This Is the End


Markets, Risk and Human Interaction

December 5, 2009

The Strategy of Conflict

December 05, 2009
To: Ismail Haniyeh, Hamas Prime Minister
Cc: Khaled Mashal, Chairman of the Hamas Political Bureau
Subject: Will you ever get Shalit off your hands?

I know you are frustrated with how slowly things are going with the Shalit prisoner swap negotiations. You must feel relieved that it is finally just around the corner. Well, it isn't. You are going to be waiting for a long time yet to come. Do you really think Israel will trade hundreds of convicted murderers for one soldier? Have you ever thought there might be something more going on?

You are being played. One tip-off is Israel’s bare-knuckled bargaining posture, which basically is, “Please, please give him back. We will do whatever you want.”

Doesn't this seem odd to you? I mean, put yourself in their shoes. If that sort of deal really goes through, what do you tell the next victims of violence perpetrated by those released in the swap? What do you tell the parents of Israeli soldiers killed in the process of capturing the terrorists who are released, not to mention the relatives of those who were killed in the terrorist attacks? And what about its effect on the incentives (a big topic of discussion in the U.S. right now, though in a slightly different context) for future acts of kidnapping.

I don't know if it translates, but in the U.S. we have a saying: If it sounds too good to be true, it probably is.

Here is what is really going on. Israel is having a lot of fun at your expense. They can use the hostage situation as a backdrop to lay siege to Gaza, make incursions with all kinds of cool military hardware, imprison various Hamas leaders as a tit for tat. They can hold off peace talks while expanding settlements. And meanwhile what can you do? Take all of this while sitting through endless negotiations.

This is why Israel is acting like the return of Shalit is the most important thing since 1948. Putting so much focus on him provides Israel a justification for all of this. It is like, well, people spending generations in refugee camps to provide a pretext for terrorism. If the Israelis had said something along the lines of, “Crap, you got one of our guys. Who do you want in exchange,” it would be hard to bring it to the scale of three years of harsh, but you have to admit, from Israel's perspective sort of appealing, measures.

Anyway, I am sure the big question, now that you see what is going on, is how you get yourself out of this mess without becoming a laughingstock. One way is to reduce the number of people you demand in exchange. But you can't do that; it would be politically disastrous. And in any case, if you do go down that path you will discover the negotiations will continue to lurch from one snag to another even when it gets whittled down to a one for one exchange. Maybe you can let him escape. Or ask the Israelis to mount a daring raid, with plenty of bystanders killed in the process – they're not going to do that, but you can – so that more attention is put on their apparent overreaction than your military failure. (You already know how well that works).

But it won't be that easy. You aren't going to be able to get rid of Shalit unless you are willing to give them something big in return.

There was a general expectation you would have figured all of this out about two years ago. By this point everyone is tired of waiting. Any gag can only go on for so long. Of course, Israel cannot be the one to let you in on it, so I am the guy who has ended up with that job.

Now that I've let the cat out of the bag, I am going back to writing about finance.

November 8, 2009

I am going to be working at the SEC

November 08, 2009
I will be working in the SEC's new division of Risk, Strategy and Financial Innovation as Senior Policy Adviser to the Director. Here is a brief article and the SEC announcement. We are facing a critical time for defining the future of the financial system; an opportunity for financial reform that comes only once in a generation (if that), and I am excited to be part of this.

I will still be able to write posts from time to time, but obviously with limits on topics and with appropriate disclaimers. How much free time I have to do so, though, remains to be seen.

I won't be able to publish comments for this post related to the SEC.

November 4, 2009

Does Financial Innovation promote Economic Growth?

