Tagged: HFT

Mercenary Prices

Florida reminded us of high-speed traders.  I’ll explain.

An energized audience and the best attendance since 2012 marked NIRI National, the investor-relations annual confab held last week, this year in Orlando.

We spent the whole conference in the spacious and biggest-ever ModernIR booth right at the gateway and in late-night revelry with friends, clients and colleagues, and I don’t think we slept more than five hours any night.  Good thing it didn’t last longer or we might have expired.

I can’t speak to content because we had no exposure. But asking people coming through the exhibit hall what moved them, we heard about IEX CEO Brad Katsuyama’s general session on the state of markets (we said hi to Brad, who was arriving in from New York about 1am as we were wrapping for the night and heading to bed).

“He said the exchanges are paying $2.7 billion to traders.”

That what folks were reporting to us.

You remember how this works, longtime readers?  The big listing duopoly doled out $500 million in incentives to traders in the most recent quarter.  That is, exchanges paid others to trade on their platforms (the rest came from BATS Global, now part of CBOE).

Both exchanges combined earned about $180 million in fees from companies to list shares. Data and services generated a combined $750 million for the two.

There’s a relationship among all three items – incentives, listing fees, data revenues.  Companies pay to list shares at an exchange. The exchange in turn pays traders to set prices for those shares. By paying traders for prices, exchanges generate price-setting data that brokers and market operators must buy to comply with rules that require they give customers best prices.

I’m not ripping on exchanges. They’re forced by rules to share customers and prices with competitors. The market is an interlinked data network. No one owns the customer, be it a trader, investor or public company. Exchanges found ways to make money out there.

But if exchanges are paying for prices, how often have you supposed incorrectly that stocks are up or down because investors are buying or selling?

At art auctions you have to prove you’ve got the wherewithal to buy the painting before you can make a bid. Nobody wants the auction house paying a bunch of anonymous shill bidders to run prices up and inflate commissions.

And you public companies, if the majority of your volume trades somewhere else because the law says exchanges have to share prices and customers, how come you don’t have to pay fees to any other exchange?  Listing fees have increased since exchanges hosted 100% of your trading.  Shouldn’t they decrease?

Investors and companies alike should know how much volume is shill bidding and what part is real (some of it is about you, much is quant).  We track that every day, by the way.

The shill bidders aren’t just noise, even if they’re paid to set prices. They hate risk, these machine traders.  They don’t like to lose money so they analyze data with fine machine-toothed combs.  They look for changes in the way money responds to their fake bids and offers meant not to own things but to get fish to take a swipe at a flicked financial fly.

Take tech stocks.  We warned beginning June 5 of waning passive investment particularly in tech. The thing that precedes falling prices is slipping demand and nobody knows it faster than Fast Traders.  Quick as spinning zeroes and ones they shift from long to short and a whole sector gives up 5%, as tech did.

Our theme at NIRI National this year was your plan for a market dominated by passive investment.  Sometime soon, IR has got to stop thinking everything is rational if billions of dollars are paid simply to create valuable data.

We’ve got to start telling CEOs and CFOs and boards.  What to do about it? First you have to understand what’s going on. And the buzz on the floor at NIRI was that traders are getting paid to set prices. Can mercenary prices be trusted?

Race Condition

You might think today’s title is about physical fitness.

No, ModernIR is an equity data analytics firm, not a personal trainer. I first heard the term “race conditions” used to describe stock-trading at TABB Forum, the traders’ community, in comments around an October 2012 article there by HFT expert Haim Bodek on why high-frequency traders have an advantage.

Reader Dave Cummings said, responding to it, “When Reg NMS was debated, several people very knowledgeable about market structure (including myself) argued against locked, crossed, and trade-through rules because of the side-effects caused by race conditions between fragmented markets.”

Emphasis mine.  You say who is Dave Cummings and what is this jargon that has me wanting to bludgeon my noggin on a wall?

I hope Mr. Cummings won’t mind my resurrecting his point. He started both BATS Global Inc., the stock exchange the CBOE is buying that by market-share the last five trading days nosed out the NYSE with 20.7% of US volume versus the venerated Buttonwood bourse’s 19.9% (the Nasdaq had 17.7%, IEX 2.2%, and nearly 40% was in broker pools), and speedy proprietary (no customers, trades its own capital) firm TradeBot.

He knows market structure.

We come to the jargon. Don’t tune out, investor-relations people and investors, because you need to understand the market to function well in it. Right?

Most people don’t know what Dave knows (that could go on a T-shirt). Mr. Cummings was explaining that trading rules prohibit the bid to buy and the offer to sell from being the same. A locked market. Crossed markets are out too, by law. You can’t make a bid to buy that is higher than the offer to sell.

And this “trade through” thing means brokers can’t continue buying stock at $20 one place if it’s now available for $19.99 another place.

