Tagged: Stocks

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.

The Middle

Keep it between the lines, advises an old country song from my youth.

“Quast,” you say. “If it’s from your youth, drop the modifier ‘old.’ That’s a given.”

You’d be right. Yesterday was ghoulish, as my Halloween trick was turning 50. Dead in the middle between zero and a hundred. And so now that I’m an elder I can pontificate with more gravity. Or such is the hope.

The Federal Reserve wraps a quiet meeting today where no doubt much pontification by elders ensued, and the trick for the Fed is to keep it between the lines. I expect the Trump administration, if the next Fed head is current Fed governor Jerome Powell, hopes to hew to the middle. No rocked boats or roiled waters, is the thinking.

The stock market is the same. It migrates to the mean. So successful is the average in 2017 that we’ve not had a single short-term market bottom (I’ll explain shortly).

The Wall Street Journal’s list of international indices shows none in the red the last 52 weeks. Root through Bloomberg and you’ll find a few deep in the ranks. Qatar is down 20%. Pakistan, Montenegro, Botswana and Bosnia in the red. But losers are few.

In the deep green are the Merval in Argentina, up 62%, the S&P 500 in the US, 21%, and the Dow Jones Industrial Average comprised of plodding blue chips, up 29%.  Even economically beleaguered Venezuela (native son Jose Altuve guilds baseball’s Astros) should’ve told citizens to buy local stocks as they’ve rocketed 4,700% in a year.

I tallied data on DJIA components.  The average blue chip is trading at 27 times earnings, with shares up 90% the past five years, 18% per annum on average. Yet a survey of financials the past four years across the thirty shows average revenue DOWN 2%, earnings down 7%.

There are some strong blue chips. But money and market structure have distorted the valuation picture (where markets and the Fed dovetail). While we’re not wary, we know it’s true and there will be blood. We’re just in the middle where everybody forgets about cause and effect.

We use the ModernIR Behavioral Index to predictively meter short-term movement of money on a 10-point scale. Over 5.0, more money is coming than going.  Under it, the opposite.  Historically, over 7.0 was a market top predicting profit-taking the next 30 days, and under 4.0 was a near-term market bottom, a value signal.

The market in 2017 is in the middle. That’s a buy and hold market, yes. But it lacks value signals too. People are overpaying. Stocks in 2012 dipped below 4.0 on 41 trading days out of roughly 260 total.  In 2013, there were 31 market bottoms; in 2014, 22; 2015, 39, and 2016, 31.

In 2017, none. Zero. The ModernIR Behavioral Index was 3.5/10.0 on Nov 8, 2016, the last bottom (those who bought then correctly read sentiment!).

I’m glad the US economy is posting numbers many thought impossible – 3% GDP growth for consecutive quarters. It can deliver even better data.  But right now too much money is chasing too few goods.

There’s one source of blame: The Federal Reserve.  Other central banks influence money supply but there’s still just one reserve currency (all efforts thus far to change it notwithstanding).

Result: Picture a Cape Canaveral launch. The space shuttles now retired would blaze 37 million horsepower fighting off gravity. The Falcon Heavy from SpaceX lifts goods to the space station with power like 18 Boeing 747s strapped on and throttled up.

There is no floating economy in space where gravity doesn’t exist. A great gout of central-bank money cannot as with space travel blast the planetary fisc past the gravitational pull of debt and spending. It can only create a long comet trail of stock prices and real estate prices and bond prices.

We think we’re in the middle. And we are. But not how we suppose. We’re between.

The Shiller PE as we wrote last week is the second steepest outlier in its history. Fundamentals don’t match stock prices. Gravitational pull is coming. We’re nearer the edge than the middle, viewed that way.

Many have decried central banks for opening floodgates, claiming it would produce a monetary Katrina. I supposed it would be two years from when the Fed’s balance sheet stopped expanding in latter 2014. But the Trump Rocket took us to zero market bottoms.