November 04, 2009
I participated in an Oxford-style debate at The Economist’s Buttonwood Gathering a couple of weeks ago. The proposition for the debate was Financial Innovation Boosts Economic Growth.
On the pro side of the proposition were Myron Scholes, the chairman of Platinum Grove and Robert Reynolds, the CEO of Putnam, and on the con side were Jeremy Grantham, the CEO of GMO and me. This was the first time I had participated in a formal debate, as I suspect it was for the others. When we came out onto the stage, I overheard one person in the audience say, with a British accent, “Well, they obviously have never been in an Oxford debate before.” I don’t know what we did wrong, but it looks like we even messed up our entrance.
The entire debate is available on the Economist site (scroll to the video "Debate on Financial Innovation") and here. It includes five-minute opening remarks by each participant – first Robert for the pro, then me for the con, then Myron and finally Jeremy. This is followed by questions from the moderator and audience and then closing one-minute Clarence Darrow-moment summations. The debate is pretty interesting, but for those who do not want to spend the time watching it, here are the main points I made.
I elected to restrict my discussion of financial innovation and economic growth in two respects.
First, I focused only on the so-called innovative products. I grant that there are some innovations in the financial markets that have been beneficial; Robert Reynolds gave a summary of many of these. I take as a given that electronic clearing, the adoption of telecommunications, the development of futures, forwards and mutual funds have all had a positive impact.
So what do I mean by innovative products? Well, I could just say you know them when you see them. But when I think about innovative products, I think about them in a three dimensional space. I look at where the product fits in the dimension of simple to complex, standard to customized, and transparent to opaque. The things I term innovative products congregate in the {complex, customized, opaque} region.
Second, I focus on the impact of financial innovation over the past ten or fifteen years. I am looking to the past rather than forecasting the future for two reasons. One is that I do not have a crystal ball, so I cannot project what innovations will occur in the future. Another is that if the future ends up looking like the past, then at least the past can provide a guide. Behavior being what it is, absent regulation to bridle our actions, this is a reasonable assumption to make.
So, defining innovative products in this way and looking over the past ten or fifteen years, let’s look at the ways financial innovation might promote economic growth.
Do innovative products promote growth by increasing market efficiency?
If we were in an Arrow-Debreu world, the answer would be yes, since these products will help span that space of the states of nature. But the incentives behind innovation move in the other direction. The objective in the design and marketing of innovative products is not market efficiency, but profitability for the banks. And market efficiency is the bane of profitability. The last thing a bank wants is a competitive, efficient market, because then it would not be able to extract economic rents. So the incentives are to create innovative products that reduce market efficiency, not enhance it.
How is this done? Well, I can quickly think of two ways. First, by creating informational asymmetries, by having products that are difficult for the users to understand and price. And, second, by designing innovative products, which, due to their non-standard nature, allow the banks to extract higher transaction costs.
Do innovative products promote growth by allowing us to manage risk better?
Hardly. They create risk, or, if you don’t want to go that far, they hide risks. They put risks off balance sheet, obfuscate them through complex schemes, create non-linearities and correlations that only become evident in times of large market changes. They also push more risk into the tails, so that in the day-to-day world things look more stable, but in an extreme event the losses are accentuated.
Earlier in the conference, Larry Summers gave an address where he remarked that since the early 1980s we have had a major financial crisis roughly every three years. Whatever financial engineering and the innovations it creates is doing for the markets, it is not tempering risk.
Do financial innovations help meet investors’ needs?
Unfortunately, the answer is yes. Well, not investor needs, but investor wants. They allow investors to lever when they aren’t supposed to lever, take exposure in markets where they are not supposed to take exposure, avoid taxes, take on side bets in markets where they have no economic interest. I go through some of the uses of derivatives for gaming and gambling in my Senate testimony from June.
Do innovative products promote capitalism?
The answer to this is yes and no. We get capitalism when things are going well, and socialism when things are going poorly. I went through this in a recent post.
Innovative products are used to create return distributions that give a high likelihood of having positive returns at the expense of having a higher risk of catastrophic returns. Strategies that lead to a ‘make a little, make a little, make a little, …, lose a lot’ pattern of returns. If things go well for a while, the ‘lose a lot’ not yet being realized, the strategy gets levered up to become ‘make a lot, make a lot, make a lot,…, lose more than everything’, and viola, at some point the taxpayer is left holding the bag.
If we were to look at the sorts of strategies employed by large investment firms and banks, my bet is we would see a bias toward short volatility, short gamma, short credit and short liquidity. All facilitated with innovative products – you can’t really do the first two without derivatives – and all leading to these sorts of return characteristics.

This was a debate, so we all took the polemic positions. I am not so extreme as to hold that all innovative products, even those that do fit in the {complex, customized, opaque} corner, are devoid of value. But just because we are able to take some cash flow and turn it into a financial instrument doesn’t mean we should. Here are three questions we can ask to determine if a new, innovative product makes sense:
  1. Is there a standard, simple instrument that could do the job – either one that already exists or one that can be created.
  2. Is the primary purpose of the new instrument to meet economic objectives (i.e. helping to get capital to the producers or helping producers layoff risks) or to meet non-economic objectives (i.e. gaming the system, making side-bets on the market).
  3. Does the instrument create negative externalities; on the margin does it increase the risk of market crisis, does it make the market more levered, complex and opaque?

October 23, 2009

Why Do Bankers Make So Much Money?