I’ve said before that there’s no such thing as a “fragmented market.” A market by definition is aggregation. The stock market today is a series of interconnected conclaves all forced to do the same thing with the same products and prices. You understand? You can buy Nasdaq stocks at the NYSE and vice versa and only at the best price everywhere.

ModernIR builds software and runs lots of data-warehousing functions so we know race conditions. It’s when something doesn’t happen in proper sequence, you might say.

For instance, a data warehouse must be updated on schedule before an algorithm processes a routine. Some hiccup in the network slows the population of the data warehouse, so the algorithm fails because data haven’t shown up. Race condition.

The stock market is similarly a series of dependent processes, some of which will inescapably fail. Why would we create a stock market with a known propensity for process errors? Exactly. But let’s focus on what this means to investors and public companies.

It means the market is barred from behaving rationally in some circumstances. What if I want to pay more for something? Or say I don’t mind getting an inferior price for the convenience of staying in one place.

Plus, can we trust prices? What if yesterday’s big gains were a product of a race condition? I’m not saying they were. But we measure discrete market behaviors setting prices. Counterparties for derivatives were heavy buyers Monday when the stock market swooned sharply and then recovered most of its losses by the close.

These big banks or insurers bought because investors had portfolio insurance to guard against losses. That’s not investment behavior.

What then if equity trades tied to derivatives didn’t populate someplace and the market zoomed yesterday on a process error? Again, I’m not saying it did.  But the things Mr. Cummings warned would create errors in markets are cornerstones of the regulations behind the National Market System.

And why can’t a bid and offer be the same? Forcing them to be different means an intermediary is part of every trade. That’s why 40% of trading is in dark pools – to escape shill bids by trading intermediaries.

Why would Congress – which created the National Market System – mandate a middle man for stocks, when to get a good deal you cut the middle man out? Think about that with health care (or with government itself, which is the ultimate middle man).

But I digress.

We have a stock market the requires an intermediary, prohibits buying and selling at the same price (unless at the midpoint between them, which is the average, which is why index-investing is crushing stock-picking), and stops investors from paying the price they want and forces them instead to take a different price.

In Denver real estate, the bid to buy is often higher than the offer to sell because there aren’t enough houses. Don’t you want people paying more for your shares rather than less? So why do rules require the opposite?

I want us all thinking about whether the stock market serves our best interests in current form where passive investment is taking over everything.

I’ll be talking about that to the NIRI Capital Area chapter Apr 4, so come say hi. And we’ll be at NIRI Boston tonight self-congratulating with the rest of the sponsoring vendors in Sponsorpalooza.  You all in Minneapolis, good seeing you last week!

I just hope there are no race conditions in our travel plans from Denver today.

Bang the Close

I find myself in an uncomfortable position.  I’m siding with a high-frequency trader.

There’s a key lesson here for investor-relations professionals about how prices are set, and it dovetails with why the bulk of volume concentrates around the open and close.

The title of this piece would be a great name for a rock band but it refers to submitting securities trades during the last 15 minutes of trading to affect how average prices are calculated. That’s “banging the close,” it’s said.

Venerable Chicago high-speed firm DRW, a proprietary trader focused on derivatives markets, has been accused by commodities regulators of manipulating prices on a key interest-rate swap. The alleged malfeasance occurred in 2011.

Normally firms settle with regulators when charged with rule-breaking. Founder Donald R. Wilson, a prominent figure in Chicago, insists DRW did nothing wrong and is battling the US Commodities Futures Trading Commission in court.

The CFTC says DRW submitted a thousand orders over seven months that didn’t conform with other prices during the vital last 15 minutes when “settlement prices,” or average prices for contracts and broker margin-requirements, are calculated. A broker serving as counterparty might have to furnish more capital if the price moves.

The CFTC is miffed because it believes DRW made money even though none of its bids produced a matched trade.  DRW says it was simply profiting on differences between the futures contract and the same product traded over-the-counter (that is, by brokers). The swaps contracts pay buyers (DRW was always the buyer) a fixed fee and sellers a floating one. Floaters lost, among them the now-defunct MF Global.

Let’s summarize for those who like me need an adult beverage after sorting this matter. The CFTC claims DRW manipulated prices for gains by putting in bids that weren’t like other bids. DRW says it bids what it thinks things are worth, not whether the price conforms to others’ views, and sometimes someone loses. That’s my interpretation.

What’s this got to do with IR and stock-trading? The IR job is predicated on helping investors understand why your shares are worth more than somebody else’s.  Are you manipulating prices then?  Of course not. And sometimes stocks decline.

Secondly, one reason Blackrock and Vanguard routinely beat your active holders for investment returns is because of stupid rules forcing prices to averages at the expense of those looking for outliers. Without outliers in markets, there’s no room for stock-pickers – the lifeblood of the IR profession. The market should reflect all prices, not averages.

