Tagged: Trading

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.

Auctioning Profits

What’s the closing auction worth?

A member of the investor-relations profession last week posted a story for community discussion on a CBOE BATS proposal to open day-end auctions to exchanges that don’t have listings.

Right now rules say only the listing venue, largely the Nasdaq and the NYSE, can host end-of-day trades that many investors count on for prices that best track broad measures like the S&P 500 and Dow Jones Industrial Average.  BATS is trying to change it.

First, what’s the closing auction? Near the end of the trading day, exchanges that list stocks start providing data on buy and sell orders that want to get the last and best price.  All three big exchange groups host them – the NYSE, Nasdaq, BATS – and new entrant IEX has gotten tacit approval for its closing auction ahead of listings.

All three big groups have rules around what kinds of orders are included, but generally they are “market on close,” or a trade that takes the best price to buy or sell, or “limit on close” trades that only execute if the specified price matches the market.

BATS is the earliest in providing data and starts sending five-second updates on buy and sell imbalances at 3p ET. The NYSE and the Nasdaq follow at 3:45 and 3:50p ET respectively, also every five seconds.  Have you noticed how prices can change significantly in the last hour and especially last 15 minutes? There’s your reason.

Oversimplifying, right at 4p ET everywhere, buy and sell interest is matched at an average price. The NYSE calls it an auction, BATS uses a Dutch Auction (averaging all prices, excluding outliers) and the Nasdaq calls it the Closing Cross.

Now it gets interesting. This mass closing trade for NYSE stocks happens only at the NYSE and ditto for Nasdaq-listed shares.  BATS has proposed to the SEC that they be able to match trades in NYSE and Nasdaq stocks in the closing auction.

This at root is why exchanges want your stock-listing, public companies. It’s where the money is made.

The listing exchanges are outraged. Who can blame them? All the more when you understand the economics. Save at the open and close, trading at the exchange is a low-margin and often money-losing business.

They pay high-speed firms to set the best bid to buy or offer to sell. They’d flinch at my description but that’s the truth. Rules cap what exchanges can charge for trades at $0.30/100 shares.  But they can pay incentives well beyond that. The big exchanges have incentive tiers and platforms for high-volume customers paying up to $0.45/100 shares. They lose money on these.

Why would they do that? Because all trades in your stocks must match between the NBBO – the national best bid or offer. It’s a central tenet of Reg NMS, which governs markets. Exchanges pay some traders to be honey that attracts the bees.

The exceptions are the opening and closing auctions. Here, all the order flow ends up between the bid and offer by rule at some average price, and exchanges do not pay incentives because they have a monopoly in their listed stocks.

In fact, they charge about $0.09/100 to both the buyer and the seller ($0.18 total), meaning they make more in the auctions than any other time. Easy money.

Nearly 10% of trading occurs in the closing auction because it offers indexes and ETFs trying to “peg the benchmark” the best chance of getting prices nearest the index they’re tracking.

With about 6.5 billion shares trading daily marketwide and roughly 2.6 billion of it at the NYSE and Nasdaq, and 10% of that in the close, you can get to roughly $150 million of potential revenue annually for the big exchanges in these auctions. These are our estimates, mind.

But that’s not the half of it. Literally. Hosting the closing auctions drives two other vital revenue streams for big exchanges. First is a share of revenue from the Consolidated Tape Association.

The Tape Plan, as it’s called, divides revenue from data generated by stock tickers (you look up a ticker, you’re driving exchange revenue). It’s hundreds of millions of dollars yearly for members.  It’s apportioned by quote-share and trade-share in stock symbols. The closing auction gives the NYSE and Nasdaq a disproportionate part.

Second and data-related, prices from the closing auction comprise valuable data, and brokers are required to buy it to prove they matched best prices. The most precious product exchanges sell is data. And it’s vital to profits, since trading is a commodity.

The Nasdaq earned $108 million of net income in fiscal 2016, NYSE parent ICE, which is less reliant on equity trading, about $250 million. Take $250-$300 million (that they split) away – figuring data is double closing-auction trading revenue – by fragmenting the close, and the bottom line for both is hampered.

