Tagged: Trading

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.

Lab Knowledge

We are finally watching Breaking Bad five years after the most successful basic cable series in television history ended.

It’s symbolic of the era that we’re viewing it via Netflix. And NFLX Market Structure Sentiment is bottomed, and shorts have covered. We’ll come to market structure in a moment because it intersects with Breaking Bad.

Launched in 2008, Breaking Bad is about high school chemistry teacher Walter White, who turns to cooking methamphetamine to cover medical bills. He becomes Heisenberg, king of blue meth.

I won’t give the story away but what sets Walter White apart from the rest of the meth manufacturers is his knowledge of molecular structure. Let’s call it Lab Knowledge.  With lab knowledge, Walter White concocts a narcotic compound that stuns competitors and the Drug Enforcement Agency alike. He produces it in a vastly superior lab.

In the stock market there’s widespread belief that the recipe for a superior investment compound is the right set of ingredients comprised of financial and operating metrics of businesses.

Same goes for the investor-relations profession, liaison to Wall Street. We’re taught that the key to success is building buyside and sellside relationships around those very same financial and operating metrics.

There’s a recipe. You follow it, and you succeed.

Is anyone paying attention to the laboratory?

The stock market is the lab. Thanks to a total rewriting of the rules of its chemistry, the laboratory has utterly transformed, and the ingredients that underpin the product it churns out now are not the same ones from before.

I don’t mean to toot the ModernIR horn, but we did the one thing nobody else bothered to do.  We inspected the lab.  We studied the compounds it was using to manufacture the products circulating in the market (ETFs, high-speed trading, etc.).

And we saw that stock pickers were failing because they didn’t understand what the lab was producing. It was not that they’d stopped finding the historically correct chemical elements –financial and operating metrics defining great companies of the past.

It’s that these ingredients by themselves can no longer be counted on to create the expected chemical reaction because the laboratory is compounding differently.

And the difference is massive. The lab determines the outcomes. Write that down somewhere. The lab determines the outcomes. Not the ingredients that exist outside it.

So investors and public companies have two choices.  Start a lab that works in the old way.  Or learn how the current lab works. The latter is far easier – especially since ModernIR has done the work. We can spit out every manner of scientific report on the ingredients.

Back to market structure, before NFLX reported results it was 10/10 Overbought, over 60% short and Passive money – the primary chemical compound for investments now – was selling.  The concoction was destined to blow up.

Everyone blamed ingredients like weaker growth and selling by stock pickers, when those components were not part of the recipe creating the explosion in NFLX. Now, NFLX will be a core ETF manufacturing ingredient, and it will rise.

Investors, what’s in your portfolio?  Have you considered the simmering presence of the laboratory in how your holdings are priced?  And public companies, do you have any idea what the recipe is behind your price and volume?

If you want to be in the capital markets, you need lab knowledge. Every day, remind yourself that the ingredients you’re focused on may not be the ones the lab is using – and the lab determines the outcome. The lab manufactures what the market consumes.

One of the things we’ll be talking about at the NIRI Southwest Regional Conference is the laboratory, so sign up and join us Aug 22-24 in Austin.  Hope to see you there!

 

 

Big Pillow Fight

I hope you enjoyed summer vacation from the Market Structure Map!

We skipped last week while immersed in NIRI National, the investor-relations profession’s annual bash, this year at the Wynn in Las Vegas, where at the ModernIR booth these passersby in feathers joined us for a photo (and Sammy Davis, Jr., whom I’d mistakenly thought had expired some time ago).

Speaking of feathers, a “big league” (bigly?) pillow fight has erupted over the SEC’s proposed Access Fee Pilot Program – we’ll explain – and the exchanges are stuffing the digital airwaves with nasal-clogging goose down over it.  How to blow the air clear?

Before we answer, you may be thinking, “Tim, didn’t you write about this June 6?” Yes. But I’ve had relentless questions about what the exchanges are saying.

The IR industry’s biggest annual event last week had nothing on market structure. Never has there been a session at NIRI National called “How Stocks Trade Under Reg NMS.”  You can earn an Investor Relations Charter designation, our version of the CFA, without knowing how stocks trade, because the body of knowledge omits market structure.

As one IR officer said to me, “It’s become acceptable today to not know how our stock trades, and that ought not be.”