What’s tripped up doomsayers is a misunderstanding of the middle. The space between actions and consequences can be long. What is the Fed getting wrong?  It’s keeping us in the middle. It’s eliminating winners and losers.

We’ve got to get out of the middle before the bottom of it drops out.  Jerome Powell, can you help?

Climbing Mountains

You’re welcome.

Had Karen and I not departed Sep 20 for Bavaria to ride bikes along the Alps, who knows what the market might have done?  There’s high statistical correlation between our debouchment abroad and a further surge for US stocks.

Stocks spent all of September above 5.5 on the 10-point ModernIR Sentiment Index. Money never paused, blowing through September expirations and defying statistics saying 80% of the time stocks decline when Sentiment peaks as derivatives lapse.

Were we committed to the interests of stock investors we’d pack our bags with laundered undergarments and return to Germany before the market stalls.

But is the market rational?

Univ. of Chicago professor Richard Thaler, who won the Nobel Prize this week for his work on behavioral economics, is as flummoxed as the rest by its disregard for risk. While Professor Thaler might skewer my certitude to knowledge quotient (you’ll have to read more about him to understand that one), I think I know why.

Machines act like people.  My Google Pixel phone constructed a very human montage of our visit to Rothenberg, a Franconian walled medieval city in the woods east of Mannheim.  I didn’t pick the photos or music. I turned on my phone the next day and it said here’s your movie.  (For awesome views of our trip click here, here, here and here.)

Google also classifies my photos by type – mountains, lakes, waterfalls, boats, cars, churches, flowers, farms, beer.

Don’t you suppose algorithms can do the same with stocks? We have long written about the capacity machines possess to make trading decisions, functionally no different than my Pixel’s facility with photographs.

For companies and investors watching headlines, it appears humans are responding.  If airline stocks are up because of good guidance from United Airlines and American, we suppose humans are doing it. But machines can use data to assemble a stock collage.

The way to sort humans from robots is by behavior. It’s subtle. If I sent around my phone’s Rothenberg Polka, where the only part I played was naming it, recipients would assume I chose photos and set them to music. Karen would look at it and say, “Get rid of that photo. I don’t like it.”

Subtleties are human. Central tendencies like flowers and waterfalls are well within machine purview. Machines don’t like or dislike things. They just mix and match.

Apply to stocks. It explains why the market is impervious to shootings, temblors, volcanic eruptions, hurricanes, geopolitical tension. Those aren’t in the algorithm.

Humans thus far uniquely grapple with fear and greed. A market that is neither greedy nor fearful is not rational. But it can climb mountains of doubt and confound game theorists. What we don’t know is how machines will treat mismatched data. We haven’t had much of it in over nine years.

Acronym Techniques

The stock market is full of acronyms.

Last month, Chicago-based DRW bought Austin’s RGM. It’s a merger of fast giants – or ones who thought they might be giants (opaque musical reference) and once were, and might be again.

You see a lot of acronyms in the high-speed proprietary trading business. Getco became KCG, now Virtu.  HRT remains one of the biggest firms trading supersonically – Hudson River Trading.  TRC Markets is Tower Research. There’s GTS. IMC.  EWT is gone, absorbed by high-speed firm Virtu.

Vanished also is ATD, the pioneering electronic platform created by the founder of Interactive Brokers bought first by Citi and then by Citadel, another high-speed firm.  Mantara bought UNX.

If I missed any vital acronyms, apologies.

RGM embodied HFT – high frequency trading, another acronym. Robbie Robinette studied physics at the University of Texas. Richard Gorelick is a lawyer, and in today’s markets one of the letters of your trading acronym should be backed by jurisprudence.  It’s all about rules. Mark Melton wrote artificial intelligence software.

They were RGM. They built trading systems to react to real-time events. We estimate the peak was 2010. They were crushing it, perhaps making hundreds of millions.  By 2012 in the data we track they’d been passed by Quantlabs, HRT and other firms.