It’s an estimate. But follow the money and this is where it leads.

I can make the argument both ways. Fragmenting imbalance data by spreading the auctions out could mean mispricing. That to me is the leading argument against the BATS proposal.  Conversely, BATS would argue that it’s using the same pricing data so it merely increases access and removes an unfair advantage from listing exchanges – which could help you pay lower listing fees, issuers.

The bottom line is you need to know how the market works. Otherwise you cede control of it to parties wanting to profit on your prices.  That’s not in the best interest of your shareholders.

Volatility Insurance

In Texas everything is bigger including the dry-aged beef ribs at Hubbell & Hudson in the Woodlands and the lazy river at Houston’s Marriott Marquis, shaped familiarly.

We were visiting clients and friends before quarterly reporting begins again. Speaking of which, ever been surprised by how stocks behave with results?

We see in the data that often the cause isn’t owners of assets – holders of stocks – but providers of insurance. To guard against the chance of surprises, investors and traders use insurance, generally in the form of derivatives, like options. 

Played Monopoly, the board game? A Get Out of Jail Free card is a right but not an obligation to do something in the future that depends on an outcome, in this case landing on the “go to jail” space. It’s only valuable if that event occurs. It’s a derivatives contract.

At earnings, if you shift the focus from growth – topline – to value – managing what’s between the topline and the bottom line – the worth of future growth can evaporate even if investors don’t sell a share.

Investors with portfolio insurance use their Get Out of Jail Free cards, perhaps comprised of S&P 500 index futures. The insurance provider, a bank or fund, delivers futures and offsets its exposure by selling and shorting your shares. It can drop your price 10-20%.

Writers Chris Whittall and Jon Sindreu last Friday in the Wall Street Journal offered the most compelling piece (may require registration — send me a note if you can’t read it) I’ve seen on this concept of insurance in stocks.

Investors of all ilks, not just hedge funds, protect assets against the unknown, as we all do. We buy life, auto, health, home insurance.  We seek a Get Out of Jail Free card for ourselves and our actions.

In stocks, we track this propensity as Risk Management, one of the four key behaviors setting market prices. It’s real and by our measures north of 13% of total market cap.

But the market has been a flat sea.  No volatility.  This despite a new President, geopolitical intrigue, global acts of terror, a Federal Reserve stretching after eight Rumpelstiltskin years, and a chasm between markets and fundamentals.

Whittall and Sindreu theorize that opposing actions between buyers and sellers of insurance explains the strange placidity in markets where the VIX, the so-called Fear Gauge derived from prices of options on stocks, has been near record lows.

The thinking goes that the process of buying and selling insurance is itself the explanation for absence of froth. Because markets seem inured to threats, investors stop buying insurance such as put options against surprise moves, and instead look to sell insurance to generate a fee. They write puts or calls, which generate cash returns.

Banks take the other side of the trade because that’s what banks do. They’re now betting volatility will rise. To offset the risk they’re wrong, they buy the underlying: stocks. If volatility rises the bet pays, but the bank loses on the shares, which fall. 

This combination of events, it’s supposed, is contributing to imperturbable markets. Everything nets to zero except the stock-purchases by banks and cash returns generated by investors selling insurance, so there’s no volatility and markets tend to rise.

Except that’s not investment. It’s trafficking in get-out-of-jail-free cards.

And despite low volatility, there’s a cost. We’ve long said there will be a Lehman moment for a market dominated by Risk Management.

We’ve seen hedge funds struggle. They’re big players in the insurance game. And banks have labored at trading. Maybe it’s due to insurance losses. Think Credit Suisse, Deutsche Bank, HSBC.  Someone else?

From Nov 9-Mar 1 the behavior we call Risk Management led as price-setter marketwide, followed closely by Active Investment. The combination points to what’s been described: One party selling insurance on risk, another buying it, and a continual truing up of wins and losses.  

Now, for perspective, the VIX is a lousy alarm system. It tells us only what’s occurred. And intraday volatility, the spread between daily high and low prices across the market, is 2.2%, far higher than closing prices imply.