No wonder our profession has officially taken a neutral position on something the listing stock exchanges generally oppose, and investors support – this latter lot the audience for IR, and ostensibly the buyers and sellers exchanges are knotting in matrimony.

Do you see?  We’re told the stock market matches investors with investments. Yet exchanges and investors have opposing views, and public companies, the investments of the market, are neutral. What could be more bizarre?

Well, okay. There are beings walking the hallways of casinos on the strip more bizarre than that. But follow me here.

As we explained last week, this trading study is intended to assess how fees and incentives affect the way stock-prices are set and how trades are circulated around the data network that our stock market has become today.

In 2004, when the current market structure was still being debated, the NYSE’s then CEO said trading incentives should be prohibited. The Nasdaq thought requiring a national best price would lead to “flickering quotes” and “quote shredding,” terms that describe unstable prices resulting purely from effort to set the price.

Step forward.  The exchanges are paying some $3 billion of combined (that includes amounts from CBOE, operator of four erstwhile BATS equity markets) incentives aimed at setting prices, and we have flickering and shredded quotes all over the market as evidenced by the SEC’s own data (Midas) on ratios of quotes to trades.

And both exchanges want these conditions to persist because both make money selling data – which is the byproduct of a whole bunch of prices.

This is the key point: Exchanges pay traders to set prices. Picture a table with marbles on it.  Exchanges are positioned at the corners. Consider incentives called trading rebates a weight that exchanges can lean on the corners to cause marbles to roll toward them.  The more rolling marbles, the more data revenue they capture.  So you see why exchanges want those payments to continue – and why they are pressing issuers hard for support.

Investors are the marbles. The incentives cause marbles to roll AWAY from each other, the opposite of what investors want. They want orders with big size and stable prices, a big marble pool.

The problem for issuers is that prices are set to create data revenues, not to match investors.  The culprit is a market that behaves like a flat table with marbles on it, when a market ought to encourage the formation of a big pool of marbles.

That the SEC wants to examine an aspect of this structure is itself encouraging, however.

Regulation National Market System, the Consolidated Tape Association Plan, and exchange order types coalesce to create the market we have now. We understand them.  Do your trusted sources of market information explain these things to you?  You cannot interpret the market without first understanding the rules that govern its function.

I don’t blame our friends at the exchanges for clinging to current structure. They have their own revenue streams in mind. Human beings are self-interested, the cornerstone of international relations from the beginning of time. But you should not count on unbiased information about your trading to come from trading intermediaries.

You can count on unbiased analytics from ModernIR, because we are the IR profession’s market structure experts.  If you want to see how your stock trades, ask us.

Piloting Fees

What do these pension funds below have in common?

All (over $1.3 trillion of assets), according to Pensions & Investments, periodical for retirement plans, endorse the SEC’s Fee Pilot program on stock-trading in US equities.

The California State Teachers’ Retirement System
The California Public Employees Retirement System (CalPERS)
The Ontario Teachers Pension Plan (Canada)
The New York City Retirement Systems
The State of Wisconsin Investment Board
The Alberta Investment Management Corp. (Canada)
The Healthcare of Ontario Pension Plan (Canada)
The Alaska Permanent Fund Corp.
The Arizona State Retirement System
The San Francisco City & County Employees’ Retirement System
The Wyoming Retirement System
The San Diego City Employees’ Retirement System

In case you missed the news, we’ll explain the study in a moment. It will affect how stocks trade and could reverse what we believe are flaws in the structure of the US stock market impeding capital formation. But first, we perused comment letters from other supportive investors and found:

Capital Group (parent of American Funds) $1.7 trillion
Wellington Management, $1 trillion
State Street Global Advisors, $2.7 trillion (but State Street wants Exchange Traded Products, ETPs, its primary business, excluded)
Invesco, $970 billion
Fidelity Investments, $2.4 trillion
Vanguard, $5.1 trillion
Blackrock, $6.3 trillion (with the proviso that equal ETPs be clustered in the same test groups)
Assorted smaller investment advisors

By contrast, big exchange operators and a collection of trading intermediaries are either opposed to the study or to eliminating trading incentives called rebates.  We’ll explain “rebates” in a bit.

That the views of investors and exchanges contrast starkly speaks volumes about how the market works today.  None of us wants to pick a fight with the NYSE or the Nasdaq. They’re pillars of the capital markets where we’re friends, colleagues and fellow constituents. And to be fair, it’s not their fault. They’re trying to compete under rules created by the SEC. But once upon a time exchanges matched investors and issuers.