Donald R. Wilson in 1992 was a kid trading options in Chicago when he founded DRW. Today it’s a high-speed trader in futures across 40 global markets with 750 employees, real estate ventures, and a major lawsuit with the Commodities Futures Trading Commission that seeks to bar Wilson from the industry.  Oral arguments were heard in December and the parties await word. DRW confidence must be high. They’re a buyer.

What does it mean for you, investors and public companies? History teaches and so we return to it.

From the early 1990s when both Don Wilson and I were youngsters out of college (we’re the same age so what am I doing with my life?) until roughly 2005, software companies called “Electronic Communications Networks” pounded stock exchanges, taking perhaps half the trading business.

The exchanges cried foul, sued – and then bought and became the ECNs. Today’s stock market structure in large part reflects the pursuit of speed and price, which began then. The entire structure has become high speed, diminishing returns for the acronyms.

Exchange are still paying close to $3 billion in annual trading rebates, incentives to bring orders to markets. Yet the amount earned by high-speed firms has imploded from over $7 billion by estimates in 2009 to less than $1 billion today.

Where are dollars going? Opportunity has shrunk as everyone has gotten faster. Exchanges and brokers that are still the heart of the market ecosystem have again adapted as they did before, becoming the acronyms that ae disappearing.  They are Speed.

Exchanges are selling speed via colocation services, and the data that speed needs. And big brokers with customers have learned to apply high-speed trading methods – let’s call them acronym techniques – to offload risk and exposure when they’re principals for customer orders.

There’s nothing illegal about it. Brokers are free to transfer risk while working orders. But now they can make money not via commissions but in offsetting risk with speed.

And speed is the opposite of the way great things are created.  Your company’s success is no short-term event.  The Neuschwanstein Castle in Bavaria (which we will visit on our cycling trip in the Bavarian Alps later this month) took 23 years to complete.

Your house. Your career.  Your investment portfolio. Your reputation. Your relationships.  Your expertise. Your craft.  What of these happened in fractions of seconds? Technology should improve outcomes but more speed isn’t always better.

Acronyms of high-speed trading have slipped yes, but remain mighty – 39% of US stock market volume the past five days. Fifteen are still pounding pulp out of prices.

But increasingly investors are adopting speed strategies driven by quick directional shifts. We are exchanging patience and time for instant gratification.

With that comes risk. As the acronyms wane in ranks the chance of a sudden shock to equity prices increases, because prices in the market depend on short horizons.

And your stock is an acronym.

Hidden Volatility

Volatility plunged yesterday after spiking last week to a 2017 zenith thus far. But what does it mean?

“Everybody was buying vol into expirations, Tim,” you say. “Now they’re not.”

Buying vol?

“Volatility. You know.”

It’s been a long time since we talked about volatility as an asset class. We all think of stocks as an asset class, fixed income as an asset class, and so on.  But volatility?

The CBOE, Chicago Board Options Exchange, created the VIX to drive investment in volatility, or how prices change. The VIX reflects the implied forward volatility of the S&P 500, extrapolated from prices investors and traders are paying for stock futures. The lower the number the less it implies, and vice versa.

(If you want to know more, Vance Harwood offers an understandable dissection of volatility and the VIX.)

For both investor-relations professionals and investors, there’s a lesson.  Any effort to understand the stock market must consider not just buying or selling of stocks, but buying or selling of the gaps between stocks. That’s volatility.

It to me also points to a flaw in using options and futures to understand forward prices. They are mechanisms for buying volatility, not for pricing assets.

Proof is in the VIX itself. As a predictor it’s deplorable. It can only tell us about current conditions (though it’s a win for driving volatility trading). Suppose local TV news said: “Stay tuned for yesterday’s weather forecast.”

(NOTE: We’ll talk about trading dynamics at the NIRI Southwest Regional Conference here in Austin on Lady Bird Lake Aug 24-25 in breakout sessions. Join us!)

Shorting shares for fleeting periods is also a form of investing in volatility. I can think of a great example in our client base. Earlier this year it was a rock star, posting unrelenting gains. But it’s a company in an industry languishing this summer, and the stock is down.

