Friday, May 28, 2010

Fictitious liquidity

Now you see it; now you don’t

My last posting closed with “Neither liquidity nor transparency is a God, but there are aspects of both that are needed for markets to function.” Transparency was discussed in “The false God of transparency.” Now, it’s time to discuss liquidity. The definition is essential to understanding my use of “fictitious liquidity” in the posting on transparency. Further, it explains the rather counter intuitive reference to liquidity and volatility in the last posting. Since this is central to what has been said on this blog, this posting will address it in three ways: (1) textbook, (2) operational, and (3) practical.

For textbooks, let’s use INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT by Frank K. Reilly and Keith C. Brown as an example. After all, it is the textbook used to train many Certified Financial Analysts (CFAs) who become market participants. After discussing information, it defines liquidity as “… the ability to buy or sell an asset quickly and at a known price….”

It then goes on to define “price continuity” as a component of liquidity. It’s at that point that the discussion of liquidity gets telling. So, here’s the definition of price continuity “…that prices do not change much from one transaction to the next unless there is substantial new information available.” By making price continuity a component of liquidity, it ducks the question of whether information about liquidity is “substantial.”

That, as it turns out, is rather essential to the discussion of what liquidity is. Add price continuity, and one is no longer dealing with a concept. One is dealing with an objective. More importantly, from a behavioral perspective, liquidity becomes self-referential.

It also ignores the fact that money, for numerating trades, is not continuous. Is it saying “same price” in dollars, pennies, fractions of a penny?

It does say next trade; thus, defining time as whatever the market determines. That raises some questions: Is an asset liquid if it trades freely at the same price, but infrequently? Seems to me it could be boring, but liquid, but it could also be illiquid. Is the boring asset more liquid than an asset that turns over repeatedly each day but bounces around? Seems to me the textbook definition is just saying that it depends on how fast it bounces. It ducks the issue of clock time. As a consequence, it falls into the trap of implying instantaneous liquidity is necessary to liquidity. Liquidity has to address the issue of “by when” (i.e., time). Otherwise, the definition seems to be of little practical use.

Don’t get me wrong. I’m not disparaging what can be accomplished with continuous, instantaneous assumptions. Newton did some amazing things that advanced physics by working out how to use those assumptions. Besides calculus is fun for me; it creates an alternative universe all of its own. It has also facilitated some interesting and vital advances in finance and economics. But, eventually, one has to deal with the operational and practical.

The texts also incorporate the concept of depth. But, at this point we are really proceeding to what I’ve called the operational. Not surprisingly, it’s at this point the definition does get more substantive.

There is liquidity as in large pools of capital participating in the market. To my way of thinking, adding “a large numbers of counterparties” to the definition of liquidity without defining a legitimate counterparty makes the definition partially conditional. There is always some liquidity based on counterparties dependent on hedges. That generates counterparties without necessarily expanding the capital pool. It increases volumes that can be supported, but the increased volumes are ultimately based on leverage (i.e., larger volumes on the same capital base).

Arbitraging forward curve is a familiar illustration, but any form of statistical arbitrage or hedging strategy could do just as well. They illustrate the consequences of this fictitious liquidity. If the markets disconnect, the liquidity based on the arb can increase as the arbs place positions, but it can disappear if the hedge that allowed the leverage fails. In short, if the hedges fail, the difference between real and fictional liquidity surfaces. Thus, volumes only indicate liquidity under very specific conditions (i.e., if the hedges work). If my belief that there is no perfect hedge is correct, then failure is inevitable. It is this liquidity that I refer to as fictitious liquidity.

So, you ask: “Why is it fictitious? Just because it can go away, doesn’t mean it wasn’t real while it existed.” The issue of liquidity based on arbitrage or hedging isn’t new. It’s been discussed in the literature on financial markets. Terms like borrowed liquidity (i.e., liquidity borrowed across markets), and aggregated liquidity (i.e., combining the liquidity of two or more markets) have been applied. It has been celebrated as one of the breakthroughs of modern finance, and justifiably so. It increases the liquidity of each individual market.

Hedging and arbitrage would actually produce multiplicative liquidity if total liquidity were the sum of individual market liquidities. But, total liquidity isn’t the sum of individual market liquidities. Total liquidity would then be a product of total market activity. This is totally circular reasoning: liquidity makes trading possible and trading defines liquidity. That may be OK since the phenomena itself may be self-referential. But, the circular definition is one argument for calling it fictitious liquidity.

The liquidity could as easily be called leveraged liquidity. But, here’s where things get weird; to the extent hedges work, they cancel each other out. However, we have not canceled the liquidities across the markets. We accept that the liquidity is there as long as we believe it is there. Lose faith and unwind the hedge, and it is gone. So, I like fictitious.

“This is all terminology; how does it contribute to volatility?” One should remember the question about whether changes in liquidity are substantive information. That is the answer to how the usually stabilizing impact of liquidity can be destabilizing. Volatility isn’t about levels; it’s about change.

Economists are use to quasi self-referential systems. We talk of virtuous cycles and vicious cycles. But, economists, especially modelers, know that a specification that is self-referential can lead to an unstable or explosive model. One seeks to avoid models where the change in a variable is dependent on the level of the same variable or the change in the same variable, much less where the change in the rate of change is dependent on the change. The modeling solution is to build in mean reversion in some form or avoid self-referential specifications totally. That, however, doesn’t negate the fact that, to the extent liquidity is, in fact, self-referential, it produces a tendency toward instability (i.e., produces volatility).

Economists aren’t alone in having to deal with self-referential systems. In math, think chaos theory and fractals. For a pop culture example, think TIPPING POINT; HOW LITTLE THINGS CAN MAKE A BIG DIFFERENCE by Malcolm Gladwell, although it mixes in non-linear systems. Many disciplines (demographics, engineering, physics, evolutionary biology) have concluded self-referential systems tend to be volatile. So, we shouldn’t be too surprised if financial economics finds an example.

Now, let’s turn to the practical. In a practical sense, time is essential. For practical purposes, liquidity is the ability to move between assets when one wants. The assets may include money, often the focus of discussions of liquidity. Being able to move to the medium of general exchange extends the definition to include moving between investment and consumption. But, let’s leave the consumption/investment decision aside for now.

Once time is introduced, we need to have a practical definition of time. Time is never continuous in this context. Even at the nanosecond level it’s a bit on a computer. For someone trading fractions of a penny for fractions of a second, the units are very small. That’s fine if they’re basing it on the same information as other traders. However, if they’re trading between ticks, it gets downright dishonest. They remind me of the currency trader who took the ten thousandths of a penny dropped in accounting for foreign currency transactions, and deposited them in his bank account (he went to jail).

For other traders, seconds, minutes, hours, days, weeks, etc. are practical. For a person planning for retirement, multiple years could fit. A trade can be structured so that the practical definition is indefinite, good until canceled or executed, or good until unwound. Thus, a practical definition of time is very personal.

In practical time, price gaps (discontinuities) become a meaningless concept or just another way to say volatility. Once practical time is introduced, liquidity becomes the ability to exchange assets. Price disappears from the definition. That puts us at the mercy of supply and demand. What really exists is some number of buyers at each price and some number of sellers. Under this definition, buyers and sellers now define liquidity, but they will also determine price. Thus, by this definition, information about liquidity is “substantial.” So, under this definition liquidity is still self-referential and directly related to price.

This has implications for what people who retain the focus on price continuity mean. Essentially they’re saying they want the same price at transaction time as existed at some earlier point. There is no reason for the “same.” Buyers want lower; sellers want higher. There is also no reason for any specific time lapse. The more one is motivated to trade the shorter the time frame. It would seem the alternative definitions that incorporate price continuity are biased in favor of frequent trading. Since trading has a cost, it is legitimate to question the result from a capital allocation perspective.

Now a disclosure, I’m so comfortable with volatility that an observer might think I’m insensitive to its impact. I understand self-referential systems reasonably well, at least well enough to recognize one. But, that’s not insensitivity to the impact of the volatility produced by the self-referential nature of liquidity. The fictitious liquidity added to liquidity due to genuine counterparties (i.e., those willing to take a position in an asset) often adds to volatility. There is enough truth to the risk-equals-volatility logic to justify concern, especially since it influences the allocation of capital and even the capital formation verses consumption decision. I also recognize that many people don’t share my indifference. Further, some people are mislead into making bad investment decisions by their reactions to volatility. Other can trade it quite well.