Let’s survey the study. The program aims to assess the impact of trading fees, costs for buying and selling shares, and rebates, or payments for buying or selling, on how trading in stocks behaves.  There’s widespread belief fees distort how stock orders are handled.

The market today is an interconnected data network of 13 stock exchanges (four and soon five by the NYSE, three from the Nasdaq, and four from CBOE, plus new entrant IEX, the only one paying no trading rebates), and 32 Alternative Trading Systems (says Finra).

The bedrock of Regulation National Market System governing this market is that all trades in any individual stock must occur at a single best price:  The National Best Bid to buy, or Offer to sell – the NBBO.  Since exchanges cannot give preference and must share prices and customers, how to attract orders to a market?  Pay traders.

All three big exchange groups pay traders to set the best Bid to buy at one platform and the best Offer to sell at another, so trades will flow to them (between the NBBO).  Then they sell feeds with this price-setting data to brokers, which must by rule buy it to prove to customers they’re giving “best execution.” High-volume traders buy it too, to inform smart order routers.  Exchanges also sell technology services to speed interaction.

It’s a huge business, this data and services segment.  Under Reg NMS, the number of public companies has fallen by 50% while the exchanges have become massive multibillion-dollar organizations.  No wonder they like the status quo.

The vast majority of letters favoring the study point to how incentive payments from exchanges that attract order flow to a market may mean investors overpay.

One example: Linda Giordano and Jeff Alexander at BabelFish Analytics are two of the smartest market structure people I know. They deal in “execution quality,” the overall cost to investors to buy and sell stocks. Read their letter. It explains how trading incentives increase costs.

Our concern is that incentives foster false prices. When exchanges pay traders not wanting to own shares to set prices, the prices do not reflect supply and demand. What’s more, the continuous changing of prices to profit on differences is arbitrage. The stock market is riven with it thanks to incentives and rules.

The more arbitrage, the harder to buy and sell for big investors. Arbitrage is the exact opposite motivation from investment. Why would we want a market full of it?

The three constituents opposing eliminating trading payments are the parties selling data, and the two principal arbitrage forces in the market:  High-frequency traders, and ETFs.

What should matter to public companies is if the stock market is a good place for the kind of money you spend your time targeting and informing. Look at the list above. We’ve written for 12 years now about how the market has evolved from a place for risk-taking capital to find innovative companies, to one best suited to fast machines with short horizons and the intermediaries selling data and services for navigating it.

Today, less than 13% of trading volume comes from money that commits for years to your investment thesis and strategy. All the rest is something else ranging from machines speculating on ticks, to passive money tracking benchmarks, to pairing tactics involving derivatives.

So public companies, if your exchange urges you for the sake of market integrity to oppose the study, ask them why $22 trillion of investment assets favor it? When will public companies and investors take back their own market? The SEC is offering that opportunity via this study.

Are there risks? Yes. The market has become utterly dependent for prices on arbitrage. But to persist with a hollow market where supply and demand are distorted because we fear the consequences of change is the coward’s path.

Ticking Down

In 2016 to much fanfare, the SEC and the stock exchanges smashed a bottle of champagne on the looming bow of a tick-size study and launched that battleship into the markets.  Two years later the tick study is limping into port in a lifeboat.

For those of you thinking what the heck is a tick-size study, the US stock market is top-heavy.  The weighted average market capitalization of the Wilshire 5000 Total Market Index is $165 billion, yet the median is $1.1 billion.  The market is skewed massively large.  We mentioned these data in our 2014 comment letter on the SEC’s tick study.

Over 90% of the Wilshire 5000’s market cap is concentrated in less than 750 companies – with the bulk of trading volume, inclusion in indexes, Exchange Traded Funds. Seen another way, the Russell 1000 is about 92% of market cap, the Russell 2000, 8%.

The SEC looked across the sea of the market and determined that small caps were marooned in forgotten eddies and byways.  How to remedy it?  Hike the spread.

Historic backdrop is needed to appreciate the irony. Today the market trades in mandated penny spreads, thanks to SEC-led decimalization of markets in 2001.  Why? Back then, many thought intermediary brokers were gouging investors by buying low and selling way too high.

By reducing spreads to a penny, computerized trading systems were able to compete with brokers. The cost to trade plunged.  Regulators cheered their own brilliance.