October 23, 2009
A tenet of economics is that in competitive markets there are no economic rents. That is, people get fairly paid for their efforts, their capital input, and for bearing risk. They are not paid any more than is necessary as an incentive for production. In trying to understand the reason for the huge pay scale within the finance industry, we can either try to justify the pay level as being a fair one in terms of the competitive market place, or ask in what ways the financial industry deviates from the competitive economic model in order to allow economic rents.
Do the banks operate in a competitive market?
No one expects competitive levels of compensation when there are deviations from a competitive market. In what ways might the banks – and here I mean the largest banks and those banks that morphed over the past year from being investment banks – fall away from the model of pure competition?
One way is through creating inefficiencies to keep competitive forces at bay. Banks can do this, for example, by constructing informational asymmetries between themselves and their clients. This gets into those pages of small print that you see in various investment and loan contracts. What we might call gotcha clauses and what the banks call revenue enhancers. And it also gets into the use of complex derivatives and other “innovative products” that are hard for the clients to understand, much less price.
Another way is to misprice risk and push it into other parts of the economy. The fair economic payoff increases with the amount of risk taken. If a bank takes on more risk it should get a higher expected payoff. If the bank can get paid as if it is taking on risk while actually pushing the risk onto someone else, then it will start to pull in economic rents. The use of innovative products comes up again in this context. They provide a vehicle for the banks to push risk to others at a less than fair price. Or, they can push the risk onto the taxpayers by hiding the risk and then invoking the too-big-to-fail protections when it comes to be realized. The current “heads I win, tails you lose” debate centers precisely on this point.
A third, and most obvious reason banks might not be economically competitive entities is the organization of the industry. There are barriers to entry. No one can just decide to set up a major bank. And there are constraint in the amount of business any one bank can do. As we have seen with Citigroup, there finally are diseconomies of scale – after a point the communication and management issues make the bank less efficient and more prone to crisis. If there is fixed supply, then the banks can push up the price of their services. The crisis over this past year has made matters worse. If you are one of those still standing, you are a beneficiary of that crisis, which has choked off the supply even further.
Are the workers getting paid fairly for their efforts?
An alternative to the idea that the industry is not competitive is that the industry really is competitive and those who are getting these outsized paychecks are being fairly compensated for their efforts. This comes back to the term we hear bandied about in conversations on banker compensation: talent.
There is no denying there are many smart people in the banking industry. (Though I think from a social welfare standpoint, we might have done better if some of those physicist and mathematicians that populate the ranks of the banks had found greener pastures in, say, the biological sciences). But I don’t buy the notion that there are so many who have the level of talent that justifies tens and even hundreds of million in compensation. I think this level of compensation, and the notion of talent behind it, is the result of the inherent uncertainty in the financial enterprise, one that makes it very difficult to assess talent. Indeed, I think the invocations of talent for money producers in finance are akin to those that, in times past, were set aside for the mystical powers of saints and witches.
Far more than other fields of endeavor, it is difficult in finance to tell if someone is good or lucky. A top trader or hedge fund manager might have a Sharpe Ratio of 1.0 or 2.0. But that Sharpe Ratio is nothing less that a statement that if you get a hundred people trading, a few will do well just by luck. (And it doesn’t matter if that Sharpe Ratio occurred over the period of one year or twenty – though the greater sample size helps, it is still the same point in terms of statistical inference, so a long track record does not get you away from this problem).
How does this tie in with saints and witches? People want certainty, and if they can’t get the certainty they want from the empirical, they fall back on superstition and witchcraft, or at least they used to way back when. In some medieval village, a priest prayed and a supplicant was healed. The odds that the supplicant would have healed spontaneously was whatever it was, but there was more of a sense of certainty to feel that it was the manifestation of healing power.
There were false saints and true saints. The difference between them became manifest over time by how frequently the prayers were answered with affirmative results. Not that any saint had to bat a thousand. Sometimes there were understandable, exogenous circumstances that inhibited the saint’s healing talents from being operative, most commonly a lack of righteousness on the part of the supplicant, occasionally an inevitability, a higher power that overshadowed that of the saint. Maybe the will of God, maybe an unknown, evil curse.
I hope the analogy is apparent. And there is a related one, an analogy to Pascal's Wager. The bank should wager that the talent of its star employee exists, because it has much to gain over time if it does, while if it does not exist, the bank will lose little in expected terms. And in a competitive world, it is even worse if they incorrectly let the talent go for lack of proper compensation, because then some competitor will pick it up.

October 11, 2009

We Need Open Derivative Models

October 11, 2009
Before I knew anything about the finance industry, if someone had thrown out the name “Blackrock” I would have conjured up a scene from the Wild West, a cattle rancher hiring a gunslinger to roust out the sheep farmers and take control of the town. But now, of course, I know that BlackRock is a financial behemoth with $1.5 trillion in assets under management -- soon to be over $2 trillion due to its purchase of Barclay’s asset management business. But of more note than its asset footprint is the mantle BlackRock is gradually assuming as the arbiter of value.

BlackRock won a set of contracts to provide analytics for the New York Fed’s trillion dollar mortgage-backed purchase program. Now, BlackRock may end up with an NAIC contract to analyze the mortgage-backed securities in insurers’ portfolios.

I do not mean to diminish BlackRock’s laudable role in assisting in many ways with the financial crisis – coming forward when a number of other large firms demurred. But as one contract is piled on another, their models will become the standard for pricing mortgages, complex derivatives and structured products. Unlike the money management business, which is competitive and relatively transparent, this is a monopoly ready for the making. A monopoly because the more institutions, industry associations and regulatory bodies that employ their services, the more they become the de facto standard. Over time, auditors, clients and equity holders – perhaps even regulators – will start saying, “Well, it is nice to see what your internal models have to say about your portfolio value, but we want your portfolio benchmarked using the BlackRock model.” A BlackRock seal of approval; BlackRock, the JD Powers of portfolio quality.

Here are the problems with this:

First, of course, is the well-known issue of allowing a private enterprise to have monopoly control of a utility – in this case a de facto replacement of the rating agencies (not a bad thing in itself) by putting one firm in the position of providing the benchmark pricing of financial products. Second, there are natural conflicts of interest given that BlackRock is also the asset manager for the New York Fed’s Maiden Lane portfolios and has raised over half a billion in private capital to purchase legacy securities as part of PPIP. (Though I should add that BlackRock is aware of this issue and has stated the firm has strict internal controls preventing any valuation services from being gamed by its investment arm. Which should make us all feel a lot better).