It’s partly why volume is big in the morning and at the close.  Those prices are used to calculate averages. Your shares often move up or down early, toward the mean between, and then up or down into the close (see yesterday’s trading).  It could be argued that many algorithms are banging the close, which means banging is no aberration – or that the whole market is a series of continuous manipulations (don’t answer that!).

If DRW is a manipulator, then so was George Soros in the British pound. So are trading algorithms pursuing volume-weighted average prices because they undermine your effort to help your stock diverge from averages.

So is the Federal Reserve. The Fed sets artificial interest rates to manipulate broader ones, which it will likely do again Dec 14 (with $460 billion of reverse-repurchases on its balance sheet, another manipulation scheme, the Fed signals hike intentions). How is that different from DRW bidding at prices it believes reflect appropriate value?

If DRW is a price-manipulator, so was my dad.  On the cattle ranch of my youth, we’d take our animals to market and bid on them to push the price up to a level we thought proper. If the buyers didn’t like it, we bought the cattle back and took them home.

This would apparently have earned CFTC accusations of manipulating cattle prices.

Pardon me for bluntness but let’s knock off the crap, shall we? Rules that force all prices to the mean – which proliferate in equities and everywhere else now – defy supply and demand, foster mediocrity and promote sudden and irrational reversions to a mean.

I don’t prefer proprietary traders committing no long-term capital to budding businesses.  But.  If we want to reduce risk in the capital market, here’s an idea:  Let any buyer or seller price as he or she wishes. Suppose brokers could do it too. Maybe that would bring aftermarket support back to IPOs, creating new IR jobs again.

That’s my suggestion for the incoming SEC chair.

Light Speed

Alert reader Raj Mehan at Steelcase forwarded a piece from the Wall Street Journal about traders now aiming with machines to execute stock-market transactions near light-speed.

Why the rush?  Companies take flak for “short-termism” that’s a quarter long and yet regulators and traders and academics extol the virtues of fast trading, claiming it makes markets liquid and efficient.

Just this week I was speaking with a CFO for a public company who yawned at the idea he should care about what priced his stock. “It’s interesting but what difference does it make?”  I’m paraphrasing a longer exchange. It’s a vital point of contention, right?

We’ll come to that in a moment. Watching the Olympics this week – exhilarating as ever – the race for speed in the water is stupefying.  Seeing Katie Ledecky crush the field by five seconds for a gold metal gives you goose bumps no matter your country. And the objective of swimming-speed is winning.

It is for traders too. In the WSJ article by Vera Sprothen, folks from high-speed trader DRW Holdings LLC (stands for Donald R Wilson) said competition in financial markets is accelerating the race. A nanosecond is a billionth of a second. Routers can send and receive stock-exchange data in 85 nanoseconds, which is how much time elapses when a bullet fired from a gun travels a half-inch.

Imagine. You fire at a shooting-range target and before the bullet gets there somebody trades your stock several hundred times.

If I’m making a big-ticket purchase the last thing I want is – snap! – to do it faster. Many of you are investor-relations professionals. Do some investors study your business for a year or two before deciding to buy your shares? When I was an IRO, that was common.

Weighty decisions are not made for light speed.  Therefore, traders are not making weighty decisions. Committing capital over time is a risky gambit. Capital deployed the amount of time needed for a bullet to travel a few feet isn’t so fraught.

It’s also not investment. Understand: The stock market in the USA and ever more around the world too is one in which the first trade to arrive prices the stock for everyone. Many stock-trades are paired with other things such as options or currencies or commodities.  Price one superfast, and race over faster than a speeding bullet to something else, and you can make money by taking advantage of price-differences. That is by definition arbitrage.

The efficiency of markets is best assessed by determining how much arbitrage occurs. There’s a lot of arbitrage in booking a hotel room on line. There’s no arbitrage in buying a cup of coffee at Starbucks (unless somebody at the Univ of Chicago wants to study that question and prove me wrong).

In the stock market, almost half of all volume is arbitrage. It may be the most colossally inefficient capital market ever created by human beings. Back up 20 years and it wasn’t. Just 15% of trading could be attributed to arbitrage, and 85% to investment.  Speed and price-differences now consume it.

Which brings us back to our apathetic CFO. If you don’t care about the market for the backbone of your balance sheet enough to understand it, you should be a private company where there’s less arbitrage.

For IR pros in the 21st century, it’s a huge opportunity. Not only is there confidence in knowing how the market works, but somewhere today there’s an IRO who will, having learned, help change the market tomorrow.

Problems are solved after we first understand them.  Most prices for stocks should not be set at the speed of light. Yet that’s happening.

Trivago and Traders

I was high-frequency traded by a travel site.

Had that happen? You web-search a place and pricing and there’s no availability for the date you want so you check elsewhere and suddenly there’s vacancy – but now it costs more so you better act fast!  It’s like the stock market’s recent performance.