But sellside research imploded. Without a trading spread to fund cost centers like analysts poring over data and penning reports, the number of firms supporting small stocks with market-making operations tumbled.

The average IPO before decimalization had 66 underwriters, which wrote research on the many thousands of traded stocks. Today’s IPOs have on average six underwriters. Of the 3,500 individual companies comprising the Wilshire 5000 Index, about 2,500 have little or no analyst coverage, and wan trading.

Regulators thought, “Maybe we should widen the spreads?”

When you’re through laughing, I’ll resume the story.

So in 2014, the SEC directed exchanges to run a study grouping stocks – comprising virtually all small caps by our count – in control and variable buckets to see if lifting the spread from one penny to more, such as five cents, would lead to more market-making.  It took two years to hash out details, and the study commenced in October 2016.

The plug will be pulled in October now because the study has produced scant measurable change.  By my reading, market capitalization has become even more concentrated during the study, and the number of public companies continues to shrink.

If wider spreads worked before, why didn’t they work this time?  Four words: Regulation National Market System. Before decimalization, stock markets were not connected to each other electronically and forced to share prices and customers and trade at a single best national price – across all platforms – called the National Best Bid or Offer.

Reg NMS gave us that market. Hike the spread from one penny to five where all trading is still electronic, markets interconnected around the BBO, all you’ve done is widen the step into the same building, and the same behaviors that run up and down the steps – high-speed machines – still set the price.

Nothing has been done to change the economics of brokerage, which still won’t support research.  Plus, rules, not economics, determine spreads.

Suppose you were in the banana business, and you flew back and forth from Belize buying bananas and selling them here. Then the government said you could only make a penny per banana. You cannot predict from time to time if a penny spread on bananas will work for you. And nearer banana growers would put you right out of business.

That is exactly what happened to small caps. They’ve been ticked down to uneconomical. You can’t expect to succeed now as a new public company in US markets unless you land among the thousand largest. The cutoff? About $2.5 billion.

Could we fix this problem? Of course!  But the forces wanting a thousand liquid low-spread stocks to support everybody’s index, ETF, trading, and stock-picking portfolios are powerful.  Until we realize we’ve no longer got a capital formation battleship and it’s instead adrift on a raft, we best love low ticks and big stocks.

SEC vs NYSE

Our good friends at Themis Trading wrote last week about a $14 million settlement between the NYSE and the SEC over a series of violations.

Why care, issuers and investors? Suppose nobody told you the road you take daily to work sat atop a growing sink hole. We’re all responsible for the market that serves us and as such we have a duty to understand it. Do you know how it works?

Credit Haim Bodek for research leading to SEC action. Had not Mr. Bodek, one of the great market-structure experts of the modern era, blown the whistle, we might not know of these problems. Follow him on Twitter: @haimbodek.

Picking up from Joe and Sal at Themis (Note: With permission.  We’ve edited some for length):

The SEC Case Against NYSE

The NYSE case involves five serious violations.  We will list them all here but we want to focus on the fifth violation since we think it is the most egregious one:

1) On July 8, 2015, NYSE and American Negligently Represented That Their Quotations Were Automated When They Were Not.  NYSE and American Negligently Marked Quotations as Automated When They Had “Reason to Believe” They Were Not Capable of Displaying Automated Quotations

2) Arca Improperly Applied Price Collars to Reopening Auctions During August 24, 2015 Market Volatility.  Arca’s failure to have an effective exchange rule regarding the application of price collars to reopening auctions violated Section 19(b)(1) of the Exchange Act.

3) On March 31, 2015, Arca Erroneously Implemented a Regulatory Halt and Failed to Publish Closing Order Imbalance Information. Although Arca intended to suspend trading only on Arca, which would allow trading of Arca-listed securities to continue on other exchanges, Arca inadvertently implemented a “regulatory halt” that stopped trading in the 134 Arca-listed securities on all exchanges.

4) NYSE and American Failed to Comply with Reg SCI’s Business Continuity and Disaster Recovery Requirements. From November 3, 2015 through November 23, 2016, NYSE and American were in violation of the requirements in Rules 1001(a)(1) and 1001(a)(2)(v) of Reg SCI that each SCI entity have policies and procedures reasonably designed to ensure operational capability.

5) NYSE and American’s Rules Failed to State That Pegging Interest Orders Created Possibility of Detection of Prices of Non-Displayed Depth Liquidity.