But the most critical problem is that its approach is at variance with the broadly held view that we need to have transparency in the derivatives markets because, unlike, say, RiskMetrics, BlackRock does not share the specifications of the models it employs. We don’t really know what these models are doing. Valuations based on a black-box BlackRock model, or, for that matter, anyone else’s black box model, do not get us the transparency we need. I don’t care what a trading desk uses for its decision making, but when it comes to valuations that carry beyond the firm, we need to be able to see and critique the models that are being used. If a model is to become a standard, if it is going to be used for regulatory or other benchmarking purposes, it should be transparent and subject to peer review.

Which gets to a simple point: If we want to go down the path of standardized valuation and comparability in these complex portfolios, we need open derivatives models. One thing we should have learned from the rating agency debacle is that even if we put aside the issues of monopoly power and conflict of interest, we cannot stop with having the proprietor of such models say, “Trust me, I know what I’m doing.”

September 22, 2009

Asset Allocation

September 22, 2009
I appeared last Friday on a the PBS program WealthTrack, where the topic was asset allocation, in particular, as host Consuelo Mack put it, how to build an all weather portfolio. I was the skeptic of the group. I don’t think there is some magic asset allocation that protects you from the buffetings of financial storms without it also trimming your sails during fair weather. Here is an encapsulation of my views from the program.

Asset allocation and risk appetite
One of the participants, asset allocation guru David Darst of Morgan Stanley, proposed various portfolios to protect against a 100-year flood, 30 to 70-year flood, a 25-year flood, etc. Those portfolios boiled down to putting less in risky assets and more in bonds; the more severe the flood you anticipate, the less risk you take. Of course, that will do the trick. If by asset allocation you mean determining where to set your risk tolerance dial, we’re all on board.

Asset allocation is like clapping with one hand
But the discussion of risk tolerance highlights that we can only go so far with asset allocation if we only look at assets. What matters is assets versus liabilities, because the liabilities determine our risk tolerance and, related to that, our demand for liquidity. It is impossible to formulate an ideal asset allocation strategy without knowing the liability stream those assets are intended to meet. There is no one-size-fits-all for asset allocation. This reminds me of an FAJ article I did back in the 1980s with pension actuary Jeremy Gold entitled “In Search of the Liability Asset”.

Diversification works well, except when it really matters
We all know the argument from Finance 101: If you hold 16 uncorrelated assets, your risk will drop by a factor of four. Well good luck with that.

During a crisis, when diversification really matters, correlations aren't near zero (as if they ever are). All that people care about is risk and liquidity. All assets that are highly risky drop, all assets that are less liquid drop. No one cares about the subtlety of earnings streams. It is like high energy physics. When the heat gets turned up high enough, matter is just matter, the distinctions between the elements is blurred away.

This is not to say that one should not try to diversify, but rather that one should not think diversification will work magic. It is a given that a portfolio should not be limited to U.S. Treasuries and S&P 500 stocks, because while it should not be oversold, diversification does have some benefit. And, on the other side, unless someone is still living in the 1970’s, it borders on the intellectually dishonest to trumpet a diversified portfolio by using the S&P 500 as the bogey. A college kid can construct a portfolio that will beat the S&P 500 on a risk-adjusted basis, because there are so many more markets available now. A better approach is to look at a given asset allocation versus its nearby well-diversified neighbors, and try to understand why one is better than the other.

Commodities do not form an asset class
This sounds heretical given what we have seen oil and gold do recently, but a lot of the reason that has happened is precisely because people are treating them as an asset class when they are not.

Commodities are not assets. They are factors of production. They do not generate returns, they have no claim on production. They have supply that flows out at a nearly fixed rate short term, and they comprise very small markets compared to the financial markets. If pension funds all decided to put two percent of their capital into commodities, two things would happen. First, that two percent would be a rounding error in their returns, no matter how commodities behaved. Second, they would swamp the supply of the commodities for economic purposes – i.e. for their true role as factors of production. I agree with Michael Masters’ view that oil prices were pushed up by this sort of financial activity. I might quibble with one chart or another, I might not couch it in the loaded terms of speculation.
But the subsequent behavior of the market demonstrated that he was right and Goldman and others who took the opposing view were wrong.

Inflation-Linked Bonds
Which brings me to inflation-linked bonds. At the close of the program we all were asked for one investment recommendation. In one form or another we all focused on the same one: inflation-linked bonds. But I would not carve them out as a distinct asset class any more than I would commodities -- though unlike commodities, at least I think they are an asset. They are one of many assets that load on the inflation factor. If you have a long-term view, equities are also decent inflation hedge. After all, over time prices adjust, and so do earnings. And, as with commodities, the supply of inflation-linked bonds is low; there is a liquidity premium to pay.