It’s not the first time I’ve been played by algorithms but it happened trying to book rooms in Crested Butte this week as we toured my visiting mother around the continental divide. Having spoken with hotel staff and knowing there wasn’t peak demand, I waited. At the hotel we got the best bargain of all. If you want a good deal, cut out the middle man.

And when you’re shopping online for a hotel deal, realize it’s a cabal. Expedia owns hotwire, hotels.com, Orbitz, Travelocity, and trivago to name the biggest brands. Priceline owns booking.com and Kayak among others.

When you start searching for a travel deal, the machines know almost instantly. It’s an integrated network where much of the pricing and supply are controlled by a handful of players.  Start looking for rooms, and rates rise not due to supply outstripping demand but because middle men change the prices.

Let’s think about the stock market. Expedia and Priceline have an advantage through being many places simultaneously. They’re in effect trading all the stocks – all the places you go unless you cut them out and go straight to the hotel.

Who in the market trades everything?  No, not Goldman Sachs. None of the big brokers trade anywhere near all the securities in the market. That’s not the business they’re in.

But high-frequency traders do. All our clients down to the very smallest ones under $50m in market cap are traded daily by high-frequency firms.

High-speed firms trade thousands of securities everywhere simultaneously, generally exchange-traded products where setting the prices everyone sees is the aim: stocks, commodities, derivatives and currencies.

But these firms don’t want to own anything. Wrap your head around this idea, because it’s a lot like getting travel-deal HFT’d.  The travel sites keep changing prices in order to prompt a reaction.  You’ll get teased: “Four left at this price!”

It’s the same in the stock market.  High-speed traders with vastly powerful networked machines connected to all the trading venues know every time there are ripples of supply or demand in any security.  Instantly, the price for that stock changes. If you’ve read the book Flash Boys, you get what I’m saying.

But let’s go one step further.  In the last 17 weeks through July 29 this year, there was not a single one in which Active Investors – buy-and-hold stock pickers – led as price-setters (through both the Brexit Swoon and Brexit Bounce).  In nine of those weeks Fast Traders did.  That’s over half the time (otherwise it’s been Asset Allocation – indexes and ETFs – or Risk Management, counterparties to derivatives like options and futures).

This is why the market is defying fundamentals. It’s exactly how pricing and supply defied fundamentals when we were trying to book a hotel in Crested Butte. Elevation Hotel & Spa was not remotely out. But the fast-trading hotel algorithms sure wanted everyone to think so.

The same thing happens repeatedly through each trading day. Stocks soar, and then falter and fall…and someone tries to book some shares…and all of the sudden prices race back up and the Dow Jones rises 80 points.  Better act fast!  These prices won’t last!

The truth is that the equivalent of booking.com is making it impossible for anyone to know the real supply and demand of stocks.  Since investors can only guess the same as we do hunting for hotel deals, they scratch their heads and try to buy.

You might say, “But we get good hotel deals.” As in the stock market, electronic trading ended laziness at big brokers and exchanges. But now the middle men have taken over. They’re now worse than what we had before. They’re fostering dangerous illusions.

Illusions cause markets to become mispriced because it’s impossible to separate the middle men from the actual supply of product.  How to solve it? First, understand how much of your daily volume is being driven by middle men. Then you can begin to measure what’s real.

Ultimately, investors and public companies should confederate to create a market that bars high-speed traders. Until then don’t be fooled by either HFT or booking.com.

Correlating Volatility

“Measure the performance of equity securities in the top 85% by market capitalization of equity securities listed on stock exchanges in the United States.”

I made it a sentence here but I clipped that phrase from a Blackrock iShares “minimum volatility” Smart Beta Exchange Traded Fund (ETF) prospectus and Googled it, and got back pages of references.  Apparently many indexes and ETFs meant to diversify and differentiate investments are built on the “top 85% by market capitalization.”

That by the way is about 700 companies. There are now over 700 ETFs in the US stock market and about 3,700 total public companies when you strip out funds and multiple classes of stock.  That’s a 1-to-5 ratio.  If many ETFs track indexes comprised of just 20% of the stocks, would that not produce high correlation?

Answer:  Yes.

I ran correlation for five ETFs from Blackrock, First Trust, Schwab, Vanguard and Invesco (USMV, FVD, SCHD, VIG, SPLV) over the past three months and it was about 90%.  Now, all five seek similar objectives so correlation isn’t surprising. But in truth they’re brewing a mixture of the same stocks.

We had the chance to participate in a wine-blending last month in Napa. The group was tasting mixtures of a core set of grapes.  What if we make it 94% Zinfandel, 3% Petit Syrah and 3% Malbec?  How about 7% Malbec, 3% Petit Syrah, 90% Zinfandel?