Since volatility is a part of life, why single out inter-tick volatility (discontinuities) for special treatment. Gapping between ticks and between years is only different depending on whether the tick or the year is your trading time frame.

Sunday, May 23, 2010

Liquidity is dangerous

If I had a hammer, I’d hammer out danger, I’d hammer out a warning…With apologies to Peter Seeger & Lee Hays

The authors might take umbrage at using their lyrics (LYRICS - If I Had a Hammer) when discussing anything as crass as money. However, hopefully one doesn’t need a hammer to teach love between my brothers and my sisters. Maybe a bell and a song will do and they can lend me the hammer. It’s a little harder to teach a little financial common sense to powerful people with vested interests. Nevertheless, here’s some food for thought.

If, as the profs theorize, risk is price volatility and volatility requires liquidity, it is only a short hop to excess liquidity will produce excess volatility. But, volatility can be endured. There is a side argument that excess volatility discourages capital formation, producing a sub-optimal bias in favor of consumption -- an argument many profs overlook. But, that side argument isn’t what this posting is about. This posting is about a sub-optimal allocation of whatever capital there is. It seems I am not alone in noting that the blind pursuit of liquidity is compromising transparency and the market maker role of exchanges. I recommend reading " Stock Market Mayhem Confirms Need for Better Regulations - Barrons.com .

This is an excellent article. However, The Hedged Economist argued that the “flash crash” is not very mysterious (see: “The day the computers panicked” in PART 1 of a three part posting). Interestingly, I reached the same conclusion as the article about transparency and the blind pursuit of instantaneous and continuous liquidity (see: “The false God of transparency” the last posting). However, this blog broached the issue of how much liquidity is needed back on January 28 in “Efficient capital allocation doesn’t require perfect liquidity” in one of the first postings on this website.

Why the hammer? Because this is fast becoming a potential source of the next systemic meltdown. I can’t emphasize enough: efficient capital allocation doesn’t require perfect liquidity. It is time to add: efficient capital allocation can’t survive perfect liquidity if perfect liquidity requires sacrificing price transparency. Neither liquidity nor transparency is a God, but there are aspects of both that are needed for markets to function.

Tuesday, May 18, 2010

The false God of transparency

Are we seeking wisdom, a voyeuristic look at secrets, or dirty laundry?

Transparency is one of those things that seems to be inherently good. But, that’s really a superficial attitude that is, fortunately, tempered by the application of common sense. It ignores a prime question: What should be shown? I certainly don’t want to see many of my friends nude, for example. It also ignores both privacy and intellectual property issues. That’s an acknowledgement from this blogger who is usually interested in what others are thinking. However, an even more interesting issue is: What will result from transparency? It’s a fascinating issue because people often don’t seem to have thought about it.

Let’s look at privacy first. We’ll use a headline issue: the GS and Paulson’s trade discussed in the two postings on how “Sometimes Wall Street provides more entertainment than Hollywood.” It is unfortunate that this example is so convenient because people get quite irrational when GS’s name comes up. But, forging ahead, we’ll set the topic with a quote from a NY Times piece entitled "From Buffett, Thought-Out Support for Goldman.” (full story at: http://www.nytimes.com/2010/05/04/business/04sorkin.html?scp=1&sq=from%20Buffet,%20thought-out%20support%20for%20goldman&st=cse )


“One Berkshire shareholder who has been a regular in Omaha is Bill Ackman, an outspoken hedge fund manager who has made a career of railing against bad corporate practices. … In recent days, he has gone even further than Mr. Buffett in his defense of Goldman, suggesting it would have been unethical for the firm to disclose Mr. Paulson’s position in the Abacus deal. He says that Goldman, as the market maker, had a duty to protect the identity of both sides of the transaction.”

Think about it this way: If it was ethical for GS to disclose Paulson's position, then it should be OK for your broker to disclose your positions to potential counterparties. Similarly, should GS have disclosed to Paulson who was taking the long position? Very analogous reasoning would argue that brokers should be allowed to disclose to potential counterparties that a mutual fund or pension fund plans to take a position in a stock; after all, Paulson had not, and could not have, taken his position until someone took the counterparty position. People have gone to jail for doing that sort of disclosure. It allows front running.

My only disclosure is that I have accounts with multiple brokers so that no single broker or dealer can disclose all my positions or even my net positions. It’s a by-product of differences in what each offers in tools and investments. But, many financial institutions use multiple dealers specifically to avoid having their positions disclosed by any one dealer. Your pension fund or mutual funds probably do exactly that.

If one tries to set parameters for when privacy should be sacrificed, it gets hairy real quick. Think about exchanges. Exchanges suppress all information about counterparties. Theoretically, one’s counterparty is the exchange. Should exchanges have to disclose their net positions? Could they even do it given the volume and speed of trading?

Many market observers hold the position that derivatives should be brought onto exchanges; I’m among them. If one shares that opinion about exchanges, but simultaneously say that GS should have disclosed that Paulson was shorting the bonds GS was selling, the observer isn’t being consistent. The observer is advocating suppressing the very information they’re saying should be disclosed. On an exchange that individual counterparty information is suppressed.

The same logical inconsistency exists whenever a person trades on an exchange (where they don’t have counterparty information) while simultaneously maintaining the counterparty should be disclosed. Do you know who your last few trades were with? Probably not.

Transparency is desirable if it involves the right information. Otherwise it is distracting and can have major negative consequences. To illustrate, both postings on how Wall Street can be more entertaining than Hollywood point out that neither the winners nor the losers felt that the motives of their counterparties were important. But, it is relevant, and perhaps not stressed enough, that most people involved either didn’t want their net positions disclosed or were worried by how much was publicly known about their net positions. In fact, some of the people who were net short mortgage bonds abandoned the trade because they feared a short squeeze. The issue of short squeezes is a point often overlooked in the discussions of transparency.

However, the really dangerous oversight from the perspective of financial stability is the failure to address what should be transparent. The motive of the counterparty is not really relevant. If it were, exchanges would be irrelevant. What matters are: (1) Is the counterparty solvent (i.e., can the counterparty make good on the trade)? and (2) Is the trade at a legitimate market price?

Why is this dangerous from a systemic risk perspective? Exchanges face conflicting objectives. They were mention in a previous posting on this blog. They are sufficiently central to this point that the discussion is quoted below:

“The issue surfaced in an exchange between Duncan Niederauer, CEO NYSE Euronext, and Bob Greifeld, CEO Nasdaq OMX Group Inc. Greifeld’s contention is that the overall volatility in the stock was increased by the Nasdaq’s inability to provide enough liquidity to accommodate an orderly handling of the volatility. He doesn’t say it that way since blaming it on the NYSE is so much more consistent with his interests. But, that’s the bottom line of his position. That seems reasonable. When all the volatility risk is shifted to one market, that market will be stressed.

Niederauer’s counter that the purpose of the NYSE is to provide an orderly market. Can’t argue with that. But, under the circumstances he seems to be overly professional in not pointing out that Nasdaq didn’t deliver an orderly market.

Here’s where the verbal exchange gets interesting, and it betrays each man’s philosophy and the market they serve. Another function of an exchange is to provide liquidity. Clearly, when the NYSE moved to slow mode it traded off providing instant liquidity for orderly market. Who is served by each? People don’t even sense instant liquidity. The slower mode and even a pause for a few minutes would hardly be noticed. By contrast, computers assume instantaneous, continuous liquidity. Put bluntly, Nasdaq would accommodate computers at the expense of people while NYSE leaned the other direction.

Next step in the analysis involves the exchange’s role as a method of price discovery. Clearly, that is a key function of an exchange. Again, Nasdaq was willing to “execute” any trade without regard to whether the price discovery was being compromised in order to accommodate continuous trading. NYSE wasn’t. If one needs proof, it will come when trades are unwound as is being discussed.

