securities-exchange business today. Exchanges are counting on machines to create arbitrage opportunities that shouldn’t exist, because that’s the core growth driver. And the fees for adding and removing shares at the exchanges – the very driver behind arbitrage – are approved by regulators.

In essence, the exchanges can only thrive if everything that you hate and which scares you increases. Clearly, companies need better trading data at minimum. And an alternative exchange model.

If every public company decided that the Berkshire Hathaway model was best – a million shares outstanding, priced at $100,000 – the entire global exchange system, and all that HFT and a great portion of the webbing of derivatives totaling $500 trillion or more would be superfluous.

And…wait for it…which model typifies the Federal Reserve? Is the dollar in finite supply of great value or in a vast and churning sea of HFT?

I’m glad when winter solstice passes, that shortest and gloomiest of days. After that, we’ve rounded the corner from darkness toward light no matter what winter yet holds.

But in trading markets, darkness thrives. Monday in the Wall Street Journal, Jacob Bunge, who covers the exchanges, wrote that 34% of trades in December matched up off the exchanges in “dark pools,” doubling from last year. Why is money streaming off exchanges in search of darkness, and does it mean your shares aren’t priced right?

Let’s clarify “dark pools.” There are trading facilities like Liquidnet, Pipeline, ITG Posit and Aqua that offer twists on paths to more share-supply. They’re like the Millionaire Matchmakers of trading, finding liquidity love for willing parties. But these independent platforms and their broker-dealer counterparts at Credit Suisse (Crossfinder), Goldman Sachs (Sigma X) and Barclays (LX) command about 12% share.

Where’s the rest? Let’s use an analogy. In the BCS championship bowl game between Oregon and Auburn next week, the stadium will fill up with fans. That’s like an exchange, or any place including dark pools where people gather for a purpose.

The other 22% of your trades are occurring in undefined places. It’s more like online gaming, where the game flows to players who gather no particular place. The trades meet and the meeting is logged on the tape and rolled into your daily volume.

Like this: A Merrill/BofA algorithm handling a rebalance for a mutual fund flings bits across thousands of other interwoven algorithms, and a tiny dab finds the other side of a trade on Sungard’s Assent linkage platform that’s shuttling back from a rebate trade at Lavaflow. They meet, kiss, and print to the tape.

Multiply that by millions. That’s trading today. It’s a vast archipelago of mostly meaningless interactions.

In November, our clients averaged 2.1 “rational” prices. In other words, just over twice in the entire month for a given company did mathematics reveal behavior reflective of thoughtful stock-picking. The other eighteen days, price was set by other behaviors.

In December, the number of rational prices dropped 40% to 1.3 on average. Nearly 20% of clients had no new rational price at all, and 75% had none or one.

Disenchanting? No, it’s logical. Rational thought isn’t boomeranging about every few seconds. But most behaviors are programmed to respond rather than viscerally drawn.

Back at the exchanges, everything is defined and controlled by rules. While the same rules apply to dark pools including trading at the best bid or offer, at the exchanges you’re banging and jostling with everyone. You can’t fall in love with a stock here. You can get in line and try to keep up.

That’s why money loves darkness. It’s quiet in the shadows. For the players looking to score, there’s arbitrage between light and dark markets.

Bottom line, dark pools aren’t hurting your share price, structure is. Worst for issuers, the data from this loopy structure are fragmented into a million little pieces.

The answer isn’t to force behavior back to the place it’s fleeing, but to change what’s causing it to flee in the first place. Price should be set by who values something most. Not simply by being the other side of a trade, and fastest to get there.

For any who say “but we need the volume,” I refer you to our rational-price statistics and the Flash Crash: Value and volume are not interdependent.

We can change this structure. If a thousand public companies banded together and demanded that the SEC change the structure, change would occur. If not, then we have much bigger problems than machined shares.

Getting back to trading, how come some investors rail at churn trading, while others love machine intermediation? Somebody must be wrong, right?

Take Templeton Global Advisors, which runs about $100 billion. The president there, Cindy Sweeting, was a fellow panelist. They favor the low-touch, low-cost structure in markets today. With fast machines taking the other side of institutional trades, funds like Templeton can re-allocate portfolios fluidly across asset classes for 60% of the commissions they used to pay, and with abundant liquidity.

What’s more, machines create value opportunities, the Templeton folks believe. The propensity of money to run in algorithmic packs today, what’s called Macro Focus investing because it’s built around big trends and large scale risk-management, means sometimes this group or that sector are left behind. Templeton can swiftly allocate resources, feed out orders through card-shuffling automated trading systems, and blend a fresh investment hand in a new suite into the deck.

