Tagged: Trading

Mr. Smith’s Money

The price-to-earnings ratio in the S&P 500 is about 23.  Is it even meaningful?

Some say a zero-interest-rate environment justifies paying more for stocks. That’s compounding the error. If we behaved rationally, we’d see both asset classes as mispriced, both overpriced.

All investors and all public companies want risk assets to be well-valued rather than poorly valued, sure. But Warren Buffett wasn’t the first to say you shouldn’t pay more for something than it’s worth.

What’s happening now is we don’t know what anything is worth.

Which reminds me of Modern Monetary Theory (MMT).  The words “money” and “theory” shouldn’t be used in conjunction, because they imply a troubling uncertainty about the worth of the thing everyone relies on to meter their lives.

That is, we all, in some form or another, trade time, which is finite, for money, which is also finite but less so than time, thanks to central banks, which create more of it than God gave us time.

Every one of us trading time of fixed value for money of floating value is getting hosed, and it’s showing up in the stock and bond markets.

Let me explain.  Current monetary thinking sees money as debits and credits.  If gross domestic product is debited by a pandemic because people lose their jobs and can’t buy stuff, the solution is for the government to credit the economy with an equal and offsetting amount of money, balancing the books again.

This is effectively MMT.  You MMTers, don’t send me long dissertations, please. I’m being obtuse for effect.

The problem in the equation is the omission of time, which is the true denominator of all valuable things (how much times goes into the making of diamonds, for instance? Oil?). Monetarists treat time as immaterial next to money.

If it takes John Smith 35 years to accumulate enough money to retire on, and the Federal Reserve needs the blink of an eye to manufacture the same quantity and distribute it via a lending facility, John Smith has been robbed.

How? Mr. Smith’s money will now be insufficient (increasing his dependency on government) because the increase in the availability of money will reduce the return Mr. Smith can generate from lending it to someone else to produce an income stream.

Mispriced bonds.  They don’t yield enough and they cost too much.

So by extension the cost of everything else must go up.  Why? Because every good, every service, will need just a little more capital to produce them, as its value has been diminished.  To offset that effect, prices must rise.

And prices can’t rise enough to offset this effect, so you pay 23 times for the earnings of the companies behind the goods and services when before you would only pay 15 times.

And this is how it becomes impossible to know the worth of anything.

And then it gets complicated.  Read a balance sheet of the Federal Reserve from 2007.  The Fed makes up its own accounting rules that don’t jive with the Generally Accepted Accounting Principles that all public companies must follow.

But it was pretty straightforward.  And there were about $10 billion of excess bank reserves on a monthly average, give or take.

Try reading that balance sheet today with all its footnotes.  It’s a game of financial Twister, and the reason isn’t time or money, but theory.  A theory of money that omits its time-value leads people to write things like:

The Board’s H.4.1 statistical release, “Factors Affecting Reserve Balances of Depository Institutions and Condition Statement of Federal Reserve Banks,” has been modified to include information related to TALF II LLC. The TALF II LLC was introduced on the H.4.1 cover note on June 18, 2020 https://www.federalreserve.gov/releases/h41/current/.

The theory is that if you just keep footnoting the balance sheet to describe increasingly tangled assets and offsetting liabilities, so long as it zeroes out at the end, everything will be fine.

Except it leaves out Mr. Smith and his limited time on the earth.

Oh, and excess bank reserves are now nearly $3 trillion instead of $10 billion, proof money isn’t worth what it was.

This then breaks down fundamental constructs of valuation.  And it’s why we offer Market Structure Analytics.  While fundamentals can no longer in any consistently reliable way be used to discern what the stock market is doing, Market Structure Analytics lays reasons bare.

For instance, Market Structure Sentiment™ ticked up for TSLA July 2. Good time to buy. It’s got nothing to do with fundamentals.  FB Market Structure Sentiment™ ticked up June 23. Good time to buy. In fact, it’s a 1.0/10.0 right now, but it’s 57% short, so it’s got just limited upside.  Heard all the negative stuff that would tank FB? Fat chance. Market structure rules this Mad Max world.

Public companies, if you want to understand your stock, you have to use tools that take into account today’s madness. Ours do.  Same for you, traders. Sign up for a free 14-day trial at www.marketstructureedge.com and see what drives stocks.

How does it all end? At some point Mr. Smith will lose faith, and the currency will too.  We should stop the madness before then.

Power of Two

We’re coming to the end of two Coronavirus quarters. What happens now?

In a word, July.  As to what July brings, it’s summer in the northern hemisphere, winter down under.

It’s also the end of a remarkable period in stocks. I don’t mean rising or falling, volatility, the invincible-Alexander-the-Great-Macedonian-phalanx of the stock market (your history tidbit…you can look it up).

By “end” we don’t mean demise.  Though a demise is probably coming. More on that later. We mean the end of epic patterns.

We wrote last week about index-rebalances delayed since December.  In patterns observable through ModernIR behavioral analytics, the effort to complete them stretched unremitting from May 28 to June 18.