Finally, an exchange acts as a clearing house becoming the counterparty. NYSE slowed trading to ensure it could fill that counterparty role. We will see whether Nasdaq honors all trades. This last issue goes to the heart of the issue of whether an exchange walked away from the market. Slowing trading isn’t walking away from the market; it’s slowing it. By contrast executing erroneous trades and then not honoring them is walking away from at least two important responsibilities of an exchange.”

The exchanges are clearly trading off providing liquidity, providing an orderly market, supporting price discovery, and acting as counterparty. Now, ask yourself which is important from the perspective of investors. My vote goes to supporting price discovery. If the price quoted on the exchange is not a market price available to every potential trader, risk takes on an additional dimension. What good are all the other disclosures if one doesn’t really know what the price is?

The argument that acting as counterparty is most important can’t be dismissed. After all, a rapid, radical shift in assessments of counterparty risk was a prime cause of the 2007-2009 financial crisis. Also, acting as counterparty eliminates any real liquidity issue if there is honest price discovery. The flash crash resulted from a fictitious liquidity created by the development of trading systems without real counterparties. So, the clearinghouse function is right up there, especially as it relates to systemic risk.

The problem is that exchanges are compromising the most important forms of transparency: price. Flash trading involves not just allowing trades at prices other than quoted prices, but is close to offering different prices on a selective basis. If selected traders are allowed access to inside information about market internals, they have an opportunity, and some would say are encouraged, to trade at other than quoted prices. This subverts basic transparency.

Similarly, dark pools, where stocks trade off of the markets, raise the same issue. If the price in the market isn’t the price at which the stock is being traded, transparency is a fiction. Again, who cares why the stock changes hands when the price at which it trades isn’t really the price?

So, it seems discussions of transparency should always be prefaced by the question: What is going to be made apparent? It also seems that the SEC and the investing public need to think about what transparency is important.

Addendum:

One could argue that liquidity is a necessary condition for price discovery. The trader would ask: What relevancy is a price quote if nothing can be traded at that price? The fund manager would say: The price isn’t valid for the volumes the fund trades. The Doc would add: There is no market without liquidity. But, that seems to be basic economics. Supply curves and demand curves have slopes. Given prices in digits and fractional shares, how much of the demand curve and the supply curve could be disclosed?

It seems with volumes and prices a lot about liquidity is already known. Bid ask spreads and/or price fluctuations over whatever time frame is assumed in one's definition of liquid, are known. Thus, historical liquidity is disclosed. Future liquidity and instantaneous liquidity are nice concepts, but not a reality. However, if blocks are traded without disclosure (i.e., in dark pools), then neither liquidity nor price are being disclosed.

Sunday, May 16, 2010

Gold again

Everyman’s speculation

The April 5 posting was about gold (see: " Gold: Be sure you know what you’ve hedged " ). So many people were touting gold that it seemed that some perspective was needed. In the long run it isn't a very good investment, but as a short run speculation, it has its moments.

When it has those moments, I get told-you-so emails from one set of friends and watch-out-for-the-bubble emails from others. But, I like to point out that Boeing made as big a percentage move early this year as gold did recently; Boeing pays a dividend, and as a long run investment, Boeing beat gold coming (dividends) and going (price appreciation).

What is certain is that the price of gold DOES measure distrust. So, it’s a good hedge against distrust. If you needed proof, recent events make it apparent. Developments in Europe raise the prospect of deflation if governments tighten budgets. Yet, gold went up. Note: deflation not inflation. Why up? --distrust of government, fiat money, the economy, banks, and just about everything else.

Gold will probably continue in that role as a hedge against distrust right up until people stop trusting it. Does that sound like fertile ground for bubbles, fraud, and pump-and-dump shops?

The problem with discussing gold is that people don't get past yesterday’s price and a short-run forecast. They'd be happy to participate in a bubble in the belief they would know when to get out. Besides, a bubble is only a bubble after it pops. Until then, it is just the new reality. So, all most people really care about is the date of the inflection point. That’s the kind of advice where if you’re right, it proves THEY are smart, and if you’re wrong, YOU are dumb. Given an advice game where if you’re right, they win; if you’re wrong, you lose, I pass.

It is worth noting that the other hedge against distrust has been Treasuries. That ought to worry anyone thinking seriously about it. The real question is which --Treasuries or gold -- will reverse trend first. Each has very different consequences.

For disclosures see: "Gold: Be sure you know what you’ve hedged" and "Debt markets as indicator or a trade."

Saturday, May 15, 2010

The day the computers panicked PART 3

“Sometimes you eat the bear and sometimes the bear eats you”

Some reader may know the source for that quote; I’d appreciate the reference. It’s cuter and more memorable than “Can’t win ‘em all” or “You win some; you lose some.” Besides, given the topic, it’s more appropriate. The topic is how to beat computer-generated meltdowns. You can call them a “flash crash,” a “one minute meltdown,” or an “insta-bear.” Most of them actually last more than minute. But, they’ve been some nice opportunities.

The March 30 posting on this blog entitled “Wall Street doesn’t run the world” http://hedgedeconomist.blogspot.com/2010/03/wall-street-doesnt-run-world.html states: “…the individual knows more about their timing requirements and has more control over them than do most institutional investors.”

There are many ways to take advantage of that control. This posting discusses some. In the posting cited above, other considerations important to individual investors are discussed. Using the techniques discussed here involves tradeoffs between those considerations, thus the citation rather than just the quote.

One consideration that will be explicitly addressed is tax treatment. Tax treatment, however, doesn’t impact whether the techniques work, but it influences how to implement the techniques and where each technique works best. But, the treatment of tax considerations only covers whether the techniques are workable in tax deferred accounts.

This posting addresses how to benefit from a meltdown using techniques that also pay off regularly. It also addresses things that backfire in a meltdown. One caution when discussing trading techniques: no technique is a substitute for common sense. Some people get so fascinated with technique they forget what they’re really doing. Technique is marginal; investing is substantive.

So, you ask: Why write about technique? Well, the previous posting mentioned quantitative funds. To some extent, they earn a rent on their analysis of the market, but, whether they know it or not, flash trading and dark pools have introduced another element. Much of their return is a rent on insider information. Since you or I would go to jail for trading on insider information, the techniques discussed are a way to level the playing field by partially protecting oneself from this insider trading by taking advantage of the behavior it spawns.

“Guarding Against Market Gyrations” at http://www.mainstreet.com/article/moneyinvesting/stocks-funds/guarding-against-market-gyrations also discusses the topic. Although I disagree regarding one of the techniques recommended, the article is worth reading. The very first point it makes is also probably the most important thing to remember. Using market orders leaves one totally vulnerable to any sudden changes in the stock’s price.

A previous posting when discussing asymmetric returns stated: “Even the probability of lesser forms of illiquidity get mis-estimated. Consider big, instantaneous changes in price (“discontinuities” or “gapping” in investor jargon). If one has investments, there is a good chance one asset experienced a gap in price during the time it takes to read this posting. It might be small, but it isn’t unusual. Some investment advisors recommend always using limit orders as protection against discontinuities being used to the investors detriment.” In a meltdown, many assets (stocks, indexes, bonds, commodities, even currencies) are likely to gap. It is the classic example of why market orders are dangerous.

The second point is related to market orders, but it addresses “stop loss” orders. I dislike market orders so much that the dislike explains why I differ with the market gyrations article on “stop loss” orders. As stated in the last posting on this blog: “A “stop loss” is a limited protection. It doesn’t guarantee a price when an asset price “gaps.” That’s the same lesson learned in October 1987. Further, they don’t protect one from volatility. One can get “stopped” out of a position at a price that is lower than the price a few seconds later. In fact, the presence of a large number of “stop loss” orders increases the probability of “gapping” because once the “stop loss” thresholds have been crossed the orders all become market orders to sell.” It’s a judgment call, but data seems to support the contention that in a meltdown “stop loss” orders are likely to do more harm than good. The “stop loss” may be a technique that meltdowns has made obsolete.

The third technique is a buy order with a price limit that is “good until canceled.” One has to remember the order has been placed and treat it as money spent. Certain conditions have to be met for this trade to make sense. The conditions are (1) one has money one wants to invest in a specific stock if it can be purchased at a given price, (2) one doesn’t currently have an alternative that is as attractive as waiting to get that stock at that price, (3) one has a strong conviction about the purchase at the target price, and (4) one can remember to remove the order as soon as any of those conditions are no longer met.

