It’s a decent name for a rock band, yes. But it means “what stuff can you do with this?”

Traders want actionable data – something to drive opportunity for profit. Investor-relations professionals want actionable tools – something that’ll improve stock ownership, share price, results of IR effort.

Knowing who owns your stock is good. But what actions can you take? Talk to sellers? That’s uncomfortable. Plus, unless you’re screwing up, selling is a compliment, an investment objective. The sellers should well buy again, when the time’s right.

How do you know the time’s right? Ownership and targeting data are fine but limited if you don’t know who or what is controlling your liquidity. Without knowing your trading behavior, it’s difficult to accurately measure actions, plot outreach, and target investors.

Money won’t simply take a flyer because you run a good business and your IR team is suave and debonair. Today, institutions cannot afford to buy stocks in a vacuum, without respect to how the first 1,000 shares alter baskets, ETFs, derivative trading tactics and all the rest swirling around your liquidity. Institutions mind risk-management obsessively now, which is about market structure.

We track data for a living. For clients, we graph volume from prop traders like RGM Advisors, against, say, executed order flow for Credit Suisse. We observe how the behaviors of the two are eerily similar in some issues (and not in others). RGM is a scientific, machine-learning trader.

Say you’re using Credit Suisse for support on a non-deal road show, but most of their volume is trend-driven. That knowledge should inform what investors you ask Credit Suisse to bring from its client ranks. You’ll want high-turnover GARP or growth money, because that’s the kind likely to wade into a mathematical market. It can be a win-win – Credit Suisse likes those customers, too.

Market structure can shape who you choose for support. Some firms have high-turnover clients because their trading products facilitate high-speed trading. If you’re after a different investor-class than what a sellside firm tends to serve, you might use a different firm with a lesser trading operation – and thus more dependence on its research. Great story isn’t enough. If your market structure doesn’t suit the money you’re targeting, you’ll waste a road trip.

IR professionals should become more tactical. Use the big picture to do it – beyond story, to structure. The final frontier for IR effectiveness rests on the actionable quality of market-structure data. Do you know how much of your daily volume is speculation? What kind of investor should you target tactically, in context of your IR strategy, if more than 50% of your volume is arbitrage? These are important things to know now.

Here’s a product announcement from Direct Edge yesterday:

ACK – SPX Accelerated Return Notes due September 30, 2011

CDK – SPX Capped Leveraged Index Return Note due July 27, 2010

ELD – WisdomTree Emerging Markets Local Debt Fund

MHM – SPX Market Index Target Term Securities due July 31, 2015

As products like these roll out each day, there’s something else for that money you’re meeting in Chicago to choose besides you. Kick it up a notch. Target more tactically. Sometimes you’re right for high-turnover hedge funds. That alone is a new notion. Then, be ready, using market structure as guide, to get on the radar of conventional fund investors before hedge funds rotate.

It’s not an exact science. But these are tools with abundant actions. If you’re expert in your own market structure, your results are going to be different from those of other IROs, because you’ll think differently about what actions you need to take.

You’ll be the IRO for the 21st century.

That’s the essence of conversations I had yesterday with two investor-relations officers. It’s tempting to suggest asking Al Gore about why things that should be up are instead down. But that’s an old joke. And it won’t make you more valuable in the IR chair.

What will enhance your value is knowing what to tell the CFO and how best to do it. Whether you provide a daily, weekly or quarterly update to management about factors behind your stock price, you should incorporate comments on your market structure. Not just the old conventional stuff.

Think of market structure this way. If you operated a retail store, and each week you summarized the state of things in your store for headquarters, you’d talk about financial performance, products moving off shelves, the traffic driving sales, and trends. Something like that, anyway.

Same with your stock’s “market structure.” There’s only one product, your shares. But otherwise, you’re assessing behaviors and measuring them to understand how your store serves its market. If you measure only one behavior or one group of customers, that’s not an accurate picture of what’s happening, and it’s bound to lead to head-scratching and questions like, “How come our stock is down when it should be up?”

What do you tell your management team about market structure? Well, say you’re providing a weekly brief on trading activity. First define your metrics – the things you’ll track. For a weekly report, you don’t want to bury them in mind-numbing data. You want a small set of consistent measures. Begin with things like the percentage premium or discount in your closing price for the week versus the trailing 20-day average price. Volume versus 20-day average. Daily average trades and shares per trade, and daily dollar flow – that is, average daily price multiplied by average daily volume.