Sounds great. How come everybody doesn’t agree? Mason Hawkins at Southeastern Management somewhat famously opined to the SEC that “current market structure is flawed because unfair structural advantages permit short-term professional traders to insert themselves between long-term buyers and sellers. This intermediation conservatively results in $20 billion per year in execution costs and untold billions in opportunity costs for investors.”

One says costs are lower. One says costs are higher. Our point, and we do have one, is to give IR professionals answers. So, when somebody dashes breathlessly up on the street and bleats, “High Frequency Trading is bad!” And you reply, “that’s correct,” and then you turn, and Cindy Sweeting, a very smart and informed investor and a really nice person to boot says “we love it,” well, how to avoid appearing the fool?

The answer lies in the difference between liquidity and capital formation. We have reached an odd place in the capital markets where the interests of growing businesses and the objectives of institutional investors are at odds. Intel went public in 1971 at $23.50, and raised $6.8 million. Its market cap is $120 billion today. That’s capital formation. But in 2005, its market cap was $150 billion.

This is part of the “untold billions” Mason Hawkins meant. We have traded capital formation for the efficient movement of liquidity, and the two are not equal. For many modern global institutions, finding gaps and divergences that span months and weeks, combined with cheap trades and bountiful liquidity, is sufficient.

It can and will produce returns for nimble investors. If it didn’t, we would not have seen fundamental investment fall from 50% of daily volume a half-decade ago to below 10% now, while speculation, program trading have exploded. In some mega caps now, forms of fast-moving liquidity ranging from Templeton’s comings and goings to mathematical arbitrage account 95% of volume.

But it’s not truly investment, but more like the nexus of dislocation and intermediation. Market caps for many fine companies are stuck in neutral (there are always outliers). Money hasn’t forsaken equities; it’s morphed from buying low and selling high on fundamentals, to buying low and selling high on divergence.

And that’s the difference. High-frequency trading is not bad. It’s superbly efficient for moving securities from point to divergent point. But intermediation replaces capital formation. How many IPOs have you seen raising $7 million now? It’s not done, and so companies don’t grow anymore from tiny to giant, which is not only the heart of job-creation, but the root of investment, and wealth.

So when you’re asked why some like it fast and some don’t, you might just say, “The card shuffler revolutionized card shuffling, just like fast trading did for liquidity. So how come they don’t use automatic card shufflers in the World Series of Poker?”

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.

We’d warned that markets showed excessive arbitrage. Arbs capture net spreads between opposing trades and care little about price appreciation. When it’s high in the broad markets (and in specific issues, too), it often points to impending switches in the direction of money, say from one mix of assets to another. Why? Traders apparently detect algorithmic activity and move to profit from it.

We’d seen the same thing in June and thought it might occur again. It didn’t, and the market removed all doubt that we were the fools we appeared to be.

Or so it seems. Are investors responsible for this nice recent run back to positive turf on the major market measures? We can only share general observations from data. The data are what they are. We observed two developments on 7/22. First, Nomura traded more than half our client base that day, a rarity. Nomura had become a primary dealer to the Spanish Treasury a few days earlier, and it’s also a primary dealer for the US Treasury. It owns the trading platform Instinet and Lehman’s Asian and European operations.

How do those facts bear on equity trading when treasuries are a credit market? We can only speculate. But we believe banks can effect carry trades – borrowing and paying interest to earn higher interest on something else.

At the same time Nomura rippled through equity markets, we saw a surge in conventional program trading. Our measures differ from what the exchanges use. Different kinds mean different things. In this case, it was the biggest firms helping global institutions manage transitions from one asset class to another. While market volumes have been relatively light, this increase in market share by big program traders attracted a surge in mathematical trading, which identifies disparities in market structure and capitalizes on them.

Together these could represent a bait-and-switch, not fundamental investment. Banks with trading technologies and commitments to governments to help them fund operations could get money from overnight treasury or central-bank facilities at low cost and use it to trade in equity markets and attract demand. Profits from these operations provide funds for use in required bidding at government primary-dealer auctions. It also gives the bond market a head feint by pulling demand to equities to improve bond-market rates and prices.

We’re not saying this happened. But trading data show that confusion reigns in equity trading markets. That’s not a mark of rational investment. Money may respond sporadically to earnings, and we do certainly see that. But the broad behavior is a mix of discordant sentiments and reactions. We see that, too. Somebody buys in a dark pool, and programs react to it, and algorithms follow, and speculative traders and all the auto-quote systems (translation: “high frequency trading”) tag along, and none of it knows the worth or driver.

Following rules of deductive reasoning, we conclude that if it’s not rational, it’s something else. What else would it be? Well, what dominates the global financial agenda now? Government debt.

So be ye not lulled into a false sense of security, IR pros. Trouble lurks below the rapids. But for now, we’re rafting on big programs, which seem, right or wrong, to know more than you and me.