To illustrate, let’s assume someone had been watching P & G trading at about 62 earlier last week. Further, suppose one heard that P & G’s earning announcement disappointed some institutional traders. This may have alerted some people to a possible drop. Now suppose the observer wasn’t willing to dismiss those earnings concerns. But, one thing the observer felt comfortable saying was that if it dropped to 55 the reaction was overblown. If the “good until canceled” order was on the books on Thursday, the observer would have made a good buy and could trade out now at a profit.

I intentionally chose P & G for the illustration since there were rumors surrounding P & G at the time. The strong conviction is important because the risk with any standing buy order is that one could end up buying a broken company and there will always be rumors. But, that risk would be there regardless of the purchase price. Psychologically, however, the act of buying at the point where it becomes apparent the company is in trouble makes it seem more painful. (Darned if I didn’t just see the same example of using “good until canceled” orders using P & G at 40 or 50. Oh well, hopefully, more people will use the approach to get stock they want).

The fourth topic is a note on a technique that doesn’t work. For most individual investors, having some liquidity available during a computer driven meltdown doesn’t help. The proverbial “cash on the sidelines,” is always nice. As they say, it lets the investor take advantage of opportunities. But, one opportunity it won’t let most investors take advantage of is a flash crash. They happen too fast.

To illustrate, with two personal stories. Last Thursday during a break at a conference, a number of us were watching the meltdown on CNBC. When they showed P & G’s plunge, I turned around and muttered “I have to get to a broker or a computer.” A concerned voice asked “Are you getting out?” My response was “Heck no; I want to buy P & G. I’ve been waiting for an opportunity.” By the time I got to the end of the table, the DOW had recovered about 500 points and P & G was showing a 50% recovery and gapping up. Unless one was sitting at a very high speed trading desk, there was no opportunity without the order already being on the books.

In the October 1987 one day 20% meltdown, a similar thing happened. Back then one traded through a broker mainly over the phone. Every broker’s phone, even the brokerage office’s lines were busy from late morning on. It was so frustrating that late in the afternoon, I left the office to drive to the broker’s office. I was desperate to put whatever money I had into the market. I arrived about fifteen minutes before the market closed. The office lights were off. A frightened administrator unlocked the door when I explained I was a customer. She told me the office had shut down. They couldn’t get the flood of sell orders processed and everyone went home. They were just too discouraged and sad. Further they feared irrate customer would get violent. When I said I wanted to buy, she just said she wasn't a broker and they had closed down the system.

So, based on personal experience, be advised: if cash on the sideline is how you plan to take advantage of computer panics, be sure you have a technique for getting the trade done before the computers reverse field.

The fifth topic is watch lists. A watch list that’s on hold for something to happen so that the investor can act will often be of limited use when computers panic. Don’t take that wrong; an investor should have watch lists for buys and sales. But for meltdowns, the logical response is a watch list (or part of a watch list) that is set up to act when conditions meet set criteria. That is the essence of this posting. If by contrast the investor can’t identify a single thing that is advisable regardless of daily updates, the investor needs to learn more about what they’re considering. Granted, other opportunities may come up, but if they aren’t there today their relevance today is limited.

So far, everything said involves techniques that can be applied in taxable or non-taxable accounts. Now it’s time to discuss some techniques most brokers won’t accommodate in tax-deferred or non-taxable accounts. Also, since the discussion involves options, it seems appropriate to remind the reader that the topic is meltdowns only. Buying panics aren’t addressed even though they often occur in other assets simultaneously with meltdowns in equities (or bonds).

The technique is selling puts as a way to acquire a stock. To review, selling a put is giving someone the right to sell you something (a stock in this case) at an agreed upon price (the strike price). The technique has been mentioned negatively on this blog a few times (for example, in connection with regulatory reform on March 4 in “Putting the adults in charge of derivative trades” http://hedgedeconomist.blogspot.com/2010/03/putting-adults-in-charge-of-derivative.html the posting noted: “…selling naked puts, do it often enough and eventually you’ll get a collateral call.”). In a meltdown it won’t be just one put that gets “assigned” They can all get assigned (i.e., the people who bought the puts could all require that the seller of the puts honor their commitment and buy at the strike price).. Thus, the person who sold the put sees all their liquidity evaporate at a time when they might like to have some money. The person selling the puts could use up their entire margin, and if stocks keep falling, end up getting a margin call.

The real point, however, is the realization that the person selling the put had already given up that liquidity when they sold the put. People will say things like “I’m selling puts so that I can hold onto my liquidity while earning a little more than cash earns.” For them, a better way to look at it is that they are using their liquidity to buy the cash flow from the time decay of the option. As the obligation goes away over time, they are getting paid back with their own liquidity. So, in a sense, they sold their liquidity for whatever they got for the put and now they’re getting it paid back in installments from their own funds.

When discussing asymmetric returns on May 1 in “ Sometimes Wall Street provides more entertainment than Hollywood: PART 2 the losers “ http://hedgedeconomist.blogspot.com/2010/05/sometimes-wall-street-provides-more.html the reason this is important was explained. It worded the reason as: “asymmetric returns are so dangerous. Making the mistake outlined above is often profitable most of the time. The Pavlovian response to the repeated positive feedback is dangerous for two reasons. First, it is a tempting trade since most of the time it makes money…. Second, the positive feedback reinforces the tendency to underestimate the risk. Thus, there is a tendency to “up the ante.” In businesses, this takes the form of increasing the risk exposure or even ignoring risk guidelines.”

So, selling puts to generate income can be deadly in a meltdown. However, selling them to purchase a stock can be beneficial. Granted, in a flash crash one may not get assigned. Similarly, the stock could “gap” right through the strike price, leaving the put seller obligated to by at a price above the market. But, if the investor wanted it at the strike price, they could just have likely bought it at that price and experienced the same paper loss. Further, if short run paper losses really upset a person, stocks aren’t the place to be.

A disclosure is in order; so, let’s get it out of the way. This posting addresses only one of many ways an individual can take advantage of their control over their timing requirements. My preferred approach was recently characterized as “diversification across time.” That characterization was so catchy it deserved quoting. A consequence of diversification across time is being close to fully invested most of the time, thus perhaps not maximizing the potential returns from computer panics. But, the strategies discussed here don’t require anything as dramatic as a flash crash. They work and I take advantage of them.

One might question why protective puts and covered calls weren’t discussed. Both covered calls and protective puts are effective techniques for reducing volatility. In fact, buying a put, so that one knows the minimum price one will get for a holding, is certainly more effective than a “stop loss.” But, both are designed to reduce volatility. The topic of this posting isn’t reducing volatility of investments; it’s profiting from market volatility. That’s why the discussion of “stop loss” focused on how they backfire. Similarly, covered calls trade off potential up side volatility for the price earned by selling the call (technically the time decay on the calls). Not an appropriate technique for profiting from volatility.

One final point, circuit breakers on individual stock will move computer panics to other markets. But, the techniques discussed work fairly well with good old fashion human panics. Thursday’s real lesson for individual investors should be not to invest in stocks unless one can tolerate volatility. If one might need liquidity over the near term, don’t buy stocks.http://hedgedeconomist.blogspot.com/2010/03/wall-street-doesnt-run-world.html ">

Tuesday, May 11, 2010

The day the computers panicked PART 2

Should we fix it?

Up to the end of March, all the postings on this blog focused on regulatory reform; as early as January 28, one of the first postings suggested a reform that would help address this issue (see: “Efficient capital allocation doesn’t require perfect liquidity”) Nevertheless, this posting on regulatory reform is done with considerable hesitation.

When it comes to regulatory reform, nothing fits better than a quote from a Rolling Stones’ song: “You can’t always get what you want, but if you try real hard, sometimes you just might find, you get what you need.” Further, over the weekend you probably saw headline like this one from the WALL STREET JOURNAL: “Regulators Are Stumped by Drop.” “Stumped?” By what? It seems to me that regulators and politicians are going to try to obfuscate the obvious. When that happens, people get divided and emotional about anyone not going along with the party line. That’s one reason for the hesitation.