Naturally one would think, “Investors are selling because fundamentals are weak.”

But the data show nothing of the sort! Short volume has been over 70% of trading volume this summer, and arbitrage is up 12% while investment has fallen.

Isn’t that important for management to understand? Yes, investing declined. But the drop alone prompted quantitative volatility traders to merchandise this company – and everyone is blaming the wrong thing. It’s not investors in stocks. It’s investors in volatility. Holders weren’t selling.

“But Tim,” you say. “There isn’t any volatility. Except for last week the VIX has had all the enthusiasm of a spent balloon.”

The VIX reflects closing prices. At the close, all the money wanting to be average – indexes and ETFs tracking broad measures – takes the midpoint of the bid and offer.

Do you know what’s happening intraday?  Stocks are moving 2.5% from average high to low. If the VIX were calculated using intraday prices, it would be a staggering 75 instead of 11.35, where it closed yesterday.

What’s going on? Prices are relentlessly changing. Suppose the price of everything you bought in the grocery store changed 2.5% by the time you worked your way from produce to dairy products?

Volatility is inefficiency. It increases the cost of capital (replace beta with your intraday volatility and you’ll think differently about what equity costs).  Its risk isn’t linear, manifesting intraday with no apparent consequence for long periods.

Until all at once prices collapse.

There’s more to it, but widespread volatility means prices are unstable. The stock market is a taut wire that up close vibrates chaotically. Last week, sudden slack manifested in that wire, and markets lurched. It snapped back this week as arbitragers slurped volatility.

It’s only when the wire keeps developing more slack that we run into trouble. The source of slack is mispriced assets – a separate discussion for later. For now, learn from the wire rather than the tape.  The VIX is a laconic signal incapable of forecasts.

And your stock, if it’s hewing to the mean, offers volatility traders up to 2.5% returns every day (50% in a month), and your closing price need never change.

When you slip or pop, it might be the volatility wire slapping around.  Keep that in mind.

Man vs Machine

If you’ve never been to Sedona, AZ in April, go but guard yourself because it will lay hold on your spirit and make it captive to unrelenting beauty.

How does the French election, yet unfinished, help US stocks?

Wait, no. It’s not the French election causing US stocks to soar, we’re told. It’s corporate earnings. Investors are loving good numbers.

Except investors didn’t set prices Monday when the market surged. Fast Traders did. The machines.

Saying the market is up because investors like Macron’s chances to win the French presidency reflects nothing fundamental. It’s an explanation fitted to an outcome.  Saying investors are gushing over corporate earnings is also finding a cause for an effect.

What data support the conclusion stocks jumped because people prefer the Frenchman Macron over the Frenchwoman Le Pen?  What data say investors are pouring money into stock because of strong earnings?  Earnings aren’t strong. They’re just better than weak results a year ago.

The data supporting those views, it turns out, is the market itself.  It’s up. So it must be that investors like something. The French election.  No?  How about US corporate earnings?  Market direction becomes a cause for humans, even when humans are not its cause.

Many suppose prices in the stock market can’t be set by machines. The opposite is true. Prices in the market can’t be set by humans. Under Regulation National Market System, it’s impossible for a human being to walk around the stock market trying to make a trade.

The rules say any “marketable trade,” a stock order wanting to be the best bid to buy or offer to sell, must be run by machines. Why? Because a human cannot keep pace with the market’s speed, and the order must be able to move fluidly to best price, So, the regulators said, it must be automated. Run by machines.

No matter where shares are listed, your stock can trade anywhere, from a private market operated by Credit Suisse, to the newest exchange, IEX.  The rules say simply that orders to buy and sell must move seamlessly to wherever the best price resides.

Well, humans devised machines with one purpose: setting price.  Humans themselves can set prices, sure. But they try to be in the middle, between the best bid to buy and offer to sell.  Yet we go on treating both events as though they are the same.

Understanding both the broad market and your own shares requires recognizing that while self-driving cars are a ways off yet, self-driving stocks are here now. When we all sit around talking about it, trying to find some rational explanation, we become weirder than the market. It’s as though we’re making excuses for the monster we crafted.