The same thing is happening with ETFs. They’re blending the same grapes – stocks.  What if we weight a little more than the index in WMT and a little less in AMZN?

It’s still the same stocks. And it’s earnings season.  Think about the impact of high correlation when in nearly all cases save an outlier handful ETFs track underlying indexes with defined composition.

Say you report results and your stock plunges (we’ll come to why in a moment). Even minute weighting in a falling stock can skew the ETF away from the benchmark, so the authorized participants for the ETF sell and short your shares, raising cash to true up net asset values and ridding the ETF of the offending drag.

At some future point now that your shares are sharply discounted to the group and the market, arbitragers will find you and the authorized participants (brokers creating and redeeming ETF shares to ensure that it tracks its benchmark as money flows into and out of the investment vehicle) who shorted will cover, and suddenly you’re the star again.

Neither up nor down did the behavior of your stock reflect fundamental value or rational thought. It’s high correlation, which rather ironically fosters mounting volatility. We’re seeing a notable increase in instances of large moves with earnings.  And your shares don’t drop 15% because active investors saw your numbers and decided, “Let’s destroy our portfolio returns by buying high and selling low.”

In the last week through Monday, Asset Allocators (indexes and ETFs) and Fast Traders (arbitragers speculating on intraday price-changes) were top price-setters.  Both are quantitative, or machine-driven, behaviors. One is deploying money following a model and the other is betting with models on divergences that will develop during that process.

Both create mass volatility around surprises in earnings reports. Fast Traders are the athletes of the stock market racing to the front of the line to buy and sell. Asset Allocators are lumbering, oblivious to fundamental factors and instead following a recipe.

You report.  Active investors stop their bits and pieces of buying or selling to assess your fundamentals. Sensing slight change, Fast Traders vanish from order books across the interconnected web comprising today’s stock market.  Asset Allocators tracking benchmarks stop buying your shares because you’ve now diverged from the broad measure.

This combination creates a vacuum.  Imagine selling your house and there was a bidding war for it and suddenly all the bidders disappeared. You’d have to cut your price. What changed?  The number of potential buyers, not the value of the house.

This is the problem with how a combination of Fast Traders and Asset Allocators dominate the market now.  Fast Traders set most of the prices but want to own nothing so the demand they create is unreliable and unstable.  Asset Allocators are trying to track benchmarks – that depend on Fast Traders for prices. Throw a wrench into those delicate gears with, say, a surprise in your quarterly earnings, and something will go awry.

Speaking of which, our Sentiment Index just turned Negative for the first time since February and yet the market soared yesterday.  From Feb 8-11, futures contracts behind some of the most actively traded ETFs in the market, concentrated in energy, rolled. The dollar had just weakened. Stocks roared.

The same futures contracts just rolled and the ETFs rebalanced (May 6-11). Counterparties covered. The dollar is rising. We may be at a tipping point again for stocks. Derivatives now price the underlying assets.

Split Millisecond

You’ve heard the phrase split-second decision?

For high-speed traders that would be akin to the plod of a government bureaucracy or the slow creep of a geological era.

Half a second (splitting it) is 500 milliseconds. One millisecond equals a thousand microseconds. One microsecond is a thousand nanoseconds, and a microsecond is to one full second in ratio about what one second is to 11.6 days.  Fortunately we’re not yet into zeptoseconds and yoctoseconds.

IEX, the upstart protagonist in Michael Lewis’s wildly popular Flash Boys, has now filed to become a listing exchange with the NYSE and the Nasdaq.  Smart folks, they looked at the screaming pace of the stock market and rather than targeting the yoctosecond (one trillionth of a trillionth of a second), said: “What if we slowed this chaos down?”

It was a winning idea, and IEX soared up the ranks of trading platforms.  Oh, but ye hath seen no fire and brimstone like that now breathed from high-speed traders and legacy exchanges.  You’d have thought IEX was proposing immolating them all on a pyre.

Which brings us back to one millisecond.  IEX devised a speed bump of 350 microseconds – less than half a millisecond – to slow access to its market so fast traders could not race ahead and execute or cancel trades at other markets where prices may be microseconds different than IEX’s.

Speed matters because Regulation National Market System (Reg NMS) which ten years ago fostered the current stock market of interconnected data nodes and blazing speed said all orders to buy or sell that are seeking to fill must be automated and immediate.

Of course, nobody defined “immediate.”  Using only common sense you can understand what unfolded.  If the “stock market” isn’t a single destination but many bound together by the laws of physics and technology, some humans are going to go, “What if we used computers to buy low over there and sell high over here really fast?”

Now add this fact to the mix. Reg NMS divided common data revenues according to how often an exchange has the best available price. And rules require brokers to buy other data from the exchanges to ensure that they know the best prices.  Plus, Reg NMS capped what exchanges could charge for trades at $0.30 per hundred shares.