I think what has elevated inflation-linked bonds from the category of “asset” to that of “asset class” is memories of the 1970s, a heyday for inflation-linked bonds. If you could have held them during the stagflation period, you would have looked golden; they would have given you a Sharpe Ratio of over 1.0 while many other assets was flat-lining. If I were building a simulation to beat the market on an historical basis, I would add in inflation linked bonds just for the pop they would give in that decade.

September 16, 2009

Regulation in Defense of Capitalism

September 16, 2009
Will regulation hobble capitalism? I think the opposite is true. Properly done, government regulation of the financial industry will move the industry closer to the capitalist ideal. By capitalism, I mean where those who take the risks and put up the money get the fruits of their labor. And, importantly, where those who take the risks and put up the money actually do take the risks, bearing the full costs of failure as well as success. As things stand now, we have a finance industry that is capitalist when things are going well and socialist when things are going poorly -- right-tail capitalist/left-tail socialist.

Capitalism means bearing the costs
I sometimes miss the rugged beauty of Utah, where I spent some of my pre-Wall Street years. From my house on the foothills of the Wasatch mountains, I could see the cliffs of Mount Nebo to the south, nearly fifty miles away. Ten miles north, the western face of Mt. Timpanogas, capped with snow into early summer. To the west, the sun reflecting on Utah Lake. Oh, and on the eastern shore of the lake, the black smoke billowing out the stacks of Geneva Steel.

Geneva Steel was built to produce steel during the war effort, and kept in operation until seven years ago. It teetered at the edge – and at least two times over the edge – of bankruptcy, closing for good in 2002. Left behind were assorted furnaces, presses and scrap metal sold to a Chinese steel producer, and a giant pond of toxic sludge.

Fortunately, we’ve learned a thing or two about toxic sludge in steel production. The steel producer, in this case the original parent of the Geneva plant, U.S. Steel, has to set aside a fund to pay for the clean-up. The sludge is part of the production process, and the clean-up is a cost of production, even though it is a cost that is not realized until many years down the road. As a result, steel costs are a little higher and the shareholders fare a little worse than if this longer-term expense were not forced onto the producers. The regulation that requires setting aside funds for the clean-up might be considered intrusive to the core values of capitalism. But it is the contrary. It is forcing the steel mills to recognize all of their costs rather than leave society to foot part of their bill.

Wall Street’s toxic sludge
Wall Street has its own forms of toxic sludge, longer-term costs and negative externalities from products and strategies: The increase in the risk of crisis that comes from the opacity of complex derivatives; the fat tail risk of positions that are short credit or liquidity; negative gamma trading strategies, strategies that in various guises are like naked call writing, making money most of the time, but on occasion failing spectacularly; the forced deleveraging and liquidity crises that come from high leverage.

These costs are easy for the Wall Street capitalist to ignore, because unlike the sludge pond behind the steel mill, they are not visible until they finally hit. Indeed, they are not even deterministic. They might hit or they might not – so what we have in financial markets is invisible and probabilistic toxic sludge. Which makes sludge-producing strategies all the more popular with banks and traders, because if you can do things where you don’t have to bear some of the costs, the odds are better you will turn an apparent profit.

The limited liability assault on capitalism
The banks and trading firms don’t have to bear these costs because of the widespread use of limited liability. Limited liability creates a ‘heads I win tails you lose’ relationship. The template for limited liability is the corporation, a template that has been copied to create the trader’s option and short-term compensation, paid out before the full costs of a product or strategy are manifest.

If I want to get the most value out of limited liability, I will gravitate toward fat tailed and complex businesses, where most of the time I pump money out with regularity, but face some prospect of a catastrophic loss. How catastrophic? The bigger, the better. It doesn’t matter to me how bad things get once they have passed my liability limit. And the larger that catastrophic case, the more costs I am passing on, and thus if a general risk-return relationship holds, the more return I will get as long as the catastrophe is kept at bay.
Put in other terms, I will look for businesses and strategies that produce the highest level of costs that I can slough off, that will be unrecognized by others. Is this the direction Wall Street has gravitated? Are the exposures of traders and banks biased toward taking credit risk, being short liquidity risk, and short gamma? Do they prefer the complex to the simple? Do they push leverage as far as regulation allows?
Regulation and capitalism
Regulation that exposes this and forces the trader or bank to absorb these costs makes the markets more true to capitalist ideals. Capitalist regulation forces the producers to recognize all of their costs. It undoes the harm to capitalism that comes from limited liability and its kissing cousins, the trader’s option and short term compensation deals. The flip side is that with capitalist regulation, no one can take on more risk than they are capable of absorbing. Which means requiring higher levels of capital on the one hand, restricting leverage on the other, which in turn means reduced capacity to generate high returns.

The aspiring capitalists among us will decry such regulation because it invariably makes our lives harder; we can’t make as much money. But if the reason is that the regulation is now forcing us to bear all of the costs of our enterprise, then we are feeling the pain of having the socialist trappings removed, and entering into a more robust capitalist regime.

September 11, 2009

The Risks of Financial Modeling: My Testimony to the House

September 11, 2009
I testified before the House for the hearing, "The Risks of Financial Modeling: VaR and the Economic Meltdown". This is my written testimony. This is the video of the hearing.