We may reach a day where banks stop buying insurance from selling investors, if indeed that’s what’s been occurring.  Stocks will cease rising.  Investors will want to buy insurance but the banks won’t sell it.  Then real assets, not insurance, will be sold.

It’s why we track Risk Management as a market demographic, and you should too.  You can’t prevent risk. But you can see it change.

Outliers

“Since I started Baron Funds in 1982,” said Ron Baron on Squawk Box last week, “we’ve owned 2,500 stocks. Take 15 of them out and we’re average.”

Baron is quintessentially rational. Visit Baron Funds and click on About and the words across the top are Long-term Investors. Research-Driven. No better proof can be found than that the director of research at Baron, Amy Chasen, was the IR head at Avon for years.

There are 36 fund managers and analysts at Baron overseeing about $21 billion of assets and the firm since 1982 has distinguished itself via patience and homework. Pick good companies and hold them for a long time. 

What percentage of the picks would you expect to be outliers – top performers? Maybe 75%?  The firm is looking for outliers after all. They’re not aiming to be average like Blackrock and Vanguard.

Okay, that’s probably a high expectation. Every time we demonstrate Market Structure Analytics to somebody new we expect there’s a 35% chance, based on the numbers we track, that that person will become a client, because we’re also patient and persistent.

So let’s lower our target for Baron.  Seventy-five percent is too high but you’d think stock pickers would be hoping they’re right at least half the time.  No?

You already know the answer: 0.6% of the firm’s stock selections beat the averages. That’s what 15 of 2,500 is.  The other 2,485 choices add up to average.  Now the good news for Baron is they don’t have to be right often to be good.

The bad news for IR is that using Baron Capital as our index of investor-relations outcomes, the likelihood that you’ll stand out from the crowd is less than 1%. 

“Oh come on Quast, what is this? The beatings will continue until moral improves?”

Oh ye pessimists, it’s the opposite.  IR is not just a storyteller.  IR is the product manager of the equity market.  If your management team thinks you have a 90% chance of standing out from the crowd and you lead them to persist in that belief, you’re creating a lot of needless IR stress. 

It doesn’t mean you stop trying of course. According to our illustrious trade association, NIRI, which at long last as a CEO again, 92% of public companies hold earnings calls (you wonder who the 8% are that don’t, and I’d love to know if they trade differently than the 92% — and my bet is there’s only about a 1% chance they do).  We tell the story because we must. 

But it’s high time IR adapts to the market we’ve got and it’s a lot like retail.  By that I mean the money isn’t one demographic, any more than the customers in Nordstrom are all one demographic group (they may share some characteristics sure, but they’re not all the same age or gender or height or weight).

And by that I also mean you all have high-speed pricing. Do you know that Amazon changes the prices of many items every 15 minutes?  They reprice with algorithms in response to online demand.  Well, now all the other retailers have had to adapt.  Walmart, Target, Best Buy and others may change prices 5-6 times a day now. 

I’ve got the Market Structure Report for a large food company here in front of me. It traded over 53,000 times daily the past week. Theoretically it could be a different price every time. The spread each day between highest and lowest prices averaged 2.3%. Add that up over 20 trading days and it’s 46% of the stock’s market cap.

Retailers are continuously engaging in markdowns to rid the shelves of “the dogs,” the stuff that’s not selling. And some hot new thing will come along and demand patterns change and retailers start lifting prices. It’s happened to me with hotels and airlines.  You too?

Juxtapose that with long-term research-driven investment and you see the problem. The dominant investment behavior of the day is Blackrock and Vanguard. They want to peg the averages of these continuously shifting notions of what’s a dog, what’s hot, what’s up, what’s down, or what’s getting continuously repriced in fractions of seconds.

And it appears they’ll be right 2,485 out of 2,500 times, or about 99% of the time. Over the past decade, 98% of active fund managers (and I think Baron was in the 2%) failed to beat the S&P 500, says Morningstar (Dec 2005-Dec 2015 but you get the point).  