Yes, June 19 was a muscular volume day with quad-witching and we saw BIG Exchange Traded Fund (ETF) price-setting that day in many stocks. (Note: ETFs are substitutes for stocks that are easily traded but entitle owners to no underlying assets save the ETF shares.)

But the patterns strapping May to June like a Livestrong bracelet (wait, are those out?) ended almost everywhere June 18.  The effort reflected work by about $30 trillion, adding up money marked to MSCI, FTSE Russell and S&P Dow Jones, to match underlying construction.

Funds moved before rebalances. And the biggest components, ETF data indicate – really, they dwarf everything else – are AAPL and MSFT. Patterns show money piled like a rugby scrum into AAPL call options in early June, and then plowed headlong into AAPL equity between June 12-18.

It’s good business if you can get it, knowing the stock will inevitably rise because of its mass exposure to indexes and how its price then when last money square-danced into an Allemande Left with indexers in December 2019 was about $280.

How many of you remember when AAPL was down to about 5% of the computing market, most of that in academia, and it looked like MSFT would steamroll it right out of business?  And then MSFT was yesterday’s news, washed up, a boomer in a Slack world.

Today both say, Ha! Suckers!

MSFT patterns are like AAPL’s but less leveraged, explaining the divergence in performance over the past year. AAPL is up 84%, MSFT about half that.  You can see here how both have performed versus the Tech-heavy QQQ (Nasdaq 100 from Invesco) and the SPY, State Street’s proxy for the S&P 500.

AAPL and MSFT have pulled the market along like Charles Atlas (and his doppelganger) towing a Pennsylvania railcar (more arcane and anachronistic history for you).

That ended, at least for now.  The Russell reconstitution continues through Friday but in patterns at this point it appears money has already changed mounts, shifted chairs.

The marvel is the magnitude of the effects of these events, and the power of two – AAPL and MSFT.

You’re thinking, “What about the rest of the FAANGs?”

MSFT isn’t one but we include it, and oftentimes now TSLA and AMD.  FB, AMZN, NFLX, GOOG – incisors dripping less saliva than AAPL – are massive, yes. But they don’t pack the ETF power of the two.

Let me give you some data. There are 500 Financials stocks, about 400 Healthcare, around 300 Consumer Discretionary.  Tech is around 200.  Most of these sectors are Oversold, and there’s a lot of shorting. The FAANGs are Overbought and more than 50% short, collectively.

The few outweigh the many.

And meanwhile, Market Structure Sentiment™ is both bottomed and lacking the maw it signaled. Either we skip across the chasm for now, or it trips us soon (stocks love to render fools of soothsayers).

The salient point is that the market can’t be trusted to reflect views on Covid19, or trade with China, or the election in November, or economic data, or actions of the Federal Reserve (curiously the Fed’s balance sheet is tightening at the moment). It’s right now defined by the power of two.

Two legs.

We humans stand fine on two. Can the market?  We’re about to find out.  And the degree to which your shares are at risk, public companies, to those two legs, and your portfolio, investors, is measurable and quantifiable. Ask us, and we’ll show you.

Squid Ink

Is retail money creating a Pandemic Bubble? Sort of. Really, it’s Fast Traders turning those orders into clouds of squid ink.

There are 47 million customer accounts at Schwab, Fidelity, Ameritrade, E*Trade and Robinhood.  These big online brokers sell their flow to Citadel, Two Sigma, Susquehanna’s G1X options platform, Virtu, UBS, options trader Wolverine, and others.

Nearly all of the orders are “non-directed,” meaning the broker determines where to send them.  Also, more than three paragraphs of market structure goop and people grab a bottle of tequila and go back to day-trading.

So, let me explain.

Do you know CHK?  A shale-oil play, it’s on the ropes financially. In May it was below $8. Yesterday CHK was near $70 when it halted for news. Which never came, and trading resumed. (Note: A stock should never, ever be halted for news, without news.)

It closed down hard near $24. Rumors have flown for weeks it’ll file bankruptcy.  Why was it at $70? People don’t understand that public equity often becomes worthless if companies go bust. Debtholders convert to equity and wipe out the old shareholders.

Hertz (HTZ) went bankrupt May 26 and shares closed at $0.56.  Monday it was over $5.50, up about 900%. HTZ debt is trading at less than 40 cents on the dollar, meaning bondholders don’t think they’ll be made whole – and they’re senior to equity.

This is bubble behavior. And it abounds. Stocks trading under $1 are up on average 79% since March, according to a CNBC report.

ABIO, a Colorado biotech normally trading about 10,000 shares daily with 1.6 million shares out made inconsequential reference to a Covid preclinical project (translation: There’s nothing there). The stock exploded, trading 83 million shares on May 28, or roughly 50 times the shares outstanding.

Look at NKLA.  It’s been a top play for Robinhood clients and pandemic barstool sports day-trading. No products out yet, no revenue. DUO, an obscure Chinese tech stock trading on the Nasdaq yesterday jumped from about $10 to $129, closing above $47.

Heck, look at Macy’s.  M, many thought, was teetering near failure amidst total retail shutdown. From about $4.50 Apr 2, it closed over $9.50 by June 8.