The second cause for hesitation involves disclosures. I’m not “talking my book” as the saying goes. After this posting, PART 3 will address how to make money from computer panics. It’s so easy it would be a shame to see this easy money go away. Further, mathematical models are intriguing especially when they involve financial markets. It would be equally sad to see them go away. Finally, people who develop trading systems that work can earn a rent on their effort. It’s only slightly different from people who develop any other type of systems. We let the market judge the value of other systems.

It isn’t hard to figure ways to reduce volatility. A fee per trade or circuit breakers will do the job. You might ask: why the question in the subtitle? The answer is “because any method of reducing volatility will have other consequences.”

Fees on trading have an impact that won’t be uniform across types of assets unless carefully designed. They have different implications depending on how one trades. Ultimately, they raise the cost of capital, but that could be reversed by linking them to lowering other taxes on capital.

Direct limits on vilatility will only force the volatility into other markets. That could be other markets for the same asset as occurred Thursday in selected stocks, or it could be into markets for other assets. One of the reasons for concern about limits as being discussed is a belief that many traders will shift volatility risk from equities to other asset classes where that risk can do more economic damage. Remember, equities are not the only asset class that gets volatile when computers panic, and quantitative trading cuts across asset classes. Further, limits, like fees, have to be carefully designed and cover multiple assets, not just one type of asset.

Limits also introduce another potentially dangerous risk. To illustrate how they could introduce more risk consider “trailing stop loss” orders. They are often a component of trading systems. Thursday many people learned the risk associated with those trading systems.

A “stop loss” is a limited protection. It doesn’t guarantee a price when an asset price “gaps.” That’s the same lesson learned in October 1987. Further, they don’t protect one from volatility. One can get “stopped” out of a position at a price that is lower than the price a few seconds later. In fact, the presence of a large number of “stop loss” orders increases the probability of “gapping” because once the “stop loss” thresholds have been crossed the orders all become market orders to sell.

Now, introduce limits. Limits would give people or computers a chance to go in and cancel the “stop loss” order if it had not been executed. That sounds positive. However, consider the other side of the trade. The trader who cancels the trade now has a totally un-hedged position. Granted the hedge was partial and may be failing to accomplish what the trader intended. But, as has been pointed out before in this blog and elsewhere, no hedge is ever perfect. So, by canceling the “stop loss” the trader is exposed to the risk that was hedged as well as the risk that, unbeknownst to the trader, never was hedged. That may or may not be good. But, it seems to this observer that canceling a large number of partial hedges at a time of particular volatility is a strange risk reduction strategy.

It would be naive to assume the trader whose “stop loss” has failed won’t pursue an alternative approach to limiting down side risk. When the limits kick in, would prices of protective puts shoot up to their limit? Would buying of “protective” assets spike? Would there be a flight to liquidity? Other traders would also react. Would short sellers smell blood in the water among this group of exposed longs? Would the more insightful traders find an alternative to “stop loss” orders ahead of time? If so, what would it be?

Would traders just move to a different asset class where there are no limits? All of those questions were brought up in 1987 after the October crash. Limits past after 1987 didn’t cause any disasters, but they also didn’t end computer panics. Also, historical experience seems to suggest limits didn’t reduce volatility and perhaps increased it, but, granted, other things being the same before and after 1987 would be a naïve assumption.

In any case, it seems very likely limits will be expanded to individual equities. That will shift volatility risk to other assets. Hopefully it won’t be Treasuries or currencies, but, quite frankly, what market needs to be more volatile?

There’s an interesting and informative sidebar issue resulting from Thursday. Let’s look at the issues surrounding the NYSE’s shift to slow trading on selected NYSE-listed stocks, Procter & Gamble in particular. It’s a perfect example of the shifting of volatility to markets that couldn’t accommodate it. However, that point is being overshadowed by differences in philosophy. As discussed below, it also looks like the markets that couldn’t accommodate the volatility want to change the issue to conceal their failure to provide an orderly market.

The issue surfaced in an exchange between Duncan Niederauer, CEO NYSE Euronext, and Bob Greifeld, CEO Nasdaq OMX Group Inc. Greifeld’s contention is that the overall volatility in the stock was increased by the Nasdaq’s inability to provide enough liquidity to accommodate an orderly handling of the volatility. He doesn’t say it that way since blaming it on the NYSE is so much more consistent with his interests. But, that’s the bottom line of his position. That seems reasonable. When all the volatility risk is shifted to one market, that market will be stressed.

Niederauer’s counter that the purpose of the NYSE is to provide an orderly market. Can’t argue with that. But, under the circumstances he seems to be overly professional in not pointing out that Nasdaq didn’t deliver an orderly market.

Here’s where the verbal exchange gets interesting, and it betrays each man’s philosophy and the market they serve. Another function of an exchange is to provide liquidity. Clearly, when the NYSE moved to slow mode it traded off providing instant liquidity for orderly market. Who is served by each? People don’t even sense instant liquidity. The slower mode and even a pause for a few minutes would hardly be noticed. By contrast, computers assume instantaneous, continuous liquidity. Put bluntly, Nasdaq would accommodate computers at the expense of people while NYSE leaned the other direction.

Next step in the analysis involves the exchange’s role as a method of price discovery. Clearly, that is a key function of an exchange. Again, Nasdaq was willing to “execute” any trade without regard to whether the price discovery was being compromised in order to accommodate continuous trading. NYSE wasn’t. If one needs proof, it will come when trades are unwound as is being discussed.

Finally, an exchange acts as a clearing house becoming the counterparty. NYSE slowed trading to ensure it could fill that counterparty role. We will see whether Nasdaq honors all trades. This last issue goes to the heart of the issue of whether an exchange walked away from the market. Slowing trading isn’t walking away from the market; it’s slowing it. By contrast executing erroneous trades and then not honoring them is walking away from at least two important responsibilities of an exchange.

The difference in philosophy revealed by the verbal exchange raises an interesting question. Do we need two different types of exchanges? One designed for computer trading with computer and one that accommodates people. People and computers could move between them, but the design of the assets would be different. It is less pie-in-the-sky than it sounds. It could be done by creating two different classes of stock. One would target those needing instant, continuous liquidity. The other would compromise instantaneous, continuous liquidity, but fulfill the ownership aspirations of some equity investors. If you think it is far fetched, remember there are ETFs that represent the same assets as traditional mutual funds although in that example the assets don’t differ much if at all. But, rather than explore that solution, let’s just hope limits aren’t viewed as a substitute for some common sense applied to the issue of fees.

Sunday, May 9, 2010

The day the computers panicked PART 1 (cont’d)

How to drive a computer mad

Although computers are emotionless, calculating machines, their behavior seems emotional at times. In that context and with tongue in cheek let me say: “Nothing irritates a computer more than violating its assumptions.” Thursday something did just that. We have as candidates “fat fingers,” Greeks, and no doubt other candidates will surface as people look into it. The exact cause of the panic isn’t really that important. But, since we have set up hearings to “investigate,” it’s probably worth pointing out a few other candidates for blame.

A posting on this blog entitled “Sometimes Wall Street provides more entertainment than Hollywood: PART 2 the losers” pointed out a few mistakes people make. These mistakes can be programmed into computers as assumptions or can be preconditions for the program to operate as intended. In fact, one of them has been advanced as a candidate.

Many programs assume instantaneous, continuous liquidity. The posting stated: “Investors get it so, so wrong. To illustrate, everyone reading this posting probably either has experienced or will experience times when most of their assets are illiquid. We aren’t just talking overnight or the mutual fund industry’s practice of redeeming at closing net asset values. Exchanges get closed down, markets dry up, and these things happen fast.” Well, an interruption to trading on selected NYSE listed stocks, Procter & Gamble in particular, has been brought up as a potential trigger for some of the volitility. Computers just don’t like the world not conforming to their assumptions.

Alternatively, the same posting stated: “Consider big, instantaneous changes in price (“discontinuities” or “gapping” in investor jargon). If one has investments, there is a good chance at least one asset experienced a gap in price during the time it takes to read this posting. It might be small, but it isn’t unusual.” Gapping due to lack of liquidity or “fat fingers” could have been a contributing factor.