The 20th century was all about active investment for IR, and telling the story, and as a result 92% of us hold earnings calls. But we’ve got to catch up to the market. 

Sometime over the next decade, 92% of us should be viewing ALL the money as the audience, messaging to some of it and consistently measuring the rest, like retailers do. We’ve got to be data analysts in IR.

Because we won’t all be outliers.

Open Water

If you want to be creeped out – and who doesn’t? – see the movie “Open Water.” It explains the problem with Board reports in investor-relations too.

American director Chris Kentis based his 2003 film on real events. A couple go scuba-diving and are left behind at sea.  He spent $500,000 making it and earned $55 million at the box office. That’s not the part resembling Board reports, unfortunately.

I don’t want to spoil the movie if you’ve never seen it, but I won’t because it’s a psychological drama depending not on action but implication that takes place in one spot on the sea.  Imagine you went scuba diving miles from shore and surfaced and everyone was gone and the current kept you out?

Now suppose as an investigator later it was your job to measure what happened to the couple. You had at your disposal film of the very spot on the ocean that the couple had occupied. You play back four three-month time-lapse slices of film at high speed.

Nothing. Open water.  It’s all you see. Sky whizzes by, days and nights are nearly indistinguishable, the sea appears as an unmarked surface moving across time.

It’s the wrong measure.  To understand what happened to the scuba divers you’d have to zoom in and watch spare increments.  Then you’d see – wait, there.  Are those specks in the water?  Sure enough, two people.  What are they doing?  Now let’s watch….

And that’s what’s wrong with Board reports.  They don’t measure the stock market the way it works. Executives have long strategic horizons and companies are generally benchmarking progress every quarter and looking at years of stock performance.

But your stock is like scuba divers bobbing on the water and your business is as timeless as the sea by comparison to what sets price. Blink.  Okay, blink again. That’s 350 milliseconds, give or take.  Many stocks trade 500 times in one blink.

No, don’t report to the Board every blink in your trading. But if we’re going to impart understanding – the point of providing information – of how shares change in value over time, the measures must reflect the way the ecosystem for your stock functions.

Your buy-and-hold investors have the same horizons you do.  But that’s not the money setting prices most days. Because it buys, and holds.

About 40% of the volume in your stock aims at horizons of a day or less, and generally just fractions of seconds to catch a penny spread a thousand times. Another 33% moves with the ocean, indexes deploying and removing money metronomically with a model. Another 13% or so pegs opportunity to instruments derived from your shares such as options, futures, forwards and swaps with horizons of days or weeks at most.

So just 14% of your market cap traces directly to your long-term strategy.

You say, “That cannot be true.”

In 2006, half the value of the housing market traced to real estate and the rest reflected rights to homes via mortgage-backed securities, and in some markets it was more than 80%. We know because that’s how much home-values declined.

On May 6, 2010, the Flash Crash, the Dow Jones Industrial Average lost a thousand points, or about 10% of its value, in mere minutes, because the money with tiny horizons disappeared from the market.

On August 24, 2015, some exchange-traded funds diverged by 30% or more from the underlying value of assets because money with horizons far shorter than the business strategy of any of the stocks giving them derivative value left. Briefly.

Those are outliers but lesser manifestations are a thrumming reef of vibrancy every day in your stock. At ModernIR, we measure price-setting in one-day and five-day increments because it’s the only way to see the scuba divers bobbing in the water – or the Activists, the fleeting shift in risk-management behavior reflecting deal-arbitrage, the evaporation of momentum, the abrupt drop in index-investment, the paired behaviors indicative of hedge funds coming or going.

Were we to paint stocks with bold brush strokes, the nuances responsible for price-changes would be as flat and impenetrable as open water. And meaningless to the Board and the management team.

The next time you ready information for the Board, think about the ecosystem, which is frenetic – in stark contrast to business strategy.  If nothing else, make sure they recognize that at any given moment, price depends on the 85% oblivious to strategy.

That might seem frightening, like sharks. Like the sharks it’s but a fact of the stock ecosystem, something to be understood rather than feared (and if you want to learn about the ecosystem, ask us!).