Since Fast Traders who want to own nothing set the pace, don’t be surprised if the pace disappears all at once.  And ask yourself every day: Are humans setting my stock price today, or is it the machines?  The answer is eminently measurable.

High Speed Risk

Is the era of high-frequency trading over? 

While you ponder whether “High Speed Risk” might be a good name for your garage rock band, let’s reflect on stocks. We said last week: “Our Sentiment is negative for the first time since the election. It’s a weather forecast.  No need for panic, only preparation.”

We measure the short-term movement of money with a 10-point scale. It was about 5.0 or higher from the election until Mar 9, 80 trading days. Last week it dipped below 4.5.

And weather arrived yesterday before today’s VIX expirations. It’s not news about the Trump administration.  It’s the end of a long, leveraged run. Monthly options and futures expired Friday the 17th.  New options traded Monday, Mar 20.

Yesterday was what we call Counterparty Tuesday. If counterparties have estimated demand Monday for new options incorrectly, they true up on Tuesday. Since markets fell, counterparties overshot demand.  

Derivatives have featured prominently in gains since the election. Investors have been buying both stocks and rights to more of them in the future. That additional implied future demand breeds higher current stock prices.

For the first time since the election, investors didn’t buy more future rights.  Does this mark an end to that pattern?  Certainly for the moment.  And it dovetails with the state of high-frequency trading.

For you new readers, let’s canvass high-frequency trading.  In 2007 after Regulation National Market System, a firm calling itself Octeg splashed through the data. In Intel alone, Octeg was driving 35% of monthly volume, crushing Goldman Sachs.

Who is Octeg, we wondered? The firm defied what we knew about brokers, which always wanted to hang a sign out, advertise that they had products for sale. We couldn’t find even a phone number for Octeg.  It was like stumbling on an unmarked warehouse in the suburbs packed to the ceiling with all the stuff you tried to buy at the mall.

While rooting through regulatory filings we found an address in Chicago and then another firm in the same suite called Global Electronic Trading Co (GETCO). 

And then we got it.  Octeg was GETCO spelled backward. The two were the same firm.

Getco dominated trading through the financial crisis, profiting on two ideas. First, exchanges began paying traders to sell shares on their markets. Think of it like a store coupon: Do business with us and we’ll give you a discount. Getco cashed coupons. In gargantuan manner. Exchanges paid them in coupons for relentless volume.

Second, Getco realized that it could be first to set price. So why not set as many prices as possible, forcing big institutions to chop their trades into smaller pieces?

Volume exploded. 

But it wasn’t investment.  Getco had no customers. It was using computers and mathematical calculations to continuously set prices in the stock market, getting paid to buy and sell stocks while simultaneously changing the price ever faster to force big investors into chopping up stock orders into smaller pieces so Getco and its burgeoning ilk could sit in the middle buying low and selling high in fractions of seconds.

At the pinnacle in 2009, we pegged this behavior, high frequency trading, at 70% of volume. Now high-frequency trading by our measures is less than 40% of volume.

The entire market the past decade is built on it. On the floor of the NYSE, four big high-speed firms price all NYSE stocks at the open. At the Nasdaq, a larger number does the same, trading prices for coupons.

The problem is high-frequency traders don’t have customers. They aren’t “working orders” for investors. They are buying low and selling high in fleeting fashion, for profit. Mistake these prices for ones from investors, and you mentally misprice stocks.   

You read that high-frequency traders are “market makers.” They’re “furnishing liquidity.” Traders with no customers can’t make markets. They can only exploit what others in the market don’t know. In 2007, it was easy. Now it’s not.

That’s because big stock brokers are doing the same thing with Exchange Traded Funds, rapidly repricing them, and index funds, and the stocks comprising them, and the options and futures derived from them. The big brokers are better at it than high-frequency traders because they have customers and can make longer directional plays by reading what customers are doing.