In time, you can provide a forward-looking expectation from data – but you must accumulate metrics first. As your management team becomes accustomed to market structure information, move to simpler but more compelling information, derived from your data: What’s setting our price? What do investors think? What are traders and risk managers doing, as opposed to what investors think? What’s likely to happen to our price next? These conclusions are extrapolated from data.

Before you know it, you’ll own your market structure. You’ll be the expert on matters related to your trading. This is the first step in a larger process of making a home for market structure in the IR department just like corporate governance has become an IR bailiwick.

Why must you own your market structure? Because roughly 90% of volume today BEHAVES either according to market risk or in response to speculative opportunity, and only a small amount is rational, or seeking long-term returns. If IR spends 90% of its effort on 10% of the market, well, at least something should be known about the rest. Or else, how can you draw accurate conclusions about stock performance, or even investor sentiment?

It’s up to IR to set that agenda and drag management kicking and screaming into the 21st century of how trading markets work.

To conclude, a challenge for you IR readers: Look up the DXY – the dollar index futures contract – and compare it to the Dow Jones Industrial Average, over, say, the past year, or the three months around the May 6 Flash Crash. What does it show you?

Speaking of waking up, did you read Sebastian Mallaby’s article in the weekend Wall Street Journal called “Learning to Love Hedge Funds?” Going back to the first hedge fund in 1949, run by Alfred Jones, Mallaby contends that hedge funds represent the optimal risk-management model.  Government tries to prevent bad things from happening. Hedge funds, where owners put their money at risk and earn returns when profits are produced, view risk as a pathway to opportunity, but one marked by prudent insurance, or hedges, against downside.  Jones produced cumulative returns of 5,000% from 1949-1968, Mallaby notes.

We’ve long contended that the contemporary IR relationship palette should reflect a variety of hedge funds and turnover timeframes. In markets predicated on the making and taking of liquidity and the constant re-allocation of risk and capital, focusing only on buy-and-hold investors is like offering a Monet to a Jackson Pollock collector.  You’ve got a nice product for the wrong buyer.

That leads to current markets.  Let’s talk again about “high frequency trading.” During a panel on trading at NIRI last week, Liquidnet’s John Adam, always an outstanding panelist, mused that “the only thing everybody agrees on about the definition of high frequency trading is that it’s trading at high frequency.”

Great assessment! There’s a bewildering variety of means and methods today by which parties large and small using networks both discrete and diffuse engage in the rapid putting and taking of shares for profit. We shouldn’t mistake it for investing. 

Here’s an analogy.  There are trillions of dollars moving through global markets.  Consider it a barge on land that must be scooted across the ground. If you’re moving a barge overland, you’ll roll it on logs, pulling the last one in the line and putting it in front and continuing to motivate the barge along.

In trading markets, everybody is moving logs now, from hedge funds, to exchanges, to institutions, to broker-dealers. The barge isn’t the best source of profit anymore; moving logs is.   Some high-frequency traders make money by collecting a fee for pulling the logs from behind and others for putting them into place at the front. Some profit by taking the logs from each other and moving them, and some by moving the logs faster than other log movers.  But it’s all intermediary service, for a fee.

While the mix of this activity varies widely from issuer to issuer, in general some 70% of volume is high-speed log-moving, and over 90% of volume is either speculatively driven – a form of intermediation or trading on gaps – or program-driven, which is managing the allocation of risk and capital.

People blame hedge funds for this.  Hedge funds would do the exact opposite, were they in charge of managing risk. These conditions we have now are what you get when you put government in charge of managing risk. What happens is that the best log movers become the most profitable enterprises. 

And you’ve got problems if the log movers decide not to move logs anymore. 

Speaking of which, we reiterate what we said last week. Despite strong market moves this week, we remain concerned that quantitative order flow might take sudden leave. Programs are responsible for positive performance since June 8. We can see it in the data. We cannot possibly predict what that means. But the allocation of risk and capital is transient today. That makes us wary.

Attendance jumped from last year. A few new firms joined the lineup on the boulevards in the exhibit hall. One first-time attendee working in corporate governance said as we sat by the fire pit Monday night and watched the party crowd and the live band and the oddity of the evening, a young woman rolling around on the pool in a giant see-through inflated ball, “You NIRI folks are the nicest conference goers I’ve ever met.”