However, the reason these weren’t initially mentioned was to keep the focus on the important issue. It would be a shame if the “investigation” obscures the obvious and most important point.

The day the computers panicked PART 1

A real instance of science fiction

By now you probably know something about what happened Thursday. In case you don’t, let me make a citation simply because it states the obvious. The headline is “Computers, Not Human Error, Likely Caused Market Meltdown.” It happened simultaneously in multiple markets: commodities (e.g., gold and oil), bonds (e.g., one could easily track in real time in Treasuries, but other debt markets also), currencies, equities, and derivatives. The plunge went furthest on purely automated exchanges. Do you think it might have been computer driven?

But for the sake of thoroughness, let’s include a more extensive quote:
“Computerized sell programs triggered by global events-rather than trader error or "fat finger"-appear to have caused Thursday's unprecedented market swing, according to market pros who are reconstructing the nearly 1,000-point stock sell off.
These experts think the intensely accelerated electronic trading was sparked by the Greek debt crisis and other events and not a trader who typed a "b" for billion instead of "m" for million in executing a trade on Thursday.”

If the link’s still good, you can grab the article at:
http://finance.yahoo.com/news/Computers-Not-Human-Error-cnbc-1614949039.html?x=0&sec=topStories&pos=2&asset=&ccode=
But really, do you need it? Something, could have been “fat fingers” or Greece, set off a panic. It would be ironic if it was Greece because that would make the discussion of sovereign risk and the rush to post on debt on Wednesday seem prescient. However, for what follows, it is irrelevant whether it was “fat fingers” or Greece.

Let’s see who panicked. It wasn’t people. It happened too fast, in too many places, and in too many markets. Put bluntly, a computer or multiple computers panicked. In case you think computers don’t panic, remember this isn’t the first time. If one follows markets, one has seen a few computer panics. Think about October 1987 for a dramatic example, but it’s just one. Yes, computers can be, and have been, programmed to panic. There is probably someone programming a computer to panic right now. The people who do it are called “quants.”

This blog has pointed out the destructive impact of quantitative trading numerous times. Perhaps too subtly, but it was the topic of “On Quants” on March 9. On February 28 in “Is the Volker Plan shadow boxing or can it help?” the posting stated: “Quantitative trading did cause some of the contagion even if it wasn’t the root cause. But, hedge funds seem to have been the more important vehicle, not banks. In fact, hedge funds were probably instrumental in transmitting the downturn from debt markets to equity markets where they had an impact on a broader set of individuals through their 401k’s and IRAs.” And, again the thought scenario in a posting entitled “Beware the risk-free return” explained why quant funds blow up. Perhaps the posting should have been more explicit about the collateral damage they cause.

So, here is the science fiction. On Thursday a bunch of computers panic; after a minute or two and into Friday the panic spreads to people. Sound familiar? We know people can sense panic. Casual observation, history, behavioral economics, and the social sciences all have confirmed it. It seems computers sense each other’s panic, too. Unlike organisms, which, according to scientists, seem to have multiple methods of sensing fear, computers undoubtedly sense it from behavior. It also seems people can sense computer panic. Witness the reporting and reactions of people during Thursday’s meltdown.

Your response might be: What’s the big deal? Panics happen.” But, we remember them and record them for history because they have consequences. In the case of Thursday, the volatility of every asset class has changed. It has changed in terms of how it is measured for investment decisions, which means it will be reflected in prices, and thus it will have an impact on capital allocation. In the last step in this chain, capital allocation will influence future economic growth.

That’s damage done. The quants update their data to incorporate the revised volatility measurement. Actually the updates are preprogrammed and have often occurred already. Consequently, post-event trading reflects this dog-chasing-its-tail computer intelligence.

But, now let’s allow people into the picture. Over the weekend they’ve also had a chance to update their perceptions. Their reactions cover a much broader range of behaviors than just the multiple markets that the programmed trades influence. Most people probably aren’t feeling as secure as they did Thursday morning. If they hadn’t already thought about the consequences of a computer panicking, they should feel less secure. Realizing computers panic is quite different from panicking and warrants a very different response.

The response from a policy perspective will be PART 2, and the response from an investment perspective will be PART 3.

Friday, May 7, 2010

Wednesdays posting on debt markets

Thursday was interesting

Wednesday's posting on debt markets is something that won't happen too often. Most postings won't get posted without complete explanations. The posting was rushed to get it posted before leaving for a two and a half day conference. Thursday, in about 45 minutes, you saw why the rush. But, Thursday's “hissy fit” in financial markets wasn’t due just to what was going on in debt markets. Debt markets were important, but by Monday there should be a posting on some other things that Thursday dramatically illustrated. They’re relevant to investing and regulatory reform.

Wednesday, May 5, 2010

Debt markets as an indicator or trade

Only relevant to traders and analysts

Quite a while back a trader asked about debt markets as an indicator. The trader focuses on equity options. In light of what is going on in Europe, an update to the response is worth posting. However, it is quite limited in depth. The trader’s question focused on not being blindsided by the end of the world while making some money trading very short term. Here’s the response; it has only been lightly edited.

Yes, debt markets were the source of the financial crash. It went way beyond being an indicator. Once debt markets realized how many people weren’t going to pay back their borrowing, debt markets froze. It started with mortgage debt, but spread via the shadow banking system. The cause of the spread was that liquidity was needed to adjust for the mis-priced Mortgage Backed Securities. The rush to liquidate (i.e., get liquid) rippled through every market in the shadow banking system. Any market and therefore any organization with a liquidity mismatch became vulnerable. That transformed a liquidity- driven contraction into a generalized fear about counterparty solvency. That was one of the unintended consequences of mark-to-market accounting as interpreted under Sarbanes Oxley.

I don’t need to go back and check. One of my kick-myself-moments was watching this happen, knowing what was happening, seeing the indicators, explaining it to people, and not trading it aggressively.

Currently, there are a few things to watch, but they are more as fire alarms than trading guidance. One should watch the relation between the short term Treasury rates and the LIBOR…the interest rates not the prices. If they start moving in different directions, it warrants a second look. It’s somewhat of a one way indicator. This can indicate when things are very bad, but most of the time it is a "no news" story. So, it generally doesn't get coverage.

If the LIBOR goes up while Treasury rates are going down it indicates something is wrong. People with money don't trust the financial system. That is exactly what happened going into this crisis.

The opposite can be timing differences as the Fed raises rates, but they shouldn't be large and shouldn't last. This is something to keep an eye on given where we are right now. If it gets large or lasts, it would indicate a reduction in the confidence in the Fed and Treasury. Specifically, it could indicate a lack of confidence in the ability of the Fed and Treasury to control inflation.

From an equity-timing perspective yield spreads between corporate debt and Treasuries are a good indicator, but the spreads have tightened enough that recently there wasn’t a lot of information in their movement. However, they generally say where we are in the cycle. When it become inconsistent with where we are in the cycle, something is going wrong in financial markets.

The problem with using debt to time equity markets in the short run is that there are so many automated trading system that rebalance big portfolios real time and daily. They kill any easy money; that leaves us manual traders with the need to interpret debt markets as well as equities. Debt markets convey a lot of information, and there is a lot less noise (i.e., random movement getting big news coverage) than in equities.

Over the next few years, one should also watch long-term Treasury rates. The Fed and flight-to-quality are holding them down, but at some point the Fed will have to stop monetizing the national debt. The flight-to-quality right now is giving them a chance to start the process without having to thread a needle. There is a good chance the Fed will miss this opportunity for reasons related to global impacts. Thus, when Fed does start tightening, the speed with which long rates rise will indicate whether the recovery aborts. It could be important early next year, say March. But a lot depends on what happens in Europe.

There was an important disconnect going on for most of this year. Gold and debt markets were making two very different forecasts. Debt markets were forecasting slow growth and price stability. Gold is forecasting inflation. They were closely reflecting currency trading but with short periods where they disconnected from the dollar and started trading on their own scenarios. The movements in both were bullish for stocks over the short run. That has changed as gold stopped rising and debt markets, especially in Europe, finally realized there is risk in sovereign debt.