Core Reality

“Our stock dropped because Citi downgraded us today.”

So said the investor-relations chief for a technology firm last week during options-expirations.

For thirty years, this has been the intonation of IR. “We’re moving on the Goldman upgrade.”  “UBS lifted its target price, and shares are surging.” “We’re down on the sector cut at Credit Suisse.”

But analyst actions don’t buy or sell stocks.  People and machines do. Thirty years ago you could be sure it was people, not machines.  Now, machines read news and make directional bets. And why is a sellside firm changing its rating on your stock smack in the middle of expirations?

We’ll get to that. Think about this. Investors meet with you privately to learn something about your business or prospects somebody else might overlook.  Analyst actions are known to all. You see it on CNBC, in new strings, from any subscription feed.

How could it be uniquely valuable information proffering investment opportunity?

Let me phrase it this way. Why would a sellside firm advertise its views if those are meant to differentiate?  If you’re covered by 50 analysts with the same view, how is that valuable to anyone?

Indexes and exchange-traded funds track benchmarks. Call them averages.  Brokers must give customers prices that meet averages, what’s called “Best Execution.” If most prices are average, how are we supposed to stand out?

Now we get to why banks change ratings during expirations. Citi knows (Citi folks, I’m not picking on you. Bear with me because public companies need to learn stuff you already know.) when options expire. They’re huge counterparties for derivatives like options, swaps, forwards, reverse repurchases.

In fact, yesterday’s market surge came on what we call “Counterparty Tuesday,” the day each month following expirations when the parties on the other side of hedged or leveraged trades involving derivatives buy or sell to balance exposure. They were underweight versus bets (our Sentiment Index bottomed Monday, signaling upside).

Sellside research is a dying industry. Over 40% of assets now are in passive-investment instruments like index and exchange-traded funds that don’t buy research with trading commissions as in the old days.

How to generate business?  Well, all trades must pass through brokers.  What about, say, nudging some price-separation to help trading customers?

How?  One way is right before the options on stocks are set to lapse you change ratings and tell everyone.  No matter who responds, from retail trader, to high-speed firm, to machine-reading algorithm, to counterparty backing calls, it ripples through pricing in multiple classes (derivatives and stocks).  Cha-ching. Brokers profit (like exchanges) when traders chase spreads or bet on outcomes versus expectations.

We’re linear in the IR chair. We think investors buy shares because they might rise, and sell them when they think they’re fully valued. But a part of what drives price and volume is divergences from averages because that’s how money is made.

In this market of small divergences, your shares become less an investment and more an asset to leverage. Say I’m a big holder but your price won’t diverge from the sector. I get a securities-lending broker and make your shares available on the cheap.

I loan shares for trading daily and earn interest. I “write” puts or calls others will buy or trade or sell, and if I can keep the proceeds I boost yield.

I could swap my shares for a fee to the brokers for indexes and ETFs needing to true up assets for a short time.  I could sell the value of my portfolio position through a reverse repurchase agreement to someone needing them to match a model.

Here’s why traders rent. Say shares have intraday volatility – spread between daily highest and lowest prices – of 2%, the same as the broad market. A high-speed algorithm can buy when the price is 20 basis points below intraday average and sell when it’s 20 basis points over (rinse, repeat).

If the stock starts and finishes the month at $30, the buy-and-hold investor made zero but the trader capturing 20% of average intraday price volatility could generate $4.80 over the month, before rental fees of say half that (which the owner and broker share).  That’s an 8% return in a month from owning nothing and incurring no risk!

Let’s bring it back to the IR chair.  We’d like to think these things are on the fringe. Interesting but not vital. Across the market the past twenty days, Asset Allocation was 34% of daily volume. Fast Trading – what I just described – was 37%. Risk Management (driving big moves yesterday) was almost 14% of volume.

That’s 85%. The core reality. Make it part of your job to inform management (consistently) about core realities. They deserve to know! We have metrics to make it easy, but if nothing else, send them an article each week about market-function.