Left to chance, how could an exchange know if it would earn data revenues or develop valuable data to sell? Well, the law didn’t prohibit incentives.

Voila! Exchanges came up with the same idea retailers have been using for no doubt thousands of years going back to cuneiform:  Offer a coupon.  Exchanges started paying traders to set the best price in the market.  The more often you could do that, the more the exchange would pay.

Now those “rebates” are routinely more than the capped fee of $0.30 per hundred shares, and now arguably most prices are set by proprietary (having no customers) traders whose technology platforms trade thousands of securities over multiple asset classes simultaneously in fractions of seconds to profit from tiny arbitrage spreads and rebates.  Symbiosis between high-speed firms and exchanges helps the latter generate billions of dollars of revenue from data and technology services around this model.

Enter the SEC in March this year.  The Commission said in effect, “We think one millisecond is immediate.” Implication: IEX’s architecture is fine.

But it’s more than that. Legacy exchanges and high-speed traders reacted with horror and outrage. Billions of dollars have been spent devising systems that maximize speed, prices and data revenues.  The market now depends for best prices on a system of incentives and arbitrage trades clustered around the capacity to do things in LESS than a millisecond. The evidence overwhelms that structure favors speed.

Is a millisecond vital to capital formation? I’ve been running this business for eleven years and it’s taken enormous effort and dedication to build value. I would never let arbitragers with no ownership interest price in fractions of seconds these accumulated years of time and investment.

So why are you, public companies? Food for thought. Now if a millisecond is immediate, we may slam into the reality of our dependence on arbitrage.  But really?  A millisecond?

False Passive

Karen and I are in Boston seeing friends at the NIRI chapter (we sponsor) and our trip today like last week coincides with snow in Denver. Next winter if the slopes turn bare, we’ll schedule a couple flights to bring in the blizzards.

Last week trooping through Chicago where you had to lean to stay upright in the wind, an investor-relations officer told me, “Passive money can’t be setting prices because it’s, well, passive. It can only follow active money.”

Sometimes I’m so close to the trees of market structure that I forget about the forest everyone else is seeing. Statisticians warn about false positives, false correlations, false precision. The descriptor “passive” for investment behavior following models inaccurately portrays what the money is doing. We call it “Asset Allocation” behavior.

To understand this money let’s first review how the stock market works:

It’s a data network comprised of visible nodes called exchanges and invisible ones called formally alternative trading systems and colloquially “dark pools,” stores for stocks where you must be a member to buy. Exchanges are required to serve all customers, who must either be a broker or use one.

All markets share customers and prices. You cannot continue to serve a customer in one market including a dark pool at a price worse than what’s available elsewhere. Thus, trades must match between the network-wide best price called the NBBO – national best bid/offer (best price to buy or sell).

Orders wanting to price the market must be automated so they can rapidly move from one node to the next, or the data network can’t function.

-Because of this structure, exchanges offer trading incentives called “rebates” to more frequently have the best price on the network. They pay high-speed traders about $0.29/100 shares to bring orders to their markets and set prices.

-The NYSE, the Nasdaq and BATS Global Markets operate multiple exchanges, rather than one that would aggregate buying and selling, so as to increase the amount of time each group has the best price, which means fast traders create many prices. By our measures, fast traders are eight times as likely to set prices, but with just 100 shares.

Exchanges want to set prices because any broker or market center handling customer orders must give customers the best prices so all are required to buy expensive pricing data, which is how exchanges make money.

Now you understand the stock market. Onto this network come seas of money from Blackrock and Vanguard and a raft of exchange-traded funds. For two decades investors have been choosing passive investment in accelerating fashion. It’s how Blackrock and Vanguard are the world’s biggest investors ($8 trillion of assets) and ETFs host $3 trillion while turning holdings at 2,500% (making buy-and-hold a parody).

Passive money is governed by the model it tracks, the prospectus describing the fund, and inflows and outflows. Tack on the explosive popularity in recent years of “smart beta” money tracking mathematical measures to capitalize on trends or market inefficiencies and you have a recipe for perpetual motion.

To that end, indexed money by rule must peg its benchmark – the measure metering its performance. Indexes use options and futures to mirror the benchmark so counterparties for options and futures are in and out of the market. That sets prices.

The majority of trading in ETFs is a form of arbitrage. ETFs don’t buy or sell stocks. ETF sponsors privately transact with authorized participants in large blocks. In the market, people are trading ETF shares that simply represent assets held by sponsors. Market-makers are shorting or going long components to capture inefficiencies, and fast traders are repricing components, indexes, options and futures for spreads.

All of this is setting your price. If money flows into SPY, the world’s most actively traded stock with $25 billion of volume daily, arbitragers, market-makers and authorized participants must respond. This trade splashing through your peer group may move members disparately at times because of liquidity, options, futures, shorting.