While we have noted many examples in the past about information leakage by the stock exchanges, this is the first time that the SEC has fined an exchange for leaking confidential client information:

– Floor brokers were permitted to enter “pegging interest” orders (PI) which allowed them to peg their order to the best NYSE quote. They could specify a range of prices for this PI order to be active. If the best NYSE quote was outside the PI range, then the PI order would price at the next level closest to the quote.

– According to the SEC, “A PI’s ability to peg to the price level of a NDRO (non-displayed reserve order) created the possibility that a floor broker, or a customer who submitted a PI through a floor broker, that sent the PI, would be able to detect the presence of same side non-displayed depth liquidity if certain circumstances were present.”

***Notice that the SEC says “a floor broker or a customer who submitted the order through a floor broker”.  This is because it is widely known that some HFT firms rent out the pipes of certain floor brokers and route orders through them to gain parity which is a benefit that floor brokers enjoy.

– PI orders could peg their price to a non-displayed NYSE order that was not part of their best bid or offer.

– The SEC explained how the initiator of the PI order could find out about hidden interest: “the submitter of the PI could potentially use identifying characteristics of its PI to locate it in the market data feed displayed at a price that did not previously have any displayed liquidity (because the NDRO was undisplayed), and if so located, conclude that there was same side non-displayed depth liquidity at that price level.”

NYSE was notified of the information leakage issue in 2013 by a client and chose to do nothing about it.  According to the SEC, “in 2013, NYSE received a complaint from a trader that the price levels of his NDROs, which were entered at prices inferior to the quote and unoccupied by any displayed liquidity, were being joined upon entry, as the trader observed in the exchange depth of book market data feed, by a displayed order.”

Apparently sensing that they had a problem, NYSE submitted a rule change in March 2015 which “modified the functionality of PIs so that they only pegged to price levels occupied by displayable interest.”  The SEC approved this rule change and didn’t appear to take any further action.

What made the SEC go back and take another look at this issue?  It looks like our old friend Haim Bodek was responsible for this with another whistle blower case. According to this press release, Haim continues to protect investors and haunt the exchanges.

Themis Concludes: The question now becomes what do we, as investors and clients of NYSE, do about this?  Should NYSE simply get away with neglecting their regulatory responsibilities?  Should they be able to pay the $14 million and just continue doing business like nothing happened? Or, should issuers and long-term investors shift their business to an exchange like IEX which seeks to protect them and not favor one class of client over another?

MODERNIR EDITORIAL NOTE:  Thanks, Joe and Sal! Issuers, you should expect honest markets free of predatory practices that distort your stock price and create risk. Two of the instances producing fines occurred in the summer of 2015 when ETFs nearly imploded. The stock market is overly dependent on intermediaries that during crises may vanish.  By then it’s too late.  We need an Issuer Advisory Committee for markets.

Machination

“It’s like the market has become some uncontrollable machine lurching around,” said friend Pat at the NIRI Rocky Mountain chapter meeting last week.

I spoke there about Exchange Traded Funds and how they contribute to market instability through the slow adjustment of collateral for creating ETF shares and the very rapid setting of prices for stocks and ETFs. If you want the presentation, send me a note and I’ll share it in pdf.

But first, breaking news from Steamboat Springs: Ski conditions are superb and you can snowshoe in deep champagne powder atop Rabbit Ears between the Yampa Valley and Grand County. We took in WinterWonderGrass too, mass musical ode to banjo, mandolin and upright bass. Blurring genres and maybe the event’s best was Fruition. They might be giants.

Back to Pat’s point that the market seems like a giant robot with the humans inside desperately fiddling with buttons and levers as it swings around destroying furniture, wouldn’t that suggest something awry in the mechanics of the market rather than human irrationality?

While you ponder, the blame may be going unfairly to new SEC chair Jay Powell. Whatever he said to Congress yesterday, the markets had from 8:30a ET to read the text.

Maybe he blew the Q&A. He used the word “strong.” Durable goods were terrible and he thinks the economy can absorb more rate-hikes. GDP may come in lighter still for Q4 in today’s revision.

We’re casting about for rational explanations where there may be none. What you never seem to hear is an investor saying “the reason I sold Powell’s testimony is because of” blah blah blah. What you hear are investors trying to explain why other investors are selling.

What if it’s the machines?