I testified in the Subcommittee on Investigations and Oversight. This subcommittee includes a number of members -- including the Chairman -- who also are on the Financial Services Committee, and so the hearing in this venue will find its way back there.

I shared the panel with Nassim Taleb. While we naturally had disagreements in some areas, I think by and large we presented the message. (For example, see this FT post). I enjoyed meeting him in person for the first time.

September 4, 2009

HALT: Imposing Limits on High Frequency Trading

September 04, 2009
In my first post on high frequency trading, I ended with a somewhat tongue-in-cheek proposal for a High-Frequency Arms Limitation Treaty, or HALT. The more I observe of the concern for this strategy, the more pervasive it becomes, and the more apparent abuses that come to the fore, the more this proposal moves from the realm of satire to the real.
As I mentioned in that post, I do not think the market benefits from moving trading speeds faster and faster in the millisecond range. But what the need for speed does do is burn through untold hundreds of millions of dollars for all the competitors to keep up with one another. And just as the complexity of derivatives can lead to the obfuscation of non-economic or manipulative operations, so can operations that blur past the screen before anyone can observe what is happening.

Here are some questions regulators should ask -- maybe they already are asking them -- to see if HALT makes sense:

What is the economic benefit of trading with twenty millisecond latency versus thirty millisecond latency?

What is the economic cost and what are the barriers to entry erected by pushing the latency envelope?

What speed of trading leads the marginal costs of obfuscation to dominate the marginal benefit for the end investor? By obfuscation, I mean the creation of a cloud around the trading activity that prevents the regulators from being able to assure the investors are being protected and the market is operating transparently and fairly.
What level of trades per second becomes problematic in terms of obfuscation versus practical and economic value? The focus with high frequency trading is the latency, but focus also should be given to the number of trades done per second. It is not just a matter of speed of trading, it is the cloud of noise that comes from what can be hundreds of different trades on one security all flowing from one trading firm into the market in a very short time period.
The answer to these question might be limits on the latency of trades and the number of trades per second allowed in any one security by private and proprietary trading firms.

August 28, 2009

Not with a Bang but a Whimper – The Risk from High Frequency and Algorithmic Trading