A paradoxical cycle forms. Indices fluctuate because of arbitrage in ETFs predicated on them, which prompts indexed money to adjust, which must happen because rules for indexes demand it.

The sheer size of this money has pervasive market impact, often blotting out effort by active investors to buy or sell growth and value opportunities (uniform rules and uniform trade-executions overwhelm outlier orders, key to why stock pickers rarely beat indexes).

There’s little that’s passive about passive investment. Call it Asset Allocation. But it lacks emotion, reason and common sense. That’s why markets are unresponsive to terror attacks or flagging economies but wedded to monetary policy. It’s about the model.

Pricing Models

The 1,200 NYSE stocks supported by Barclays were the last redoubt of the old market-making guard.

Yesterday, New York City-based Global Trading Systems (GTS) said it will buy the Designated Market Maker (DMM) unit from Barclays at the NYSE. GTS joins KCG Holdings, IMC Financial Markets and Virtu Financial Inc. (which may have to call itself VFI to keep acronym pace) as the quad core making markets and setting prices for NYSE stocks trading at the home exchange.

Barclays likely exited the DMM business because it couldn’t compete. For one, banks are under regulatory pressure to quit trading for their own accounts. Second, rules on the floor prohibit DMMs from using customer orders to price the market. Barclays has customers. The rest were free from the task of sorting those from proprietary trades.

GTS is a high-frequency trading (HFT) firm like its floor brethren. KCG alone has an agency brokerage business with customers, but it’s the progeny of a marriage between Knight Securities and seminal HFT firm GETCO (the Global Electronic Trading Co., the first curiously anonymous massive volume-maker to grab our attention ten years ago).

DMMs pay roughly $0.03 per hundred shares to buy stock, and earn about $0.30 a hundred to sell it. It works poorly for a conventional broker-dealer like Barclays matching buyers and sellers, or crossing the transaction. Proprietary traders find it a money-minting model.

Lest you Nasdaq companies feel special, you’re no different. Prices at the Nasdaq are set by incentives and dominated by HFT too.  Real buyers and sellers rarely price shares – a fact we establish with Rational Price, our fair-value measure, which changes infrequently.

Virtu and IMC Financial Markets, like GTS, say they’re automated market-makers, an innocuous term implying a robotic form of erstwhile human effort. But GTS isn’t matching buyers and sellers.

In its own words: “Today HFT makes up approximately 51% of trades in U.S. equities, and technology-driven innovations continue to transform the investment and financial sectors in profoundly positive ways. At GTS, our advanced algorithms and ultra-fast computers execute thousands of transactions in fractions of a second.  This automation provides liquidity in all the markets we trade and enables our trading venues to provide lower transaction costs.  GTS is proud to be one of the industry innovators contributing to the evolution of the modern market.”

You see? Not a word about match-making. GTS hopes to convince us that its brilliant technology is profoundly positive when in fact it’s exploiting our ignorance.

Various markets for thousands of years have experienced arbitrage – capturing spreads that develop because of inefficiencies in pricing, supply, demand and information. Take theater tickets. Scalpers arbitrage supply and information asymmetries. They are intermediating intermediation. What if we were all forced to buy tickets from scalpers – somebody wanting to profit from owning nothing? Scalpers should be a small part of a market, not 51%.

There are four primary problems with a market priced by HFT:

Risk. If regulators think proprietary trading is risky, why then is 100% of the DMM model proprietary trading?  Why are regulators propagating rules that fashion a market inhospitable to firms taking companies public and supporting them with research and true market-making (carrying inventory, serving customers)?  Following the August 24 trading debacle, JP Morgan changed DMMs from KCG to Barclays because, rightly or wrongly, it lost confidence.

Volatility.  HFT claims to smooth volatility with rapid-fire transactions. That’s muddying the definition. Volatility means “tending to vary often.” Things vary often when they’re broken into fragments and bounced around. That’s intraday volatility, or the spread between high and low daily prices. Tally yours for a month. For AAPL over 20 trading days ended Jan 25, it’s 55.8% – or in dollars, $56.39. That’s the sum of spreads between highs and lows. The Fed shoots for a 2% annual inflation target (wrong but a separate story). AAPL changes more than that each day.

HFT isn’t intermediation but arbitrage. Intermediating by definition is fostering agreement or reconciliation. It involves a vested interest in outcomes. Customers are a tacit requirement. HFT firms have no customers and care not about direction. They create fleeting price-changes for profit.  That’s not market-making.

HFT distorts supply, demand and price. Deduct half your volume because it’s HFT (and over 48% of volume is borrowed so add that to the risk equation). But it set prices and created impressions of supply and demand.  These firms commit little capital, manage no investment portfolios and execute no trades for investors. They’ve devised proprietary pricing models that find short-term inefficiencies (fractions of seconds at once in equities, currencies, commodities and derivatives). They obscure the truth in effect, and in a crisis of magnitude, discovering that most of the prices and half the volume are arbitrage could have devastating consequences for multiple asset classes simultaneously.