In a market without high-frequency trading, all stocks would trade like Berkshire Hathaway Class A shares.  About 400 shares daily.  It would be better for investors. But all the exchanges would go broke. Ironic, isn’t it?

High-frequency trading isn’t done. But with the market we’ve got, the harder it is for high-speed machines to price stocks, the greater the risk of big moves.

The Rising

Can’t see nothing in front of me. Can’t see nothing coming up behind. 

Those of you who know me know I would never write “can’t see nothing.” But Bruce Springsteen can get away with it.

He and the E Street Band put out the eponymous album on July 30, 2002, and it was appropriate for the stock market as the S&P 500 bottomed October 4, 2002 at 800 and proceeded with The Rising, traveling steadily upward to 1,561 by October 12, 2007. 

We didn’t return until Mar 2013, taking longer to get back than to arrive in the first place.

Now we’ve had variations on a Rising theme for eight years. The market bottomed this week in 2009, on Mar 6, at 683 for the S&P 500, lower than when our troubadour from Long Branch, NJ first commanded in gravel and guitar that we come on up for the rising.   

As with the last lyric in Bruce the Bard’s melody, it’s on wheels of fire that we’ve come rolling down here to 2017 in the stock market, blistering records and burning up the tape. 

We at ModernIR study equity data in our inimitable way, the cross of our calling, Bruce might say.  And that’s all the poetry I can muster.  But I’ve got some facts.

We measure Sentiment on a purely mathematical basis, tracking how the four big reasons people buy and sell interact with market prices and where these wax and wane.

We’re good at capturing short-term asset-price changes. We’ve been doing it for a long time. Our five-day forecasts are roughly 95% correlated to the actual average prices for stocks after the five projected days have elapsed – statistically interchangeable.  

Putting it in English, in short spans we can foretell the future, using math, because the money in the market is using math in ways we can observe with precision. 

Here’s what we know about market Sentiment and short-term prices. For 77 consecutive days now, back to Nov 14, 2016, the stock market has been about 5.0 or higher on our 10-point Sentiment Index.  Since June 2012, some 1,200 trading days, 715 have been 5.0 or higher. It’s been a bull market.  But ten percent are in a row since the election. 

Remarkable. (Aside: If you want to kick this around, catch me Friday at the NIRI Silicon Valley Spring Seminar.)

To our knowledge, the previous record for extended neutral or better Sentiment without a single tip to negative was 53 days, from Feb 22 to May 6 last year.  Back in 2013 when we had a momentum stock market, our Sentiment gauge would carom from below 4.0 to over 9.0 – a rocking Richter event – about every month. 

Here’s the thing:  When last year’s epic Sentiment run concluded in May, we were never able to rise sustainably again – until November. It required an extraordinary catalyst in the form of the Wildly Unexpected Donald Trump. The S&P 500 finished October 2016 lower than it wrapped May 2016. Even with another massive catalyst, the Brexit Boomerang, between. 

This is not scientific. It’s not fundamental. It’s not a factor model. But it IS mathematical, and it does reflect how money behaves today. Here’s my conclusion: Without an extraordinary event, a catalyst, when this long Sentiment run atop 5.0 stops, it will mark the end of this particular bull market. 

What’s a real-world application for investor-relations people? We track Sentiment for you.  When you’re Overbought your price will fall, absent a catalyst. When you’re Oversold, barring a tsunami, your shares will rise. It’s not rational. It’s math.  

You can use this data to your advantage.  When you’re a 10, call a couple of your good value holders to check in, because you’re likely to dip, and if your holder buys (you will be on their minds), you might revert to 5.0 quicker – and 5.0 stocks are the bedrock of solid investment portfolios. 

And vice versa. You’re 1.0?  Pick up the phone. The first investor to buy probably makes money (and will remember to look when next you call) and you’ll return to 5.0. It’s not what you say. It’s that you call that counts. Put yourself on the screen.

Won’t that work for the market? Sure.  At Feb 11 last year, the market was a 1.0/10.0. Great time to buy, turned out.  It was a Rising. 