W, the online retailer that’s got just what you need, is up 700% since its March low despite losing a billion dollars in 2019.

When day traders were partying like it was 1999, in 1999, stocks for businesses with no revenues and products boomed.  Then the Nasdaq lost 83% of its value.

About 95% of online-broker orders are sold to Fast Traders – the Citadels, the Two Sigmas, the Virtus.  They’re buying the tick data (all the prices) in fractions of seconds. They know what’s in the pipeline, and what’s not.

Big online brokers sell flow to guarantee execution to retail traders.  I shared my experience with GE trades. The problem is retail prices are the ammunition in the machine gun for Fast Traders. They know if clips are being loaded, or not. And since retail traders don’t direct their trades (they don’t tell the broker to send it to the NYSE, Nasdaq, Instinet, IEX, etc., to hide prices from Fast Traders), these are tracer rounds stitching market prices up and down wildly.

The Fast Traders buying it can freely splatter it all over the market in a frenzy of rapidly changing prices, the gun set on Full Automatic.

This is how Fast Traders use retail trades to cause Wayfair to rise 700%. The order flow bursts into the market like squid ink in the Caribbean (I’ve seen that happen snorkeling), and everyone is blinded until prices whoosh up 30%.

A money manager on CNBC yesterday was talking about the risk in HTZ. She said there were no HTZ shares to borrow. Even if you could, the cost was astronomical.

Being a market structure guy with cool market structure tools (you can use them too), I checked HTZ.  Nearly 56% of trading volume is short. Borrowed. And the pattern (see here) is a colossus of Fast Trading, a choreographed crescendo into gouting squid ink.

How? Two Sigma, Hudson River Trading, Quantlab, etc., Fast Trading firms, enjoy market-making exemptions. They don’t have to locate shares. As high-speed firms “providing liquidity,” regulators let them do with stocks what the Federal Reserve does with our money. Digitally manufacture it.

Because they buy the flow from 47 million accounts, they know how to push prices.

That’s how ABIO traded 83 million shares (60% of the volume – nearly 50 million shares – was borrowed May 28, the rest the same shares trading many times per second).

It’s how CHK exploded up and then imploded as the manufactured currency vanished. And when stocks are volatility halted – which happened about 40 times for CHK the past two trading days – machines can game their skidding stop versus continuing trades in the ETFs and options and peer-group stocks related to the industry or sector.

This squid ink is enveloping the market, amid Pandemic psychology, and the economic (and epic) collapse of fundamental stock-pricing.

Dangerous.

You gotta know market structure, public companies (ask us) and investors (try EDGE).

Disruption

What did you say yesterday to your executive team, investor-relations officers, if you’d sent a note Monday about mounting Coronavirus fears?

The market zoomed back, cutting losses in the S&P 500 to about 2% since Jan 17.  We said here in the Market Structure Map Jan 22 that data on market hedges that expired Jan 17 suggested stocks could be down about 2% over the proceeding week.

It’s been a week and stocks were down 2%. (If you want to know what the data say now, you’ll have to use our analytics.)

The point is, data behind prices and volume are more predictive than headlines.

NIRI, the professional association for IR, last year convened a Think Tank to examine the road ahead, and the group offered what it called The Disruption Opportunity.

If we’re to become trusted advisors to executive teams and boards, it won’t be through setting more meetings with stock-pickers but by the strategic application of data.

For instance, if Passive investment powering your stock has fallen 30% over the past 200 trading days, your executive team should know and should understand the ramifications. How will IR respond? What’s controllable? What consequences should we expect?

At a minimum, every week the executive team should be receiving regular communication from IR disruptors, a nugget, a key conclusion, about core trends driving shareholder value that may have nothing to do with fundamentals.

Take AAPL, which reported solid results yesterday after the market closed.  AAPL is the second most widely held stock in Exchange Traded Funds (there’s a nugget).  It’s over 20% of the value of the Tech sector, which in turn is nearly 24% of the S&P 500, in turn 83% of market-capitalization.

AAPL is a big engine (which for you cyclists is American rider Tejay van Garderen’s nickname).  And it always mean-reverts.

It may take time. But it’s as reliable as Rocky Mountain seasons – because the market is powered today by money that reverts to the mean. Over 85% of S&P 500 volume is something other than stock-picking.

AAPL has the widest mean-reversion gap in a half-decade now, with Passive investment down a third in the last week.  AAPL trades over 30 million shares daily, about $10 billion of stock. And 55% of that – 17 million shares, $5.5 billion of dollar volume – is on borrowed shares.

Those factors don’t mean AAPL is entering a mean-reversion cycle. But should the executive team and the board know these facts?  Well, it sure seems so, right?

And investors, would it behoove you to know too?

The Russell 1000 is 95% of market cap, the Russell 3000, over 99.9%.  That means we all own the same stocks.  You won’t beat the market by owning stocks someone else doesn’t.

How then will you win?  I’m coming to that.

IR pros, you’re the liaison to Wall Street.  You need to know how the market works, not just what your company does that differs from another. If your story is as good as somebody else’s but your stock lags, rather than rooting through the financials for reasons, look at the money driving your equity value.