August 28, 2009
Skynet begins to learn, at a geometric rate.
It becomes self-aware at 2:14 a.m. eastern time, August 29.
In a panic, they try to pull the plug. -- Terminator 2
There is a general view that one way or another the end result of all the high frequency and algorithmic trading will be a blowup. But I don’t think the risk is as big as many are making it out to be.
First, let me point out the difference between high frequency trading and algorithmic trading. Both execute using computers, and since computers work really fast, both can be accused of whatever sins are embodied in millisecond trading.
High frequency trading is a type of proprietary trading. The trader (or his computer) sees a profit opportunity and trades accordingly. This profit opportunity might occur because the high frequency trader observes signals in the way the market is trading that makes him think the price is moving up temporarily because someone needs to buy. He supplies the other side of that person’s demand, and once the demand is satiated the market price will most likely revert, and the high frequency trader will make a profit. And in doing so, he will be providing a service to the market – he will be a liquidity provider, and by getting into the market faster he will provide that liquidity for a lower price. Put another way, the better he is at his business, the less the price will be moved by the person who is requiring liquidity, and thus the lower transaction costs will be. Another way the high frequency trader will make money is by getting into the market before others do when there is information that is moving the price. Which explains the arms race in getting news feeds and executing based on the news a few milliseconds faster than others.
Algorithmic trading uses computer algorithms to facilitate trade execution. For example, some investor has decided to buy ten thousand shares of a particular stock. Once that decision is made, the question remains of how to execute the trade. One way to do it is to put a ten thousand lot buy order into the market. Another way is to have somebody sit on the phone and call the order in a hundred shares at a time in ten minute intervals until it is all done. Or, another way is to program a computer to do it. The computer can be programmed to do it any way a person can be told to do it. It can parcel the order out in fixed intervals, it can parcel more of it out during periods of high volume, it can throw orders out at random times and in random quantities. The point is that all this computer program is doing is facilitating a buy or sell order that has already been determined, and doing it based on a trading algorithm of the investor’s choosing. It is cheaper and more exacting than having someone do it on the phone, but really is not much different. If we are going to pose a horror story based on the huge volumes of computerized trading, we should not count the substantial portion of that volume that is occurring due to this algorithmic trading. Because one way or another, these trades are going to be done, and it is simply cheaper to have the computer do it.
So, having made the distinction, why am I not as worried as many others about a computer based cataclysm as a result of this sort of trading?
To answer this, let’s look at the example that often comes up as an object lesson for what can go wrong, the 1987 crash. On the face of it, the 1987 crash seems to be a reasonable historical case study, because the crash was, in a sense, the result of computers gone mad. It was the computers behind portfolio insurance that dictated more and more selling of futures to hedge equity portfolios as the market dropped, and that selling of futures in turn added to the drop. I gave a blow-by-blow description of this in Chapter 2 of my book – I had a front row seat because I was one of the people doing portfolio insurance, throwing my computers into the fray for such blue-chip clients as Ford, Chrysler and Gillette.
I wrote about portfolio insurance to illustrate one of the demons that we have created that contributes to the crisis-prone nature of our markets, namely, tight coupling. Tight coupling is a term I borrowed from engineering. A tightly coupled process is one which, once it gets going, cannot be easily stopped. If there is a problem – if the train starts going off the tracks, so to speak – no one can pull an emergency brake to pause the process until a committee convenes to figure out what to do. A computerized system like portfolio insurance is tightly coupled. The liquidity crisis cycle that comes about from the forced liquidation of highly leverage investors is a tightly coupled process. So are processes in other areas, like a space shuttle launch, a nuclear power plant moving toward criticality, or even something as prosaic as the process of baking bread.
But just because something happens in milliseconds doesn’t mean it is tightly coupled. And, for that matter, just because something is tightly coupled doesn’t mean it is prone for disaster. You need something more to cause such a cataclysm than computers trading quickly. You need a lot of them all doing the same sort of thing, and doing it in a way that feeds back on itself. And doing it in a way that is not brought to a stop when it seems to be going awry. That is why portfolio insurance was a problem. While computers were involved, which of course makes for a better story, it could have happened even if people had been making the calculations on an abacus and phoning the orders in. Because the problem was that many people were all pursuing the same strategy, and that strategy was one that reinforced a drop in the market – that is, it was a strategy that sold into a market drop, leading to a further market drop. I don’t see this essential element in either high frequency trading or algorithmic trading.
For algorithmic trading, the issue is simple. Some investors have determined to buy and others have determined to sell. They have reached these determinations however they have done it in the past; it doesn’t have anything to do with the advent of millisecond trading. Now they happen to decide to execute these trades over time as a function of the bid-offer spread, the volume of trading, the level of prices – that is, based on the same sorts of things that they would have without computers. And they can monitor what is going on with their trades over the course of the day. So this is not a tightly coupled process. A call to their broker, and the trading stops. Just like if the broker had someone doing it on the phone.
For high frequency trading, the issues are not as simple. It is possible to construct a scenario for high frequency trading where a strategy is widely shared which has a reinforcing feedback and which pushes forward without anyone intervening. But I can construct such scenarios even without the need for millisecond trading. Not just construct such scenarios – I have seen them, and so have you, in any number of bubbles and crashes.
But speaking specifically about the risk due to high frequency trading, the risk of a cataclysm is constrained by the lack of feedback and lack of tight coupling. High frequency trading is a matter of individual trades – or possibly baskets of trades. It is not a process, much less a tightly coupled process. And while no doubt similar strategies are employed by many of the traders, if they are liquidity or information oriented, they are not going to be subject to reinforcing feedback. The sort of trading strategy that could be a problem is a trend following strategy with participants piling on in ever-increasing size. And, again, you don’t need a computer to have that occur.
I think the popularity of high frequency trading will end not with a bang but a whimper. As the field gets increasingly crowded, market impact will rise and opportunities will diminish. Day by day more and more of the high frequency traders will see small negative numbers rather than small positive numbers in their P&L columns. The nice thing about high frequency trading is that it doesn’t take long to know if a strategy is working or not. The trader gets many draws of his strategy every day. And there is no cost to closing a strategy down – often every position is set to zero at the end of the day.

July 17, 2009

Goldman and High Frequency Trading

July 17, 2009
There is a funny attempt at logic going around in trying to explain Goldman’s high earnings:
1. Someone has been charged with stealing code from Goldman, code used for high frequency trading.
2. Goldman made tons of money last quarter.
3. Therefore, Goldman made its money from high frequency trading.

This argument not withstanding, I doubt that Goldman is making much of its money from high frequency trading. For one thing, high frequency trading does not have a lot of capacity. For another, why bother with high frequency trading, an area where there are relatively low barriers to entry and where you have no particular comparative advantage, when you have a screaming money-making franchise that is close to unassailable?

I even wonder if the code really was for a high frequency trading operation. Prosecutors want to paint the most extreme picture possible. So if you listen to them, you will come away thinking the code not only made untold millions for the firm, but if put in the wrong hands it could destroy the Western world. And the person accused of the theft, Sergey Aleynikov, would have had an interest in exaggerating the value of his work to potential future employers – at least before he was apprehended. Granted it might have been valuable for a high frequency shop, but it is more likely is that this code was one component of a broader trading operation, a way to efficiently execute trades, to add value to other systems. We do know, for example, that Goldman – like others – has substantial infrastructure for automated trade execution algorithms as a part of its market making and brokerage business.

More interesting than what this alleged code theft might tell us about how Goldman made money is that it highlights that we have no clue how the firm really did make money. And, more to the point, that the regulators have no clue.

Imagine if early into the current crisis the New York Fed’s Division of Bank Supervision had performed a routine analysis to see where the banks’ profits were coming from. That question would have led to the burgeoning structured products markets. The next questions would have been – or at least should have been – whether those profits came from cutting corners in terms of risk or compliance. Or, whether the scent of yet larger profits might lead to future corner cutting. I gather that such an exercise never took place. (I also wonder why there hasn’t been more finger pointing toward the Division of Bank Supervision, but that is a different matter).