This is the disclosure relevant at the time. You may remember a discussion we had about gold trades. I got in below 1K for the trade I wanted. But, the other side of the trade was puts on Treasuries as a hedge for the corporate bonds I had rebalanced into. The disconnection referenced above (gold and debt markets) resulted in the bonds going up in price. The hedge wasn’t necessary. Net, I got where I wanted to be, but it was more complicated than I like.

Angel, entrepreneurs, and diversification: EPILOGUE

Just an example

In this weekend’s WALL STREET JOURNAL there was an article about small caps. The previous posting on “Angels, entrepreneurs, and diversification” made a reference to differences between small caps prices fluctuate and large caps’ prices patterns. If you want further discussion the article is at: http://online.wsj.com/article/SB10001424052748703572504575214722949936724.html?mod=WSJ_PersonalFinance_PF2
The article discusses timing; something the postings didn’t discuss since timing was incidental to the issue discussed in “Angels, entrepreneurs, and diversification.”

Saturday, May 1, 2010

Sometimes Wall Street provides more entertainment than Hollywood: PART 2 the losers.

It’s unfortunate that people don’t like to talk about trades gone sour.

Behavioral economists and market observers have known for years that people take credit for their success, but the same people attribute failures to other people’s behavior or advice. In addition to people’s reluctance to face their own mistakes, much less talk about them, the media is not much help. Efforts to find scandals are all too easy; they’re the lazy man’s reporting. The result is that one can expect more stories of victims than analysis of mistakes. That’s unfortunate because other people’s mistakes are a possible source of insight; besides they’re usually cheaper than one’s own.

The Goldman Sachs story references in PART 1 may prove to be an exceptional source of information on mistakes to avoid. But, even when the facts do surface, reporters’ search for villains may obscure the potential lessons. GS clearly doesn’t come out looking like a saint. But, at the same time, it seems silly to portray them as a beneficiary. As mentioned in PART 1, loans from Buffet and TARP as well as big write-downs of assets aren’t typically what one would associate with a winning portfolio. So, how did GS and others end up needing the help?

As background, the reader will find a lengthy quote below. The quote isn’t included to explain how organizations wrecked themselves. It talks about millions which is small change when considering the scope of what happened. Rather, the quote will serve as a source of illustrations.

Also, the quote was taken from a story making a bullish case for GS stocks. However, PART 1 already made the case for avoiding investments in situations involving conspiracy stories. Thus, no reader who checks out the full story could misinterpret my reason for the quote. The full story can be found at:
http://online.barrons.com/article/SB127146775162378679.html

“The SEC complaint shows the lengths to which Paulson -- and Goldman -- went to create a CDO that Paulson figured stood a good chance of collapse.
Paulson & Co., led by John Paulson, correctly anticipated that the worst subprime securities would come from adjustable-rate loans to borrowers with low credit scores in such states as Arizona, California, Florida and Nevada, where home prices had soared, the SEC said.
Paulson & Co. cleverly sought to bet via a CDO, or a collection of existing sub-prime securities, rather than simply bet on a newly created pool of loans. The securities that were the focus of Paulson's efforts were rated Triple-B by the rating agencies and stood beneath a large group of highly rated bonds.
The Abacus CDO was backed by about 90 individual Triple-B tranches from sub-prime deals. Paulson probably recognized that if losses on the underlying subprime pools hit 10% to 15%, the triple-B tranches would be wiped out, resulting in a total loss on the Abacus CDO despite Triple-A ratings on the instrument. That is indeed what happened.
The losers from the Abacus deal were a German bank, IKB (IKB.Germany), which lost $150 million, and Royal Bank of Scotland (RBS), which lost $840 million.
The Scottish bank's loss, which helped lead to a giant bailout by the U.K. government, itself is fascinating. ACA Capital, designated to select the underlying securities, originally guaranteed the $909 million top-rated tranche of the Abacus deal for just 0.50%, or about $4.5 million.
ACA subsequently got buried by mortgage losses and couldn't pay the claim. ABN Amro, the Dutch bank subsequently bought by Royal Bank of Scotland, provided a backstop to ACA on the deal for an estimated $2 million. That $2 million guarantee ended up costing Royal Bank $841 million when the CDO collapsed, and most of that money was paid to Paulson.
Royal Bank's huge loss raises questions about whether the ABN Amro managers knew what they were getting into and demonstrates the risks in the financial-guarantee business, which Buffett has described as ‘picking up nickels in front of a steamroller.’
In a statement late Friday, Goldman emphasized that it lost $90 million in the transaction, that IKB was a highly sophisticated investor and that ACA had ‘every incentive’ to select appropriate securities because it issued a $900 million guarantee on the deal.”

The quote is rich in examples of mistakes. There are mistakes both involving actions taken and interpretations of the actions. As written, it tells an interesting story. But, when one looks at it from the perspective of an analyst rather than a narrator, it’s always good to start with the most important item.

1) Asymmetric payout as a warning

The most important point is to be extra careful when asymmetric payouts are involved. From the perspective of mistakes to avoid, Buffet’s quote comparing the risks in the financial-guarantee business to "picking up nickels in front of a steamroller” is the most important point.

Why is this point most important? After all, if payouts on good trades verses losses on bad trades are markedly different, of course one would be careful. One would do the math on the payouts, calculate the odds they imply, then compare them to one’s own best guess as to what the odds really are. What’s the big deal?

First, one should remember that if the payouts are very different, any small error in the estimate of the odds will have a big, I mean BIG, impact on the payout. That in itself is a big deal. But it’s worse than that, never mind estimates. If there are even small errors in how the odds are measured , and there are aways some errors, disaster can follow.

Second, there is considerable evidence that people do funny things when large sums of money are involved. It can be seen as irrational or as evidence that a million dollars means something other than one dollar times a million. Economists say the marginal utility of money isn’t linear. Doesn’t mater what one calls it; lottery ticket sales clearly aren’t in the financial interest of the buyer from the perspective of the probable payout verse the price. Clearly, there is more to the phenomonal success of lotteries than just people shelling out a buck for a few days of the dream. It doesn’t end there. It also seems that most people don’t do extremely large numbers well. Witness how many don’t distinguish between million, billion, and trillion when discussing public policy. So, it seems important to be especially clear about what one is buying and to not confuse dollars and dimes.

Third, often asymmetric returns are associated with what is known as tail-risk in risk management and financial economics. Tail-risk involves very low probability events. This is exactly the area where traditional quantitative financial economics tends to fail. Further, the reason it fails seems to reflect basic, or at least common, perceptual predispositions of humans. We are so dependent on basing our expectations on what is common that we underestimate the probability of the uncommon. In quantitative financial economics, this surfaces in assumptions about the probability distributions associated with events. So, one has to overcome one’s own predisposition and recognize that a lot of “sophisticated” potential counterparties are in a worse situation since they are paying other people to estimate a risk that even the “professionals” are predisposed to underestimate.

The point about being paid to mis-measure the risk is only one example of why asymmetric returns are so dangerous. Making the mistake outlined above is often profitable most of the time. The Pavlovian response to the repeated positive feedback is dangerous for two reasons. First, it is a tempting trade since most of the time it makes money. Entire businesses have been built on the returns. Second, the positive feedback reinforces the tendency to underestimate the risk. Thus, there is a tendency to “up the ante.” In businesses, this takes the form of increasing the risk exposure or even ignoring risk guidelines.

“Is this relevant to the average investor?” You bet it is! People often make exactly this kind of trade. This blog has mentioned selling naked puts before, but a far more common example is not having any “rainy day fund.” As absurd as it is, we have to force unemployment insurance. Unemployment, at least once in a career, is almost inevitable. Beyond that, not insuring against risks one can’t bare is almost too common to deserve mentioning. We’re debating whether people should have to carry medical insurance and have liability insurance when they drive. Sure, most of the time one gets away without either; thus avoiding having to pay the premium. It is continuous positive feedback. But, it only takes once to wipeout any premiums previously saved.

More in the investment area as we usually define it; think about why we have margin limits. Enough people get the likelihood of unusually large moves so wrong that it makes margin limits advisable as protection for individual investors and to protect the clearing houses.