Take CRM. Salesforce is a great company but underperformed its industry and the S&P 500 much of the past year – till all at once in the new year it surged.

There’s no news.  But behaviors show what caused it.  ETF demand mushroomed. CRM is in over 200 ETFs, and the S&P 500.  For a period, ETFs could get cheap CRM stock to exchange into expensive SPY shares, an arbitrage trade.  The pattern is stark.

Now that trade is done. CRM market structure signals no imminent swoon but Passive demand is down over 20% because there’s no profit in the CRM-for-ETFs swap now.

That fact is more germane to CRM’s forward price-performance than its financials.

This, IR pros, is your disruption opportunity in the c-suite. If you’re interested in seeing your market structure, ask and we’ll give you a free report.

Investors, your disruption opportunity isn’t in what you own but when you buy or sell it. Supply and demand rule that nexus, and we can measure it.   If you’d like to know about Market Structure EDGE, ask us.

What Matters

Happy New Year!

I hope you enjoyed our gift:  A two-week break from my bloviating!  We’d planned to run best-of columns and thought better, because everybody deserves a respite.

We relished the season in the Colorado mountains, as this album shows (see world-class ski-race video too).  If the album eludes you, this is Steamboat Springs 2020, and us on snowshoes, and the view up high where it’s always 3 o’clock (a superb ski run).

I’m thinking about 2020.  And I’m reading “The Man Who Solved the Market,” about quant hedge fund Renaissance Technologies, by Wall Street Journal reporter Greg Zuckerman.  You should read it, too.

About 47% in, my Kindle says, Zuckerman writes, “One day, a data-entry error caused the fund to purchase five times as many wheat-futures contracts as it intended, pushing prices higher.

“Picking up the next day’s Wall Street Journal, sheepish staffers read that analysts were attributing the price surge to fears of a poor wheat harvest.”

There’s so much going on behind stock-prices that’s something other than we think. The point for IR people and investors is why do we do what we do?

In fact, it’s a human question. We do things on the belief they count.

For instance, the quarterly “Q&A bible,” the compendium of earnings-call questions, dominated holiday discussion in NIRI eGroups.

Discourse is great.  But does all that preparatory effort matter?

If we’re spending the same time and effort in 2020 on earnings-call Q&A that we did in 2000, well, why?  In 2000, more than 70% of the money was rational. Today it’s 14%.

Tesla is up 42% the past year, which included an earnings call where CEO Elon Musk trashed an analyst during Q&A.  The Twittersphere blew up.

The stock didn’t.

You should have your executive team prepared for questions, investor-relations professionals. But you don’t need a bible in 2020 because rational behavior is a paltry part of why stocks move.

Equal to preparation for questions should be the time directed to educating your executives and board on what can move price with results, and why, and what historical data indicate are risks, and why risk exists in the first place – and if you can mitigate it by changing WHEN you report and how you notify investors.

And if you’re 10/10 Overbought and 60% short before you report, put your best VALUE foot forward. Data, not Q&A, should driver call-prep.

Human beings do things because they ostensibly matter and produce returns.  If we’re going through motions because it’s tradition, then 2020 should be the year you change tradition.

And investors. What matters to you?  Returns, right?

The average S&P 500 component moves 36% every month, intraday (1.6% each day between highest and lowest prices), change often lost in closing prices.  In a perfectly modulated, utterly quantitative Shangri-La, you’d capture ALL of that by buying low and selling high.  You could make 432% per year.

That’ll never happen. Eugene Fama, legendary University of Chicago economics professor, who’s 80 years old and still teaching, won a Nobel Prize for demonstrating the return-diminishing pugnacity of volatility.

But if there’s so much volatility, why expend immense effort finding great companies when the odds are roughly 1% that doing so will produce market-beating returns?

Wouldn’t it be smarter – wouldn’t it matter more – to surf volatility waves in today’s market?

I find in traveling around the country – we’re headed to Austin Thursday – talking to IR people and investors that they’re depressed by these things.

If what we learned doesn’t matter, should we rend garments, gnash teeth and weep?

No.

That’s like being depressed by passing time.  Time is a fact.  We can make the most of it, or we can rue its passage.  What’s it gonna be?

So what, IR people, if you don’t need a 400-page Q&A document that requires a software package to manage?  A single Word page, stored to the cloud so you can cross-reference in future quarters, is proportionate.  You’ve saved TIME to do things that MATTER.

What matters?  If you want to be in the US equity markets in 2020 as a public company, an investor-relations professional, an investor, what matters is knowing what money is doing.

It’s a law of success.  It’s not what you know about YOU that matters.  It’s what you know about life, the environment you’re in, the job you’re doing, about how to build relationships.

Right?

We should stop spending all our time understanding our businesses, and none understanding the market that assigns value to them.  That’s the flaw of IR.  Nothing more.  Let’s change it in 2020.

And you investors, why all the Sisyphean work finding great businesses without first understanding how the market transforms those businesses into products with fleeting and ever-evolving value?

If you could capture just 10% of the daily volatility of the S&P 500 by buying stuff low and selling it high, you’d win. It’s provable, useful math. That matters.

