“Let me tell you a wonderful old joke from communist times. A guy was sent from East Germany to work in Siberia. He knew his mail would be read by censors. So he told his friends: Let’s establish a code. If the letter you get from me is written in blue ink, it is true what I said. If it is written in red ink, it is false. After a month his friends get a first letter. Everything is in blue. It says, this letter: everything is wonderful here. Stores are full of good food. Movie theaters show good films from the West. Apartments are large and luxurious. The only thing you cannot buy is red ink.”

Great joke. No doubt scrutinizing your trading data to make sense of it is like something written in red, the code for which is blue.

Speaking of which, chances are, your earnings date is approaching. Your intraday volatility (spreads between high and low prices) is perhaps 4%. Across our client base, it’s now over 4% on average. To help you make sense of your stock price, the exchanges and designated market makers and surveillance firms are giving you columns of data on trading by different brokers and sector or economic news. They tell you so-and-so upgraded the sector, causing a strong rally.

You’re not sure. In your gut you think the euro has got a lot to do with it. Maybe the dollar. It would be nice to know. And it would help if you could assess how money will react to the news you announce next week or the week after.

There’s a lot you can know (don’t miss the Nov 3 IR Magazine Think Tank where we’ll discuss it). As much as we rant about the Swiss-cheese state of data for issuers in a gold-bar kind of world for speculators, your trading data in context of market rules is like an electrocardiogram. You can identify what generates the pulse and what’s driving fear and greed in the corpus of your equity market.

It’s a math problem (oh boy). I randomly sampled ten market structure reports for clients. In the past five trading days, Rational share of volume ranged from 10% to 16%, with an average of 12%. Speculative trading averaged 34%; Programs reflecting passive behavior were 29%. Another 24% went to risk-hedging and other things that don’t fit these buckets.

So if you are going to beat your active investors’ expectations on the call, and they consequently value your shares 5% higher, but programs for funds and models – asset managers – set your value 3% lower because of balance-sheet issues, what might happen to your stock?

It’s math. Programs are 29% of your market, so their pricing weight is twice the factor of rational investment. And if speculators have multi-leg straddles that pay off in cash if your shares move down, we can run a calculation that projects what will happen.

We are almost always within 1%. So we must be doing something right. If your stock were trading at $36 ahead of your call, we’d project a close at $34.81, with these expectations applied to outcomes.

How can this be? Markets are a maze of varying purposes and horizons following prescribed rules and order-types to match up as buyers and sellers. This mathematical maze can be sorted through a model.

Since rational investment is about 12% of the market, using data analytics to understand your trading – the same things the folks do who trade it to begin – is a good idea for the IR chair today. You know the 12%. You talk to them all the time. It’s the rest you need to get a grip on, so you can equip management with rational expectations.

We are willing to bet the sum total of wages for a large Wall Street demonstration that no surveillance firm or exchange can equip you with these answers.

June launched by kicking markets right in the rump. We blamed economic data. It’s true but not that simple. Behind the data at the behavioral level, institutions decided against equities roughly May 13. We don’t make this up, we just observe it in the way trades execute. When methodologies, purposes or time horizons change, it manifests in trade executions.

Money didn’t hedge with options expirations May 18-20 either. If you decide not to insure your house against loss, what might that mean? That you expect to sell it shortly, that risk is nonexistent, or that insurance is too darned expensive. As an analogy, two of those three are negatives and the middle one doesn’t exist on Wall Street.

Here’s another example of behavioral signs. Russell indexes benchmarked against market caps on May 31. MSCI indexes for global quantitative diversification recalibrated the same day. What matters isn’t how they rejigger but what demand is reflected in algorithmic and speculative trading. Demand was terrible. Brokers overestimated demand and so shed excess shares June 1, crushing broad measures.

While bad economic data are a root cause for institutional wariness, it’s not that money woke up Wednesday June 1 and said: “Holy gray underwear, Batman, the economy is lousy!”