However, my favorite example is liquidity risk. Investors get it so, so wrong. To illustrate, everyone reading this posting probably either has experienced or will experience times when most of their assets are illiquid. We aren’t just talking overnight or the mutual fund industry’s practice of redeeming at closing net asset values. Exchanges get closed down, markets dry up, and these things happen fast.

The probability of more routine fluctuations, even big ones like the recent events, are underestimated. They not only happen, but they last longer than most people realize. To illustrate, think about mark-to-market accounting for a minute. Aside from the absurdity of assuming the market is always right, we’ve almost enshrined the idea of continuous liquidity into accounting.

Even the probability of lesser forms of illiquidity get mis-estimated. Consider big, instantaneous changes in price (“discontinuities” or “gapping” in investor jargon). If one has investments, there is a good chance one asset experienced a gap in price during the time it takes to read this posting. It might be small, but it isn’t unusual. Some investment advisors recommend always using limit orders as protection against discontinuities being used to the investors detriment.

A disclosure seems appropriate. I have a strong preference for avoiding asymmetric payouts totally, and when they are unavoidable, I lay the risk off with insurance.

2) Complexity as a risk

Beyond asymmetric risk issues, the quote also implies a few other mistakes to avoid. First, my reading is that complexity is its own risk We’re not talking the complexity of the instruments being traded. Seriously, the parties involved all understood the instruments being traded. They weren’t that complex to people familiar with bond markets. The complexities that probably tripped them up were the complexity of their own organizations and the complexity of the RISK embedded in the instruments.

One could argue that complexity of the risk embedded in an instrument is complexity of the instrument. So, that leaves organizational complexity. The key quote is: “Royal Bank's huge loss raises questions about whether the ABN Amro managers knew what they were getting into…” That can be interpreted two ways: as either not knowing the risks implied by the guarantee or not knowing what the risk implied by the guarantee did to the Royal Bank’s overall risk. The quote addresses only the first. That’s possible, but seems less likely than the second.

But, the reader might ask: “How does that relate to an investor?” First, a direct implication is worth noting. If the second is true, it raises questions about the viability of the Basel II framework. It implies we are underestimating the level of risk in large banks operating under Basel II. Basel II could be conceptually correct, but impossible to implement in practice. There can’t be any doubt that the concept of hedging risk is a risk reduction strategy, but it is equally obvious that the more complex the risks being hedged, the greater the risk of gross mis-measurement somewhere in the process.

This reasoning would imply that growth as a risk reduction strategy has some inherent limitations. Further, it would seem logical that growth through acquisition, especially acquisition in new financial service areas, would carry the greatest risk. This could explain why banks’ initial acquisitions in non-banking areas often don’t work out. It wouldn’t be the only reason, but it probably contributes.

That would still limit the implications to investments in the financial service industry. However, if one views portfolio complexity as analogous to organizational complexity, it suggests additional implications.

First, if big financial firms with all their staff have trouble managing complexity, most investors are going to have a harder time. One should try to simplify away any complexity that one can’t clearly justify. Put, differently, know why each holding fits into the portfolio, not just why it is a good standalone investment. Balance the two: portfolio fit and standalone appeal. If an investment looks good as a standalone, but, for example, over-weights an asset class, use forced choice. Some asset in that asset class should be sold. A disclosure is appropriate because this discipline has worked so well for me that I might be overlooking limitations. A true fundamentalist would argue a total from-the-ground-up approach with each investment ONLY assessed as a standalone is better.

Second, financial firms can’t get hedges perfect: one should never assume a hedge is quantitatively right even if it is checked regularly. The quantitative values of hedges fluctuate just like the value of other assets. In other words, hedges have to be rebalanced periodically, just like any other asset in a portfolio. But, rebalancing isn’t enough. Hedges, just like any other asset, are subject to tail-risk. It even seems the tail-risks are greater with hedges than net long or net short positions. Perhaps it’s because hedges involve at least two positions. From what has been said, it should be apparent hedges don’t provide a perfect substitute for liquidity and don’t necessarily justify greater leverage risk. My disclosure is that I use traditional hedges sparingly, and always to hedge only one very specific risk associated with another position, not the position itself.

Third, when taking a position in a new asset, think of it as analogous to a corporate acquisition. If it’s new in type, expect errors. Some advisors recommend starting small; others admonish against any experimenting with a new investment style (i.e., “stick to your style”). Some advisors suggest doing it on paper first. My tendency is to only take on one new type of asset or type of trade at a time and to assume I’ll make some mistakes. My motto is “Stick to your style to make money. Experiment to learn.”

3) Know the difference between fees and profit

Perhaps it is how the transactions are reported, but one is definitely left with the impression that the pursuit of the fees that they would earn tempted these firms into trades that resulted in some losing investments. One might conclude that the point is irrelevant since fees are what financial firms are about; it’s their business. However, the point has relevance to non-institutional investors.

First, one should always remember that hedging away all risk is desirable in the financial service industry where there are fees to be made on both sides of the transaction. Most investors don’t enjoy that benefit. For most investors the fees flow out, not in. So, trying to do what the “big boys” do can be foolish. Risk isn’t something to avoid. It is inevitable for investor.

Second, fees can’t guarantee you’re not trading against your counterparty. You’re always trading against your counterparty. It is amazing that some people want to vilify GS for trading against “clients” they sold assets to. They don’t seem to realize that selling or buying an asset implies trading against one’s counterparty.

Third, fees appear to have encouraged participants to take on more risk than they could manage. For investors it is a reminder that fees are a consideration, but not THE primary consideration. Avoiding fees shouldn’t drive the investor away from a good investment any more than the pursuit of fees justified losing position by parties to the trades involved in this situation.

4) Information disparities

This is the heart of the civil suit against GS. So, it would be premature to go too far in discussing it until the suit is determined. However, there are some anomalies worth noting. One contention is that two facts weren't disclosed: (1) a short was the counterparty and (2) GS’s position. That these are an issue seems curious. They are information that one doesn’t have on any trade executed on an exchange. The anomaly is that regulatory reform would expand the role of exchanges in derivatives trading, thus extending the absence of this information to more of the derivatives market.

In the March 4th posting, The Hedged Economist argued: “Bringing more derivatives (i.e., like some standard interest rate and default swaps, some commodity hedges, etc.) onto exchanges makes sense.” Both the use of an exchange and a clearing house were endorsed. If that position is correct, one might conclude that the information at issue in the Goldman Sachs civil suit isn’t “material.” Yet, the April 23rd posting noted investors who successfully traded the same instruments “put effort into understanding whether their immediate trade was with a counterparty or a middleman.” It goes on to suggest that it’s a good idea for investors to do the same. That would suggest that the information is “material.”

The April 23rd posting, when discussing the successful traders, went on to say “Once the people making the trade understood who their counterparty would be, their primary concern wasn’t motive. Their concern was solvency.” Their concern wasn’t whether their counterparty thought the price would go up or down. They understood that their counterparty probably had an opinion different from theirs.

But interestingly, a second issue related to the suit is the fact that a short seller was involved in structuring the asset. The irony here is that a short is often the originator of many positions in any asset without it being disclosed. It’s very common in options. But even with stocks, short sellers may be selling an investor a stock or selling it to an individual’s mutual fund. Most successful investors have no reservations about buying without knowing whether a counterparty is a short seller.

Ultimately asymmetric information is a fact of life. The court will decide what information should have been disclosed. Putting limits on the information asymmetry is desirable. But, from an investor’s perspective, making assumptions about the direction of the asymmetry can be as big a mistake as assuming there is no asymmetry. Furthermore, and far more importantly, it is essential for investors to decide what information is important to their own investment decisions. The courts can’t do that for them.

It would be unfortunate if GS’s role or Paulson’s success keeps investors from looking beyond the superficial media coverage. This could be an instance where we aren’t left with only our mistakes as examples of what doesn’t work. The most obvious lesson for investors is how dangerous it is to just blame GS if the recent crisis hurt one’s portfolio. Many people won’t bother to look at how they managed their liquidity or their leverage levels, or examine the risks associated with their investment strategy. While it’s important to learn from others’ mistakes, it’s essential to think about how they compare to one’s own.