Resolve to make 2020 the year you learn what the money is doing.  It matters. We at ModernIR figured out the road map. Ask us how to start on the journey.

Activism Science

In fourteen years, we’ve not missed an Activist.

“Chest-thumping, Quast?” you say.

No, a market structure lesson, a way for investor-relations professionals to be valuable.

Activism has become the de jour Value Investment proposition for modern markets. Our data indicate 10% of all US stocks – just 12% of daily volume is driven by Active Investment – have footprints of Activism.

Think about the enormous sums spent on Activism defense.  Surveillance firms that (no offense, friends!) almost never catch Activist presence proactively because Activists have had 35 years to know how to hide their footprints from settlement-based market intelligence.

The lawyers.  The bankers. The proxy solicitors. The communications consultants.  The running taxicab meter for expenses.

I’m not saying these advisors are pointless by any stretch. But wouldn’t it be prudent to observe what the money is actually doing?  I can offer a litany of examples (scores, but here just a few).

We saw footprints of Activism more than a quarter ahead of the advent of Activism in a small-cap.  Nine months later, the Activist pushed the company into a merger with a competitor.

Maybe a deal was best. But clunky Activist steps were crudely apparent in the data. We’d see a burst of derivatives bets – and five days later the Activist would issue some public declamation. So we could always tell the company when the Activist was about to spout off again.

At no point during the process were investors enthusiastic – but management quit early. The data clearly indicated they could win. The bankers didn’t have that data. Neither did surveillance or the proxy solicitors. I don’t know what those advisors told the team. Isn’t it wise to check and balance your advisors too?

Our data in the hands of a management team with temerity would have produced a fight – and maybe a much better deal.

Market Structure Analytics are like an EKG. We can see how the heart of investment is responding. Is there a burst of adrenaline? We’ll measure it. Apathy? We’ll see that too.

We warned another small-cap two quarters before Elliott showed up in 13Fs (and surveillance was utterly unaware throughout). We have algorithms that remove subjectivity. They are indiscriminate in identifying hedge funds, which half the time are not nefarious. But it’s better to know than not, right?

Advance warning put management in a strong position, and while that situation too also concluded in a deal, the company drove it rather than the other way around, which is always best for executive teams. And too, investor-relations is frontline defense, chief of intelligence for its boards and executive teams. That earns rewards, kudos.

In a high-profile case, we observed pervasive deal-arbitrage in a large-cap with a controlling shareholder. We told the IR team we were flummoxed, but the data were irrefutable. People were betting on a deal. They had no answer.

Then they and we both learned that indeed a deal was in the works that no one (apparently not no one!) ostensibly knew about, including the IR team.

Then an Activist manifested. Every time the Activist would publicly oppose the plan, we saw short-covering and long bets hidden behind headline selling – telling us the Activist really favored the plan but wanted a bone, an appeasement.

That data was vital for decision-making and led to a solution favorable to all parties.

Behavioral data isn’t a silver bullet freeing you from the travails of event-driven behavior (Market Structure Analytics are equally effective at predicting deals and their success, signaling where arbs expect news, predicting and tracking the arc – including success or failure – of short attacks, and spotlighting big bets on surprises around financial results).

The market is mathematical. It’s unwise in event-driven situations to spend all your resources on qualitative input from wildly expensive advisors, when affordable quantitative data offers the most accurate, predictive, unvarnished and timely view of success, failure, threats, opportunities.

If you want to know how we see Activism, deal-arbitrage, short attacks and more, ask us. We can look back historically and show patterns around your own experiences – which lays the foundation for future warning. And we have a compendium of event-driven situations we’ve addressed.

What’s better than glimpses into the future? Would that we had more of them in life – but you can have them in the stock market. It’s math. And science.

Exchanging Data

Do we need another stock exchange?

I’ve been asked this question repeatedly since Bank of America Merrill Lynch, Charles Schwab, Citadel Securities, E*TRADE, Fidelity Investments, Morgan Stanley, TD Ameritrade, UBS, and Virtu Financial agreed Jan 7 to collaborate on seeking approval for a 14th official US stock market.

The answer? It depends on who “we” is, or are.

Adam Sussman of block-trading firm Liquidnet wrote that it’s an effort to lower trading costs which, thanks to high prices from exchanges for data feeds, have gone the opposite direction of trading commissions.

As to further fragmentation – more venues, less aggregation of buyers and sellers – Sussman says amusingly (the whole piece is funny) that “fragmentation is like having kids – after you have three of them, you just go numb to the pain.”

Michael Friedman, formerly of proprietary trading shop and technology vendor Trillium Management, said at TABB Forum (registration required) that these trading firms representing perhaps more than half of all volume resent how the exchanges keep raising prices for market data that brokers themselves create.

Before the exchanges IPO’d – all but IEX are now owned by public shareholders – they were member-owned, and members didn’t pay for data. Coincidentally the new market is called MEMX, or Members Exchange, anachronistically hailing a different era.

Friedman artfully unfolds market structure, explaining how a bid to buy shares at $9.08 at the NYSE cannot execute if the Nasdaq has a bid to buy at $9.10 because buyers willing to pay more are given legal priority and the trade must route out to the Nasdaq.