In a terrific interview with the New Yorker last December, Jim Simons said, “I looked at the price charts and analyzed them, and they didn’t look random to me.” Simons, a mathematician, founded hedge fund Renaissance Technologies and is today worth $20 billion.

The firm’s flagship Medallion Fund has generated 80% annually before fees for almost thirty years. It’s size-constrained because big money can’t be moved quickly, and longer-term trading makes algorithms less useful. “It’s like the weather,” says Simons. The nearer in, the higher the certainty.

So think about that. Humans and their fundamental models are trying to produce returns years in the making – which is highly uncertain. Machines focus on the moment. A high-speed trader told me they think of stocks in real time as moving from 5s to 6s, or 6s to 5s. “Buy the 5s that are becoming 6s, and short the 6s that are becoming 5s, and never take your eye off the book – the money at risk.”

I can tell you we rarely see arbitrary scatterplots in the behavioral trends we track. There’s a mathematical symmetry everywhere that defies the idea of a random walk down Wall Street.

It would make sense if the rules required machines to set—wait a minute.  The rules DO require machines to set prices.

Every “marketable” order that wants to be the best bid to buy or offer to sell must by law be on an algorithm, a machine, so it can move fluidly around the market, much faster than humans can react.

The spreads are regulated, to the penny. The bid to buy can’t be higher than the offer to sell, nor can it be the same as the offer to sell.

That’s math. Machines can be programmed to adapt to rapidly changing prices. Simons told The New Yorker he “never overrode the model.”

And maybe that’s your answer. Nobody overrode the model.

So, then? First, investors and public companies have to stop thinking rational thought is responsible for all prices, and boards and management teams better know. Both investors and companies should become better at data analysis if they’re to compete with machines.

Second, there is irreconcilable conflict between humans focused on fundamentals and machines fixated on data patterns – and the machines have the advantage because the market has been handed to them by rules.

Third, should there be different markets for the two? We’ll have opportunity to grapple with that idea when next machines drive the market somewhere it wasn’t prepared to go.

Day to Day

Here in CO we can count on sun much of the time but we still watch the weather forecast.

It would be a real pain to drag the skis out and drive up the mountain only to find the resorts bereft of snow.  For one, it’s an hour and a half on I-70 through the Eisenhower Tunnel to Summit County and the Arapahoe Basin, Keystone, Breckenridge and Copper Mountain ski resorts (and double that to our fave, Steamboat).

“You could use social media, Tim.  You can have the resorts text you about conditions.  You can go to onthesnow.com, opensnow.com, coloradoski.com—”

Right, I know that. I’m making a point about dealing with things as they come without thinking about the future. What’s called living day-to-day.  Some of us might want to do that. Get away from the schedule, the rat race. But it’s not a life strategy.

How come we do it with stocks?

Let me explain. Investor-relations folks, for the moment I’m talking to you.  (Investors, listen and see how it applies.) This is typically what you’ll get if you ask an exchange what’s happening with your stock:

The stock opened just above the blah blah blah level then broke out to the upside before basing around noon as profit-takers took over. The bulk of the volume occurred in the morning hours. There was one block, the opening trade, and BAML led most actives (880k), along with Interactive Brokers (615k), GSCO (325k) and JPM (70k).  IBKR often handles retail while the rest generally trade for institutions.

I’m not picking on exchanges. I’m asking what this tells you? It’s the same information I was getting fifteen years ago. No comparative forecast, no indication of what behavior set price, no trends, patterns. It’s a narrative suggesting the day is an end unto itself.

This is lugging skis to Breck on a shorts and flip-flops day.

Compare to the oft-maligned weatherperson.  They’re not always right but they give reliable forecasts. It’s math.  The weather keeps changing but we don’t stop reading forecasts. Right?

Like the weather, the stock market is continually changing. And like weather it’s got measurable patterns because it too is governed by mathematical principles.

Patterns abound. We give Wall Street general expectations of financial trends and patterns through guidance. The Peloton stationary web-connected exercise bike we love gives us troves of trend and pattern data on our performances (sometimes to our chagrin).

I know executives love trends and patterns because they tell me. They like to know what’s coming because they’re people responsible for outcomes and it’s how they think. They appreciate seeing patterns behind price-moves.

We have your trends, patterns and forecasts.  If you’d like to see them, let me know.