Investor-relations types are people people. Who like to party.

There’s not a lot of partying in the equity markets yet. While the IR tribe whooped it up in San Diego, the markets didn’t. We’d expected better. We wrote two weeks ago that hedge resets on May 21 (think of them like climbing cams keeping you anchored to the rock face on Switzerland’s Eiger), signaled better things for a brief spell. But days later on May 26, something rippled portfolio trading schemes. Alert reader Eric Boni at Ashland Inc. said to us, “Could it be the MSCI rebalance?”

These rebalances and other forms of risk-management are often why markets seem schizophrenic. Last week on a similar jobs report to the one we got today the market kamikazes 300 points. Today, it’s up 2% so far. What gives?

There’s arbitrage, as we described last week. Compare big ETFs like QQQ, SPY and EEM, which track the Nasdaq 100, the S&P 500 and global emerging markets. You’d think they’d diverge more since they aren’t the same things. But with most trading behind them arbitrage, they look like each other instead of the segments they approximate. Or so it seems.

There’s also leverage. Back to MSCI. EEM, the ETF noted above, is an MSCI product in the iShares family bought by BlackRock from Barclays. It’s a $35 billion ETF that mirrors the MSCI Emerging Markets Index. MSCI was Morgan Stanley Capital International, a Morgan Stanley subsidiary that first created index investment products in 1969. In 2004, MSCI acquired Barra, Inc., a risk-analysis software firm, which combined to form publicly traded MSCI Inc. (NYSE:MXB), no longer affiliated with Morgan Stanley. In March this year, MSCI said it would acquire RiskMetrics, the risk-management and corporate governance giant.

Why are indices, ETFs, software, pieces of giant investment banks, and corporate governance rolled into one? Risk management is the biggest deal today. Yet investment managers must produce returns for clients. A white paper called The Perils of Parity from MSCI stuffed with terms like “empirical plausibility” and “derived conditions” explains that institutions have moved from allocating capital to allocating risk, and in so doing, leverage has become “necessary to achieve the expected return required by institutional investors.”

Suppose you met with investors and told them your growth story. But as you talked, the investors were thinking about how to allocate risk to you, not how to get a return from investing in your stock. That’s what software is doing today, and what these indices and ETFs are designed to do. So a bad jobs report last week in context of allocated risk was ugly for equities because the risk was allocated to stocks. This week, the risk is allocated somewhere else, and the capital gets allocated to equities. And the outcome is reversed.

Bottom line, you must pay attention to rebalances, IR folks, if only so you can talk briefly to the CFO about the difference between allocated risk and allocated capital. Next up on June 18, smack in the middle of options expirations, are the quarterly rebalances for the S&P 500, the Midcap 400, and the Smallcap 600. All of which have mirrored ETFs. And who knows where the risk and capital are allocated.

Maybe we need more swimming pools filled with inflated see-through beach balls ferrying flexible young females through happy partiers. It would make at least as much sense.

Speaking of power outages, starting April 22 equity markets developed voltage problems. IR professionals, we’ve got two words for when you meet the CFO in the hallway and she asks, “What’s up with the stock market?”

Risk Management. What two words did you think we were going to offer? “Risk Management” is why the same stocks that were up yesterday can be down today. We saw surging European and Asian inflows April 22, and a reversal of the same inflows on April 27.

From the IR chair, it’s flummoxing. Your nearest peer, in the same industry, about the same market cap, doing similar things, reports results on April 22 and beats expectations and soars 10% in a day. You then report the same good results almost pound-for-pound, a handy beat. And your stock declines three percent.

What gives?

Time for those two words: “Risk Management.” Large portfolio trading schemes such as pension and investment funds may hold an array of securities. Let’s say euro-zone bonds, currency futures, US Treasuries and US growth stocks. Suppose these investments are protected with risk metrics software from SAS, and trading-desk level systems from prime brokers JP Morgan and Deutsche Bank. These systems are designed to monitor and maintain portfolio risk and return within certain parameters.

Greece’s bailout is approved. The systems determine that this will strengthen the US dollar, thus weakening inflows to US equities from European and Asian sources. The systems themselves execute automated trades, complete with offsetting derivatives, to control risk.