What if these firms were to route all the best trades – ones wanting to be the highest bid to buy or offer to sell – to themselves?  They could conceivably ravage market-share among big exchange groups until costs fell to a new equilibrium.

I think there are two other big reasons for this new cooperative.

One is easy to understand. Brokers are required to prove to customers that they provide “best execution,” or trading services that are at least as good as the average.  Paradoxically, that standard is predicated on averages for customer trades in the market – which concentrate heavily into the largest firms, including several MEMX backers.

If the order flow is consistently better than the average, it’s conceivable these firms could use their own data for free to meet best-execution requirements, a tectonic fist-bump amidst market rules.

So how would they boost odds that their data are better?  Look at who’s involved. They are mostly retail brokerage firms, or firms buying retail flow.

At Fidelity, about 97% of the firm’s retail orders are “nondirected,” lacking instructions about where the trades should occur. And well over 50% of those orders are sent to Virtu and Citadel.

Schwab says 99.6% of its trades are nondirected and 70% of them go to Virtu, Citadel and UBS.

And guess what?  Retail orders are permitted under rules to, in the jargon of market structure, “price-improve” trades.  The NYSE says its Retail Liquidity Program “can be used by retail firms directly as well as by the brokers who service retail order flow providers.”

Interactive Brokers, a firm for sophisticated retail traders and hedge funds, says retail orders with a limit, or set price, can be hidden from display at exchanges in increments of a thousandth of a dollar better than the displayed one, and the orders will float with a changing bid to buy or offer to sell.

That is, if the best bid to buy everyone sees is $9.08, a hidden limit order can be set at $9.081 and bounce like a bobber, staying always a fraction of a penny better than visible prices.

Under market rules, stocks cannot quote in increments below a penny. But they sure can trade in smaller increments, and they do all the time.

By aggregating retail order flow that market rules give a special dispensation to be better than other orders the members of MEMX believe they can not only match more orders but create the best market data.

How is it possible? Regulators wanted to be sure the little guy wouldn’t get screwed, so they give retail trades preference. They never dreamed innovative high-speed traders would buy it, or take advantage of rules permitting these trades to have narrower spreads.

It may work.

The problem is that the advantage MEMX hopes to leverage is a regulatory one that gives special access to one kind of activity.  (Editorial note: As we’ve written repeatedly, it’s just as Exchange Traded Funds have proliferated not by being better but through unique regulatory advantages giving them a private, wholesale block market with no transparency).

What’s it mean to investors and public companies? Investors, you could be picked off because MEMX could have compounded capacity to price-improve non-displayed orders. Public companies, something other than capital-formation is driving markets, which is not in your best interest.

We’d prefer a fair, level playing field serving investors and issuers, not rules permitting exceptions traders can game.

Sector Insights

We take a moment to honor the passing of George Herbert Walker Bush, 41st President of the United States, who earned respect across aisles and left a legacy of dignity, achievement and service.

Markets are closed today in Presidential honor, perhaps fortuitously, though it won’t surprise us if stocks surge back, confounding pundits. A CNBC headline at 4:24pm ET yesterday said, “Dow plunges nearly 800 points on fears of cooling economy.”

The article said the slide steepened when Jeffrey Gundlach of Doubleline Capital told Reuters the yield-curve inversion (three-year Treasury notes now pay more than five-year notes) signals that the economy is “poised to weaken.” A drubbing in Financials (weren’t we told higher rates help banks?) and strength for Utilities were said to support that fear.

Yet Sector Insights (I’ll explain in a moment!) for Financials show the rally last week came on Active Investment – rational people buying Financials.  In a spate of schizophrenia, did Active money seize a truncheon and bludgeon away its gains in a day?  Possible, maybe. But improbable.

Utilities have been strong all year (see Figure 1). Market Structure Sentiment™ for Utilities from Jan 3-Dec 3, 2018 is 5.4/10.0 – solidly GARP (sectors trade between 4 and 7 generally). Utilities haven’t dipped below 4.0 since late June.

If strength in Utilities signals economic fear, did it commence in January (or March, when they soared after the market corrected)?

What if it’s market structure?  Did anyone ask?  Add up the week-over-week change in the two behaviors driving Utilities highe

Figure 1 – Market Structure Sentiment(TM) – Utilities Sector – 2018. Proprietary ModernIR data.

r the past week and what we call internally “behavioral volatility” was massive – 22%.  Daily behavioral change is routinely 2% total!

We’ve long said that behavioral volatility precedes price-volatility.  Last Friday, daily behavioral volatility in the entire market was a breathtaking 19.6% (5.4% jump in Active Investment, sizzling 14.2% skyhook from Fast Traders) at month-end window-dressing.  On Thu, Nov 29, it was 20%, driven by Passive Investment and Risk Mgmt, a behavioral combination signaling ETF creations and redemptions.

On Monday Dec 3, ETF basket-moves drove another 15% surge. Think about it: 20%, 20%, 15%. Picture a boat rocking as people rush from one side to the other, and the momentum builds until the boat tips over.