The stock market isn’t a set of disconnected events one upon the next called trading days that begin at zero, crescendo, and conclude at a finish line. It’s impossible for everything material to investment behavior to wrap by 4:00 p.m. Eastern Time each day. There’s a pattern at work you can be sure. The average stock trades 13,000 times per day in 200-share increments (and the last price of the day is the 13,000th then).

I’ll share some patterns and trends to finish. Broadly, the key behavior the past week driving big gains and yesterday’s intraday volatility is Risk Mgmt – the use of derivatives to protect and leverage portfolios. Second is Passive Investment. That combination means ETFs are responsible (passive money, plus a risk-transfer effort by market-makers).

Options expire tomorrow through Friday. The Sentiment trend in the market is white-hot growth behavior slamming into a ceiling, based on past trends and patterns. Shorting is rising, intraday volatility is rising.

While the market has persistent upside fervor, near-term volatility is baked in via behavior and options-expirations regardless of a government shutdown. Trends and patterns show it. It may change again next week. That’s how the market works.

If you’re an observer it’s nice to know what’s coming. If you’re an investor, it’s very material to know patterns and trends because your money is on the line. And if you’re in investor-relations, it’s your job.  You don’t want to live it day-to-day. That’s not a strategy.

Evaluation

We’re in San Francisco at the NIRI meeting, warming up with winter coming to Denver and as summer carries airily on in stocks.

What metrics do you use to evaluate your own shares, investor-relations folks, or ones you own, investors?

I don’t mean fundamentals like cash flow, growth, balance sheet data. Those describe businesses. Stocks are by and large products.

If you bristle at that assertion, it’s just math. JP Morgan and Goldman Sachs have either outright said or intimated that about 10% of their trading volumes come from fundamental investment (our data show 13.5% the past five days). Implication: The other 90% is driven by something else.

This disconnect between how investors and public companies think about stocks and what sets stock prices is to me the root of the struggle for stock pickers and IR professionals alike today.

For instance, the winds are starting to whip around the regulatory regime in Europe called MiFID II, an acronym profusion that considers securities “financial instruments” and will dramatically expand focus on data and prices – two things that power short-term trading.

For proof, one expert discussing MiFID II at TABB Forum said derivatives are “ideally suited” to the regime because they’re statistical. And a high-speed trading firm who will remain anonymous here because we like the folks running it sees MiFID II as a great trading opportunity.

Back to the question: What are your metrics?  It might not be what you’re thinking but it appears to me that the metrics most widely used by investors and companies to evaluate stocks are price and volume. Right?

But price and volume are consequences, not metrics. Think of it this way: What if meteorologists had gone to Puerto Rico and surveyed the damage and reported back that there must’ve been a hurricane?

That’s not very helpful, right? No, meteorologists forecasted the storm’s path. They offered predictive weather metrics. Forecasts didn’t prevent damage but did help people prepare.

The components of the DJIA are trading about 27 times earnings, as I wrote last week. Not adjusted earnings or expected earnings. Plain old net income. It’s a consequence of the underlying behaviors.

By understanding behaviors, we can prepare, both as investors and public companies, for what’s ahead, and gain better understanding of how the market works today.

I can summarize fifteen years of studying the evolution of the US equity market: machines are creating prices, and investors are tracking the averages. That combination creates valuations human beings studying businesses would generally find too rich.

How? Rules. Take MiFID II. It’s a system of regulation that advantages the pursuit of price based on market data, not fundamentals. In the US market, stock regulations require an intermediary for every trade. That also puts the focus on short-term prices.

Then every day by the close, all the money wanting to track some benchmark wants the best average price. So short-term price-setters can keep raising the price, and money tracking averages keeps paying it.  It’s not a choice.  It’s compliance.

In the past five days, data show the average spread between intraday high and low prices is a staggering 3%.  Yet the VIX spent most of that time below 10 and traded down to 9!

How? Machines change prices all day long, and at the close everything rushes to the average, so the VIX says there’s no volatility when volatility is rampant. Since machines are pursuing the same buy low, sell high, strategy that investors hope to execute save they do it in fractions of seconds, the prices most times end higher.

But it’s not rational thought doing the evaluating.

The lesson for IR folks and investors alike is that a market with prices set this way cannot be trusted to render accurate fundamental evaluation of business worth.

What causes it to break? Machines stop setting prices.  What causes that? There’s a topic for a future edition!  Stay tuned.