Every day, the collective We in the USA and the globe round take various economic temperatures. We watch retail sales reports, oil inventories, speeches by Fed rulers. We check jobs numbers. In our businesses we’re measuring cash flows, sales channels, balance sheets, income statements. We monitor our health with physicals and checkups (We just battered ourselves Sunday riding Elephant Rock).

Why would it be odd to do that with our traded shares? We in IR sometimes pay lots of lip service to market-structure stuff, but we still BEHAVE as though fundamentals are the only price-setting force. The best of the best in terms of rational investment behavior across our client base registers investment at about 16% of daily volume. If you don’t measure data and behavior, you won’t know what’s setting your price.

That’s what we do. We’re sort of the Redbook of stocks, the Fed survey of trading behaviors. We’re assessing different purposes and time horizons behind trading activity to provide a realistic, three-dimensional view of the health of your trading environment, and the role of investment versus noise or risk-management in setting price and driving volume.

By the way, we saw a marked increase in Speculative “over-valued” signals in trading last week for clients. It’s observable mathematically.

We’ll leave you with a scintillating market-structure tidbit. We saw a particular Asian bank program-trading a great number of securities the past three days. It could be that easing done around the Japanese earthquake in which yen were deployed to purchase securities and stabilize markets might now be reversing out.

Behaviors are the best measure of purpose. Life and trading do not happen in vacuums, and the IR pro who knows has a valuable advantage. It’s good to be cool in the IR chair. See you at NIRI!

First, these markets. Real, or more statistical arbitrage? Checking the data, something very unusual occurred last week. On November 4 in our data, the volumes we call electronic and speculative were dead, spot-on, even, at 35.8% of the total, each. That day, divergence in major market measures ceased, and volumes turned bullish. It stood out to us.

Now maybe it’s coincidence. Or it may be that risk-management systems that statistical arbitragers had rocking like a boat twice last month found harmonics. Think of a guitar string coming into tune and your music teacher nodding approval. You may think this stuff is so much financial balderdash. Well, it’s responsible for a very great portion of daily volume. So don’t brush it off like dandruff. But bottom line, money felt more confident, and it showed up on electronic platforms, not in programs. But it’s more like betting than investing.

In general, we’ve observed a return to normal market structure across the bulk of our client base. Twice in October (Oct 1-2, and October 28-30) markets were in danger of swinging wildly out of whack, but healed themselves. It’s disconcerting that it happened twice so quickly. It’s comforting that it happened. Still, market structure is in constant flux. A graph can turn positive for a few days and then develop instant weaknesses. This happens for one undeniable reason: trading is reactive, not committed. That condition remains a deep-seated threat that regulators seem not to recognize.

You might gather now that “tail risk” has something to do with hedging. Vineer Bhansali at PIMCO funds, an expert on tail risk, says it’s “risk posed by rare events.” How institutions manage for these outliers on the edges of bell curves – tail risk management – affects vast clusters of equities.

Now, stay with me, IROs. What we’re getting to here is another reason why your stock may lack staying power on good results or news, seeming instead to constantly fluctuate. Bhansali explains that traditional risk-management techniques often fail to accurately estimate the frequency and size of “left tails,” or catastrophic events. Since everybody is acutely aware of bell curves and trend following, and not wanting to be the one who lost the institutional jewels to a bad hedge, we find that trading stays in the heart of bell curves and spends less time playing around the edges of the curve where the tail can lash left suddenly and leave you in the soup line.

So part of what happens is this: your results produce an immediate stock bounce, followed by an immediate retreat, as everybody supposes their investment is in the middle of the bell curve now, and it’s time to take profits. This is a new phenomenon. It did not exist a year ago, before Lehman’s demise. And if Lehman and all the rest had in fact demised as they should have, we probably wouldn’t be experiencing this phenomenon now.

All hedging reflects value uncertainty. When it occurs every other day, the degree of uncertainty is so great as to constitute an almost complete absence of any certainty at all.

That’s meant to make you chuckle. How do we fix it? U-turn back the other direction, away from whatever we’ve been rushing at for a year, like a vortex down a drain. And by the way, this does not mean markets will falter. We can continue on for some time. But sooner or later some little tail will flick left, right in the heart of the bell curve. And no one will be expecting it.