We don’t know what’s ahead. Don’t know what’s coming up behind. But the math says we’ve had it good for a record stretch. It’s hard to keep setting records. 

Metrics

How many of you wear a Fitbit?

I remember the last time I saw Jeff Morgan, erstwhile NIRI CEO.  I said, “Jeff, you’ve lost weight. You’re a lean machine!”

He tapped his wrist, and said, “Fitbit. You can appreciate it, Tim. It’s just measuring data, right? Burn more than you take in.”

When we were roaming Barcelona last September, Karen’s phone was a cheering section congratulating us for achieving footstep goals.  Because there’s an app for that of course.

We’ve now bought a Peloton for our home gym, a finessed stationary bike replete with interaction and data. You can measure everything. You mark progress and capability.

On Friday the 13th the Wall Street Journal ran a story about online life insurance. Companies are using algorithms that parse lifestyle data from prescription-drug, motor-vehicle and credit-card sources to meter risk in place of testing blood and urine.

Data reveal facts about conditions. That’s the starting point. The next step is comparing data gathered in one period with the same metrics from another to see what’s changed. It’s what your doctor does.

And it’s the heart of financial reporting. We can debate the flaws of the requirement, but every quarter public companies are providing metrics to investors and analysts, who in turn model the data to understand business outcomes.

In fact, it’s the beat of the market. Every week data pours forth from governments and central banks on producer-prices and purchasing managers and jobs and consumer sentiment and on and on it goes.

I think it’s too much, promoting arbitrage on expectations versus outcomes. But think of the cognitive dissonance in our profession, investor-relations.  While everyone is measuring short-term, IR is trying to manage long-term. Yes, we want long-term commitment to our shares.  But that’s not how prices are set.

Unless you measure something the way it functions, you’ll get incorrect conclusions.

Much of the IR community isn’t measuring at all. We react. Right? The stock moves, and we call people for explanations.  How can answers be accurate without comparatives?  You don’t know what’s changed. No Fitbit is delivering data supporting conclusions.

The key to good management is consistent measurement. It’s the only way to understand an ecosystem and sort what you can control from what’s systemic.

Suppose I declare that I will float across the room.  Well, gravity, the rule governing the movement of bodies in this universe, says on this planet my pronouncement is flawed.

The gravity of the stock market is Regulation National Market System.  It defines how money moves from point A to point B.  We can observe those movements.

I showed a company yesterday how shares climbed from $60 to $70 during election week last November on Asset Allocation, and from $70 to $72 on Risk Management. That means ETFs and derivatives boosted shares.  Active money didn’t buy until the stock was at $75, even though it was selling the stock at $61 right before the election. Active money didn’t know what to do.

What followed? Fast Traders sold and shorted because the last fools to the party were the Active stock-pickers unaware of how the market works now.  No wonder many lag the averages.

If investors making rational decisions set the prices of stocks more than 50% of the time, the market can be called rational. Otherwise, it’s got to be called something else.  IR professionals, it’s your job to help management see the market realistically.

All the people talking about stocks are of a breed. The sea of money using models isn’t telling others what it’s doing!  But it’s setting prices.

You must measure now. What’s your Fitbit for the IR job?  Is it calibrated to the market we have today or one that no longer exists?

Case in point: I told a healthcare company recently that the data showed they would be unable to hold any gains until short volume were no longer consistently 65%.

“But our short interest is well below sector averages,” they said.

“That measure is from 1975,” I said. “It doesn’t reflect how the market works now.”

The stock dropped 8% yesterday and remains at the same average price it’s had since short volume rose over 60% well more than a quarter ago. The data – the Fitbit for IR – will tell them when conditions have changed.  Fitness can be measured in IR as it is elsewhere.

Measurement is management.  Put key metrics in front of your management regularly. Don’t wait to be asked for information – then it’s too late and you’ve lost control and become a glorified assistant (and they’ll define the job for you).