Economic fear exists. And the yield curve has predicted – what’s the economics joke? – five of the last three recessions.

But the curve could as well trace to selling by the Fed of $350 billion of Treasurys and mortgage securities while the Treasury gorges on short-term paper to fund deficits.

Most see the market as a ticking chronometer of rational thought.  It’s not, any more than your share-price is a daily reflection of investors’ views of your management’s credibility. It is sometimes. Data say about 12% of the time.

If pundits think it’s economics when it’s a structural flaw in the market, the advice and actions are wrong.  And we could be caught unprepared.

Don’t people move money into and out of index funds or ETFs too in reaction to economics?  Sure. But not daily.  We just had this discussion with our financial advisors and we like most allocating assets plan in long swaths on risk and exposure.

And I’ll say it till everyone gets it: ETFs do not form capital or buy or sell stocks. They are continually created and redeemed by parties swapping collateral (stocks and cash) back and forth to profit on spreads between that underlying collateral and the frenzy of arbitrage in ETF shares traded in the stock market.

It’s those people and machines in the market who rush back and forth and rock the boat, arbitragers trying to profit on different prices for the same thing.

Especially if they’ve borrowed collateral or leveraged into expected short-term moves. They’ve tipped the market over three times now just since early October.

You can see it in patterns. Speaking of which, wouldn’t it be nice to know what’s driving your sector the next time the CEO says, “Why is our stock down while our peers are up?”

To that end, we’re delighted to announce our latest innovation at ModernIR:  Sector Insights.  Now you can compare the trading and investment behaviors behind your stock and your sector.

We classify every company by GICS industry and sector.  Algorithms can then cluster a variety of data points from investment and trading behaviors, to shorting, and intraday volatility and Market Structure Sentiment™, providing unprecedented clarity into sector trends and drivers.

If you’re interested in seeing your Sector Insights alongside your Market Structure Report, send a note to Mike Machado here. (Clients, you can see a three-minute overview of how to use Sector Insights in concert with your Market Structure Reports here.)

Meanwhile, buckle up.  December could further provide a wild ride to investors – and you’ll see it in Sector Insights if it’s coming.  We’ll be here to help you help your executives and board directors understand what’s driving equity values.

Borrowed Time

“If a stock trades 500,000 shares daily,” said panelist Mark Flannery from hedge fund Point72 last Thursday on my market-structure panel, “and you’ve got 200,000 to buy or sell, you’d think ‘well that should work.’ It won’t. Those 500,000 shares aren’t all real.”

If you weren’t in Austin last week, you missed a great NIRI Southwest conference.  Mr. Flannery and IEX’s John Longobardi were talking about how the market works today.  Because a stock trades 500,000 shares doesn’t mean 500,000 shares of real buying and selling occur.  Some of it – probably 43% – is borrowed.

Borrowing leads to inflation in stocks as it does in economies.  When consumers borrow money to buy everything, economies reflect unrealistic economic wherewithal. Supply and demand are supposed to set prices but when demand is powered by borrowing, prices inevitably rise to unsustainable levels.  It’s an economic fact.

All borrowing is not bad. Borrowing money against assets permits one to spend and invest simultaneously.  But borrowing is the root of crises so watching it is wise.

Short interest – stock borrowed and sold and not yet covered and returned to owners as a percentage of total shares outstanding – isn’t unseemly. But it’s not a predictive indicator, nor does it describe risk. The great majority of shares don’t trade, yet what sets price is whoever buys or sells.

It’s far better to track shares borrowed as a percentage of total traded shares, as we described last week. It’s currently 43%, down one percentage point, or about 2.3%, as stocks have zoomed in latter August.

But almost 30% of stocks (excluding ETFs, routinely higher and by math on a handful of big ones averaging close to 60%) have short volume of 50% or more, meaning half of what appears to be buying and selling is coming from something that’s been borrowed and sold.

In an up market, that’s not a problem. A high degree of short-term borrowing, much of it from high-speed firms fostering that illusory 500,000 shares we discussed on the panel, means lots of intraday price-movement but a way in which short-term borrowing, and covering, and borrowing, and covering (wash, rinse, repeat), may propel a bull market.

In the Wall Street Journal Aug 25, Alex Osipovich wrote about how Goldman Sachs and other banks are trying to get a piece of the trading day’s biggest event: The closing auction (the article quotes one of the great market-structure experts, Mehmet Kinak from T Rowe Price). Let’s dovetail it with pervasive short-term borrowing.

We’ve mapped sector shorting versus sector ETF shorting, and the figures inversely correlate, suggesting stocks are borrowed as collateral to create ETFs, and ETFs are borrowed and returned to ETF sponsors for stocks.

A handful of big banks like Goldman Sachs are primary market-makers, called Authorized Participants (as opposed to secondary market-makers trading ETFs), which create and redeem ETF shares by moving stock collateral back and forth.

The banks give those using their versions of closing auctions the guaranteed closing price from the exchanges.  But it’s probably a great time to cover short-term ETF-related borrowings because trades will occur at an average price in effect.