This behavior causes a domino effect. The same securities the system said to buy last week are now the ones it sells. That triggers other limit orders and stop-losses, changes the nature and size of passive market-making trades, and attracts statistical arbitragers finding fleeting imbalances. And because ONE variable in the overall risk-management schematic is different – maybe a risk metric is the ratio of dollars on reserve at the European Central Bank, which has just returned a bundle of them to the US Federal Reserve – it over-corrects.

The next day, the system tries to rebalance the overcorrection, producing a spike in US securities again. Commentators bray about renewed enthusiasm for US economic growth, which in fact plays almost no role. Leveraged ETFs had just today adapted to yesterday’s big risk-management change. Now those are out of balance.

Suddenly, inefficiencies abound. Passive market-making systems aren’t getting liquidity to the right spots fast enough. Stat arbs are executing simultaneous offsetting trades in ten different market centers, creating the illusion of movement where none exists.

And the next day, the risk-management system tries to rebalance again.

This is how you get great volatility in markets designed to function smoothly and efficiently.

You don’t need to explain it in detail to your CFO. But you should be able to say, “We have integrated global markets. Our results, which were great for our active investors, now are secondary to global risk management. That’s the reason we’re under pressure. It’s a portfolio problem.”

But portfolio problems are our problems too. What’s the answer? We invite your suggestions. Meantime, be sure management doesn’t take it personally. It’s not always about you.

When I was a fresh-faced goofy college kid, my Logic professor, who was Greek and credible with his Hellenic accent, would say that a thing was theory only until you provided examples in the real world.

We hear that notion regularly. “So what exactly do you see with market structure? Give us some examples.” You asked. We’re doing it. We’ll aim to give you them regularly. Each will be an actual, real-world example, though the confidential nature of the data we track may preclude names.

As background, we’re clustering trading volumes behaviorally. It’s not quantitative analysis, which follows price and volume. It’s sorting out volumes with different time horizons and purposes to see which kind is prevailing. Often, price and volume change little, while behind the scenes tumult ensues among parties trading for different time horizons and purposes.

Here’s an example: Two large technology companies engaged in a bidding war for a third company. One of the two bidders was our client. There are three basic dimensions to market structure: trade executions driven by rational investment theses; trades for risk-management purposes based on changing market information, economic data or portfolio risk; and speculation in which traders take the other sides of trades, or sit between buyers and sellers to capitalize on short-term price movement or liquidity fluctuation.

Speculators are the truth-tellers about rumors and deals. If outcomes are uncertain, the parties most likely to know are the ones whose whole business it is to figure such things out. They’re not always right, but their batting average in our experience is over 80%. We pay attention.

In this instance, we saw 100% uniformity in speculators’ conclusions about the deal. How? They all did exactly the same thing. Literally no arbitrager questioned the prevailing sentiment.

For the IRO, that’s powerful data to present to boards and management teams. “Market structure indicates that the market universally expects us to prevail.” That says two things: Either your business and resources are more potent than your competitor’s, or you had better prevail or be prepared to suffer a high price. As a kicker, the IR team also could tell the Board and management that stock price was unlikely to change much at conclusion of the deal. Such was the outcome.

These are the things we see every day with market structure analytics.

Everybody’s got an opinion on why the market is yinning and yanging. We, I believe uniquely in IR, look at market structure first. That is, we see the trading data and behavior, and then from it we ask, “Why did that happen?”

Most everybody looks at what happens and infers that these are the causes for market activity. But, here’s the thing: money moves for three reasons today – investment behavior, speculation, and risk-management. It’s easy to get it wrong from the outside looking in. Thus, we think there’s greater accuracy in drawing conclusions from the evidence than in applying the evidence to your conclusion.

We saw a large rift form in the equity markets on February 2. Trading and investing activities were subordinated to risk-management flows. These are orders managed by software systems that respond to instructions and data about market risk. It may have been prompted by Greece’s problems. Perhaps American jobs data, or central bank woes in Argentina, where inflation was 17% in 2009. Maybe something else.

But that would be looking in from the outside. Inside looking out, here’s what happened: Systems executing orders for defensive reasons rose up in mass. It’s like a crack in the continental crust that squeezes out the stuff that forms mountains. Except here, it was risk-management volume – both buying and selling – that extruded from the rupture. When it ripples through nearly every issue like a fault line, you may be fairly certain it’s macroeconomic, not about your stock or story.