Create anticipation with metrics. “We’ve had a nice run but Fast Traders are leading, we’re Overbought, and short volume is over 50%, so expect some pressure next week.”

That’s what you should be doing.  Stop calling people for wild guesses unsupported by data AFTER something has occurred. Start measuring and setting expectations – especially around earnings, or events like options-expirations today through Friday.

You can only set expectations if you’re first consistently measuring and comparing key data points. This is evolved IR.  You can invent your own metrics. But we’ve already done that for you.

Verve and Sand

The whole market is behaving as though it’s got an Activist shareholder.

In a sense it does.  More on that in a minute.

We track the effects of Activism on trading and investment behaviors both before it’s widely known and afterward. A hallmark of these event-driven scenarios is behavioral volatility. That is, one or more of the big four reasons investors and traders buy and sell stocks routinely fluctuates day-over-day by more than 10% in target companies.

(Aside: Traders and investors buy and sell stocks for their unique characteristics, when they have characteristics shared by others, to profit on price-differences, and to leverage or protect trades and portfolios. The market at root is just these four simple purposes.)

Event-driven stocks can override normal constraints such as Overbought conditions, high short volume, or bearish fundamentals.  In fact, short volume tends to fall for catalyst stocks because the cost of borrowing shares rises as more want to own rather than rent, and unpredictability of outcomes makes borrowing shares for trading riskier.

Currently in the broad market, shorting trails the 200-day average marketwide. The market has manifested both negative and overbought sentiment and has still risen.

And behavioral volatility is off the charts.

Almost never does the broad market show double-digit fluctuations in behavior because it’s a giant index smoothing out lumps. With quad-witching and quarterly index rebalances Dec 16, Asset Allocation ballooned 16.3% marketwide, signaling that indexes and ETFs are out of step with assets (and may be substituting).

Also on Dec 16, what we call Risk Management (protecting or leveraging trades and portfolios) jumped 12%. It’s expected because leverage with derivatives has been pandemic in markets, with Active Investment and Risk Management – a combination pointing to hedge funds – currently leading.

Here’s the thing. The combined increase for the two behaviors last Friday was an astonishing 28%.  Then on Dec 19 as the new series of marketwide derivatives issued, Fast Trading – profiting on price-differences – exploded, jumping 25%.

A 25% change for a stock trading $100 million of dollar-volume daily is a big deal. The stock market is about $300 billion of daily dollar-volume.

Picture a skyscraper beginning to sway.

Looking back, Risk Management jumped 16% with July expirations, the first after searing Brexit gains. The market fell from there to September expirations when again behavioral volatility exploded. The market recovered briefly before falling all the way to the election. With expirations Nov 18, Risk Management shot up 11.2%.

Behavioral volatility precedes price-volatility. We have it now, monumentally.

What’s happened in the broad market is a honeymoon before the wedding. The incoming Trump administration has sparked an investing surge betting on a catalyst – exactly the way Activist investors affect individual stocks.  Fundamentals cease to matter.  Supply and demand constraints go out the window. A fervor takes hold.

The one thing our long bull market has lacked is fervor. It’s the most hated – and now second longest ever – bull market for US stocks because so many have loathed the monetary intervention behind ballooning asset prices.

That’s all been forgotten and a sort of irrational exuberance has set in.

Those who know me know I embrace in libertarian fashion broad individual liberty and limited government because it’s the environment that promotes prosperity best for all. I favor a future with more of it.

We should get the foundation right though. I’ll use a metaphor.  Suppose a giant storm lashes a coast, burying it in sand. Some return to the beach to rebuild homes and establishments but much lies listlessly beneath a great grainy coat.

Then a champion arrives and urges people to build. The leader’s verve lights a fire in the breasts of the people, who commence building a vast structure.

Right on the sand.  Which lies there still unmoved, a shifting layer beneath the mighty edifice rising upon it.

It’s better to remove the sand – all the central-bank buildup from artificial prices, the manufactured money, the warped credit markets.  Otherwise when the next wave comes the damage will be that much greater.

So call me wary of this surge.