The confluence of offsetting economic incentives (selling, covering borrowings) contribute to a stable, rising market. In the past week average intraday volatility dropped to 1.9% from a 200-day average of 2.5% at the same time shorting declined – anecdotal proof of the point.

What’s the flip side?  As with all borrowing, the bill hurts when growth stalls. When the market tips over at some future inevitable point, shorting will meet shorting. It happened in January 2016 when shorting reached 52% of total volume. In February this year during the correction it was 46%. Before the November election, short volume was 49%.

The point for both investors and public companies is that you can’t look at trading volume for a given stock and conclude that it’s equal and offsetting buying and selling. I guarantee you it’s not.

You don’t have to worry about it, but imbalances, however they may occur, become a much bigger deal in markets dependent on largescale short-term borrowing. It’s another market-structure lesson.

Rules and Money

There are two pillars to market intelligence: The Rules, and The Money.

By market intelligence, I mean information about what’s pricing a stock. So, translating, information about what’s pricing a stock must derive from the rules that govern stock-trading, and how money conforms to those rules.

Wouldn’t that be supply and demand?  Would that it were! There are instead four big rules for stocks now, tenets of Regulation National Market System about which every investor and investor-relations officer should have a basic grasp.

“Quast,” you say. “This sounds about as exciting as cleaning a tennis court with a tooth brush. In Houston. In the summer.”

It can be very exciting, but the point isn’t excitement.  If you don’t know the rules (always expect your market intelligence provider to know the rules for stocks), your conclusions will be wrong.  You’ll be guessing.

For instance, if you report strong results and your stock jumps on a series of rapid trades, can a human being do that?  Refer to the rules. What do they require?  That all marketable trades – an order to buy or sell stock – be automated.

No manual stock order can be marketable. Manual orders are nonmarketable, meaning prices for the stock must come to them instead. Picture a block of cheese and a grater passing by it and shaving some off.

The rule creating this reality in stocks is the Order Protection Rule, or the Trade-Through Rule. Same thing. It says traders cannot trade at $21.00 if the same stock is available for $20.99 somewhere else. To ensure compliance, regulators have mandated that orders wanting to be the best bid to buy or offer to sell must be automated.

And the bid to buy will always be lower than the offer to sell. Stocks may only trade at them, or between them.  There can only be one best price (though it may exist in several places).

Now start thinking about what money will do in response.  Orders will be broken into pieces. Sure enough, trade size has come down by factors, and block trades (we wrote about it) are a tiny part of the market.

Big Commandment #2 for stocks is the Access Rule. It goes hand-in-glove with the first rule because it’s really what turned the stock market into a data network.

The Access Rule says all market centers including stock markets like the five platforms operated by the NYSE, the three owned by the Nasdaq, the four owned by CBOE, the newest entrant IEX, and the 32 broker markets that match stock trades must be connected so they can fluidly share prices and customers.

It also capped what exchanges could charge for trades at $0.30/100 shares – paid by brokers trading in the stock market for themselves or customers (the SEC Fee Pilot Program aims to examine if these fees, and their inverse, incentive payments, cause brokers to execute trades in ways they would not otherwise choose).

The third big rule outlaws Sub-Penny Pricing, or quoting in increments so small they add no economic value.  You may still see your stock trading at $21.9999 because of certain exceptions for matching at midpoints of quotes.

Reg NMS lastly imposed new Market Data Rules. Since everyone is sharing prices and customers on this network called the stock market, plans had to be refined for pooling data-revenue (prohibiting sub-penny trading was meant to prevent a proliferation of tiny meaningless prices).

Yet, data is a byproduct of prices. There are hundreds of millions of dollars of revenue governed by the Consolidated Tape Association, which divides proceeds according to how various platforms and brokers quote and trade in accordance with best prices. Outside the CTA, there may be billions of dollars now in proprietary data feeds.

These rules drive how money behaves. The fastest machines will price your stock to start the day no matter where you trade, because they have the quickest bids and offers. But their purpose is to profit on changing prices, not to own stocks.

Passive investment dominating the market is aided by rules. What lies between the bid and the offer? The average price. Those tracking benchmarks like index mutual and exchanged-traded funds get a boost toward their objective.  Prices become uniform (our data show very tight Poisson distribution in the stock market – which helps securities tracking benchmarks).

And because stock prices are highly unstable – average intraday spread in the Russell 1000 the past five trading days is 2.6%, and the typical stock trades over 16,000 times daily in 167-share increments – investors turn to substitutes like derivatives. Even Warren Buffett who once famously skewered them as instruments of mass financial destruction has large derivatives positions.

Let’s finish where we started. Why doesn’t supply and demand drive stock prices? Because rules governing trades don’t let supply and demand manifest naturally. The greatest proportion of trades are now driven by machines wanting to own nothing, the opposite of a market animated by supply and demand.

When you look at your stock or stocks in your portfolio, remind yourself: What’s driving them up and down are rules, and money racing around a course in compliance with those rules.  Some part is rational. A bunch of it isn’t.  We all – investors and public companies – can and should know what’s going on. The first rule, after all, is to be informed.

Welcome to the 21st century stock market.