In fact, from the completion of monthly expirations on Jan 20, to February 4, we saw strong indications of risk management trading. It was similar to what we observed on October 1-2 last year, when the markets nearly fractured, and akin to the “healing” volumes in March and April 2009.

There are certain entry points where these volumes can be found. Among them is Goldman Sachs. When GS appears with large volume increases in 80% of issues (but you won’t see it in trading volumes), it’s a curious thing, and it affects all other behaviors. If you try to isolate whether it’s buying or selling, it’s impossible. All programs do both. So it requires seeing the activity in relation to other activities in order to understand what form of behavior has changed conditions in the markets.

Goldman isn’t alone. In fact, most times these volumes hit the markets through “sponsored access,” one of the activities that the SEC considers a gateway for exploitation. We don’t know if that’s true or not. We do know that in three different significant instances in the past twelve months, sponsored access has helped the markets heal.

We call these events “synthetic weaves” in the markets, stitching up a gash in the market structure. It leaves big question marks. Who’s behind it? Where is the money coming from? Why does it buy and sell seemingly unrelated issues en masse? Is it helpful or hiding a chasm ahead?

We can posit ideas in response, but who’s to say? We surmise, however, that economic data are secondary to the supply and pricing of currencies. And we can think of only one force with that sort capital capability.

Why does it matter? It’s a great way to clear the crowd out from around the water cooler. People quickly go quiet and start glancing at their watches when you let drop “synthetic weave in the equity markets.” Also, it helps explain why your business isn’t properly valued by trading markets.

A word on last week’s panels in KC (see Dick Johnson’s write-up at his superb blog) and NYC about modern trading: Had a great time in KC and felt we effectively explained how different time horizons and purposes, combined with lots of passive market-making, affect stock prices today. In NYC, it was a bit frustrating. We started in the middle and never got out of the maze. Sometimes the magic works, sometimes it doesn’t.

Speaking of the maze, you hear the term “program trading” often. Did you know that every other purpose for owning your stock may be overwhelmed by programs? It’s important to know their effect on your stock, and what’s behind them.

The NYSE defines programs as system-driven orders in 15 or more securities totaling more than $1 million. Every Friday, there’s a blurb in the Wall Street Journal on it, and Friday January 22, it was 27.6% of volume on the Big Board, up quite a bit from the week before.

We view program trading a bit differently because markets have radically evolved since the NYSE defined program trading that way. To us, managed, multi-day, multi-stock order-execution is program trading. Stripping out the jargon, we cluster execution by its behavior, and if it’s being managed to fit volume, and it’s happening over multiple days in more than one issue, it’s program-driven. We miss some, but not much. By our measure, program trading on the Big Board averages over 50% of volume, and a bit more than that on the Nasdaq.

This river of liquidity is the lifeblood of the equity markets. It balances out mutual fund inflows and redemptions, it rebalances ETFs and asset-allocation models and pension and sovereign-wealth funds, and it tweaks portfolios according to market risk. Just a few years ago, it had the flavor of investment value. That is, data on financial performance played a big role in its behavior. Today, those things take a back seat to market risk, an eyelid-drooping term that means “what can screw up my portfolio performance today?”

The markets have changed a lot. Shares for meeting the needs of these constantly swirling programmed waters are harder to locate. There are many intermediaries, and pockets of liquidity tucked into corners, and everything is affected by everything else. Morgan Keegan executes a sell order for a conservative investor in bank stocks, and over in tech equities, the trades trigger rebalancing in leveraged ETFs.

While any little thing can affect trading now (that’s a separate discussion), and high-speed, low-cost execution cloaks some massive inefficiencies in our markets when it comes to re-locating liquidity of any size at all, everything depends on the river. If we don’t have good, healthy program trading, the risk climbs for everybody, and prices move inversely to risk.

During expirations last week, we had a massive, program-led dislocation in the markets stemming from a steep rise in the cost of portfolio insurance, reflected in the pricing of various hedges. So money sold equities to reduce risk, and bought derivatives as insurance. Result: markets crumbled by hundreds of points. This is the truth. We can see it in the data. Anything else is peripheral to risk-management right now.

And here’s what keeps Ben Bernanke up at night, we surmise: half the volume in the equity markets is dependent on program trading. Most of that volume is driven by a handful of very large banks. Liquidity is now being withdrawn from the banking system. Mortgage-backed securities auctions, which have a big impact on other asset classes including equities in programs and which are led by the same banks, are ratcheting down.