Solutions? In Swiftian spirit, there’s the Berkshire-Hathaway Option.  If every US-listed company would reverse-split its shares to $200,000 each, the cost would force arbitragers out. Our serene market would lack arbitrage and intermediation and trade about 1.5 million shares daily. Of course traders, brokers and exchanges, even the regulators (the SEC budget depends wholly now on Section 31 trading fees), would go broke.

Moral of the story? If intermediaries are half our market, it’s a poor one. That should make us mad (why doesn’t it?). It matters not what altruistic oratory streams from the community of high-speed traders. Calling arbitrage market-making will not magically make it so, nor will a better deal materialize from a multitude of middle men.

Mispricing

If the stock market reflects all information currently known, why are buyout deals nearly always done at a premium to market price?

“Because, Quast, deals involve proprietary pricing models that account for synergies.”

Sure. But I want you to think about prices. The Wall Street Journal recently reported that Blackrock cut fees on several exchange-traded funds (ETFs) to three cents per $100 of assets annually.

Low fees appeal. But how are they doing it?  After all, ETFs are notoriously high-turnover vehicles. The Investment Company Institute says conventional institutions sell about 42% of asset annually. Data from ETF Database showed ETF turnover of 2,200% annually, and leveraged ETFs using derivatives to achieve returns turning over a shocking 164 times more than underlying assets. At that rate, a $1 billion ETF could trade $164 billion of shares in a year. Tally your volume over the trailing year and divide by your average market-cap and it’s probably 1-3 times.

It’s an axiom of financial markets that churning assets consumes returns. So how can ETFs be low-cost vehicles? In June 2011, Financial Times of London writer Isabella Kiminska brilliantly observed that ETFs are built around what she termed “manufactured arbitrage.” If ETFs aren’t making money on fees it’s because they make it elsewhere.

In fact shares of ETFs represent something that exists elsewhere. Every day, ETF sponsors like Invesco and Blackrock give their brokerage agents called authorized participants (APs) a creation basket, a list of securities or other assets held by the ETF. The AP assembles this list for the ETF and receives in kind a bunch of paper – a chunk of ETF shares to sell. The AP may substitute cash for the creation basket too.

APs thus always know before everyone else whether demand is rising or falling. An AP could buy underlying securities (or borrow them) and supply them to the ETF, and then sell the ETF shares, and if the ETF is later discounted to the underlying securities, buy the ETF shares and redeem them to the ETF. The ETF industry in fact touts this continual arbitrage opportunity in ETFs as a key efficiency feature.

Actually, it explains why ETFs have low costs. There’s a lot of money in trading paper back and forth while not having to compete with anybody else.  ETFs and APs are a closed market that collectively is always a step ahead.

High-frequency traders (HFT) also claim to offer efficacy through frenzy.  Modern Markets Initiative, the HFT industry lobbying group, says HFT fuels “market efficiency” because automated markets reduce costs, enhance access and increase competition. It defies logic to propose you can reduce costs by doing more of something (politicians often make this claim, which future financial outcomes refute).

“Market efficiency” is a euphemism for arbitrage. We’ve been led to believe that because arbitrage occurs where pricing gaps form, created arbitrage will eliminate gaps. No, what goes away are real prices.

There’s yet a third instance of this pricing contradiction amid the market’s core building blocks. Reg NMS capped the fee for buying shares at $0.30 yet all three big exchanges pay sellers more than that. The NYSE pays its best trading customers about $0.34 per hundred traded shares, the Nasdaq about the same. BATS Group pays top customers in thinly traded stocks $0.45 per hundred shares to sell while charging just $0.25 per hundred to buy.  All three will pay extra to traders active in both stocks and derivatives, the latter called “Tape B” securities denoting the facility for most derivatives trades.

Why are they paying more than they charge? Arbitrage, here between the trades and the value of data. By paying traders to set prices, data become more valuable. All three sell feeds and technology to brokers and traders for sums ranging from $5,000 monthly for a cabinet in a collocation facility to $100,000 monthly for an enterprise data feed.

What drives most of the volume in markets? ETFs are behind disproportionate amounts. HFT gets paid to set prices.  And APs – the big prime brokers like Goldman Sachs and Morgan Stanley – drive half the market volume. A key motivation across the three is profiting on spreads.

These gaps aren’t occurring through information asymmetry or market inefficiencies but are manufactured through the form ETFs take as derivatives and through the fee-structure and function of the National Market System.

No wonder there’s a premium on go-private deals.  They cut out the middle men arbitraging away real prices. And no wonder it’s so difficult to match the market to reality. It’s deliberately and mechanically manufacturing prices. That’s apparent when one understands ETFs, HFT and exchange market-access fees.