If program trading starts falling, risks rise in the markets. This is a delicate balancing act for monetarists. And of course, if something other than supply and demand or buying and selling is setting prices, then the market isn’t really free.

I grew up in the Snake River Breaks northwest of Boise. In tiny Huntington, where I quarterbacked the eight-man high-school football team, a guy ahead of me several years achieved local fame at middle linebacker for the Boise State Broncos. BSU was I-AA back then, in the Big Sky league. Last night, it was great seeing the Broncos go 14-0, beating undefeated and 4th-ranked TCU in the Fiesta Bowl. The little big sky school has come a long way.

Speaking of a long way, here we are in Twenty Ten. What to expect this year? Lots of fun, of course! For those of us hovering about the gilded IR chair, it’ll be the year you create job security for yourself by knowing your market structure. The moment you start chattering about risk-management resets, you might see the eyes of execs glazing over – but they’ll be happy to pay you to know what you’re talking about! I’d say that’s worth looking forward to.

And will we here at The Map shut up about money supply already? Nope. You’ll hear more about monetary policy, because it’s the entire – yes entire – reason that neither the IR industry nor the global economy is really, in fact, growing. You cannot claim to have a free market and at the same time manage market outcomes with monetary policy. Nobody knows the value of things, then, and that’s really bad if you’re trying to create value.

Plus, Nature constantly changes. Capitalism is profitable adaptation to change. When the whole world is fixated on keeping some unfortunate event from ever happening again – trying to stop change – we are defying not only Nature, but the very thing that fosters prosperity and a vibrant IR profession – adapting to change.

As to what happens in the markets, nobody can predict the future. Money will continue to value your stock on the basis of use, with risk managers more powerful, investors less powerful, and speculators reacting to both. We track the behavior of money because IR folks now must be purveyors of knowledge, not just voices to investors. Knowing what’s happening, even if you can’t change it, is critical to IR value.

Differing ways money uses stocks is likely to result in continued broad equity appreciation, perhaps beyond 11,000 on the Dow. But like a bungee cord, markets stretched by elastic money supplies will contract. Period. Equity markets do still reflect the value of created things. Even if risk managers continuously tweak settings and speculators arbitrage movements. If we’re not creating things, and we’re gumming the gears of adaptive change with rules and hoops and do’s and don’ts in a bid to protect ourselves from the scary unknown, our equity markets will come to reflect moribund inertia.

Moribund Inertia isn’t even a good name for a rock band. So let’s change it.

If you wondered why your trading seemed odd that day, there’s a good chance it had to do with inscrutable black-box risk metrics run by major sellside firms helping the buyside modulate macroeconomic risk.

Oh, for the days when buyers and sellers set prices.

Volatility contracts expire tomorrow, Dec 16, and the usual index, treasury, currency, bond and other futures and options contracts cease Thursday and Friday the 17th-18th. Also, Christmas week, the S&P 500 futures, the SPL/SPX contracts, convert, and a new SPL series is added.

What do these mean to the IR job, and how do they work? SPLs and SPXs are options to buy or sell the S&P 500 index at future dates. They can be used as an asset for margin, as protection against risk, for trading volatility, for synthetically adjusting portfolios to mimic the S&P 500 without buying the actual elements – all kinds of things. How the market behaves around these expirations is like seeing the attitude of money rather than hearing the words it speaks.

Here’s the key: contrary to prevailing notions, derivatives are not an evil tool of wicked free markets. Derivatives are always an effort to deal with price and risk uncertainty. The more widely they’re deployed, the greater the risks and uncertainties. Risks and uncertainties are greatest in speculative markets and highly regulated markets. In both instances, the role of value in setting prices is obscured.

IROs and execs, these features matter. Imagine going up the down escalator. This is the nature of the capital markets at present. Too many factors are interfering with natural price-setting mechanisms. In order to explain what seems inexplicable about your share price at times, it’s necessary to understand how the value of money and the effects of risk-management work in equity markets.

We continue to say that the single largest problem now is Federal Reserve policy. Central bankers believe that the supply of money, which represents an exchange of value, can increase, even if there is no exchange of value. On corporate balance sheets, these conditions would result in a reduction to retained earnings, a dilution to equity, a writedown of asset values, or a journalizing entry affecting net worth in some way.

But that doesn’t happen in Federal Reserve policy. Inevitably, a bubble forms someplace.