Well, we missed on that one. But maybe it is worth learning from the past and begin asking those questions of the banks as part of the supervisory process. Banks have plenty of ways to make money through questionable means and through imprudent risk taking. Come to think of it, if we ever get to the point of having hedge fund regulation, maybe the regulators should ask the same sorts of questions there, too.

I am in the middle of writing a novel that begins in the midst of the 2008 crisis. In the novel there is an investment bank where one of the trading units gets requests from its clients to price their illiquid inventory. (This is an exercise that occurs in real life, because the clients have to mark to market, and for some assets there is no market. So they go out and get bids from a couple of banks, and then mark at the average of these two prices). This trader puts in incredibly low-ball prices. One bank prices a security at $92. He prices it at $50, leading to a mark to market price of $71. The trader knows that with such a low price, the client will be forced into liquidation mode. The trader positions his book for the forced sale that he helped precipitate, generating big profits from his scheme. This is fiction. But if we have learned one thing over the past couple of years, in the world of finance truth can be stranger than fiction.

July 16, 2009

Regulating Hedge Funds -- My Testimony before the Senate Banking Committee

July 16, 2009
I had the opportunity to testify yesterday on hedge fund regulation before the Senate Banking Committee. Here is my written testimony.

June 22, 2009

The 7 Habits of Highly Suspicious Hedge Funds

June 22, 2009
Note: This post will appear in The Journal of Investment Management

You've heard this story before: A trader at a bank is knocking the cover off the ball. His success garners political power within the bank. He creates a fiefdom that insulates him from the rest of the firm; his trading group explodes in size. He lives a conspicuous, extravagant lifestyle. His ego alienates the management and intimidates the support staff. Then the trader hits a rough patch. He uses all the tricks in the book to keep his poor results under wraps while he tries to find a way to recoup. Everyone is gunning for him, so he has to get back into the black, and fast.

How does he try to do that? He ratchets up his risk. He knows he won’t be able to turn it around fast enough if he plays it prudently, whereas there is some chance to stay in the game if he bets it all on 00, or better yet, if he levers up as much as he can, borrows all the money he can get his hands on, and then bets all of that on 00. If he loses, well, he was going to be gone anyway, so he may as well try for the big time.

That is one of the reasons there are risk managers. Risk managers know to put extra focus on traders who are struggling and, for that matter, on traders who seem to have an eerily hot hand. Especially if those traders have the ability to lever and to obscure their risk through the use of sophisticated instruments.

This story is now primed to play out in the hedge fund space. How many hedge funds do you know that more or less fit this description: A hedge fund manager had a run of great returns. His fund has grown by leaps and bounds. He has doubled his staff year after year in anticipation of even greater things to come. He has enjoyed a Page Six lifestyle; he is the belle of the ball, his dance card always filled. But now his kingdom is under siege. Assets under management have dropped precipitously due to redemptions layered on top of poor trading results. The investors that remain are demanding reductions in management fees. Incentive fees are gone until he scales the wall to get back to high water mark. With the way his operation has ballooned, he realizes that if he doesn’t make serious returns over the next few years, he will be crushed under the costs and the dwindling asset base.

What does he do? If he follows the same course as the trader at the bank, he will try to find ways to take on more risk. Of course, any investment fund might face the same temptation, but hedge funds have more tools at their disposal to make good on the try. Hedge funds can lever, delve into wide-ranging and risky markets and readily employ the so-called innovative securities to increase risk in ways that are difficult to discern. And unlike the trader at the bank, the hedge fund can operate without anyone seeing what it is doing. No one is looking over its shoulder at the trading positions each night.

Is the risk management in place to deal with this scenario? Here are seven “habits” that an investor should look out for:

1. No independent risk reporting.

One lesson that has been driven home from Madoff is not to trust the numbers coming out of any fund. Or, at least, trust but verify. If things go wrong and that is what you relied on, you will look like a fool, or worse. The risk numbers must come from having a third party getting the fund’s positions and doing the analysis.

The risk reporting must go beyond the VaR numbers to include measures of leverage, concentration, degree of diversification and size in markets (to assess liquidity risk). Again, all independently provided.

The diversification and concentration are necessary because, as we now know all too well, the relationships between markets can change. These risk measures cannot be calculated simply by knowing how many markets the fund is trading. It is critical to know how linked the markets are; how concentrated positions are when aggregated across similar markets. With globalization, diversification opportunities aren’t what they used to be. And in any case, it isn’t much value to be active in twenty markets if two-thirds of the positions are in three or four markets that are closely related.

2. A change for the worse in the critical risk numbers.

When you get independent reporting, don’t stop with looking at these numbers as they stand today. Demand to know what they have been over the past years. Have the risk statistics changed for the worse? Have they been different than what was represented by the fund’s own, internally generated reports? For example, is the third-party view of leverage, liquidity or diversification as favorable as has been represented by the fund itself, both now and historically?

3. Increased use of derivatives.

In my recent Senate testimony, I said that derivatives are the weapon of choice for gaming the system. Among other things, derivatives can be used to hide increases in leverage. Their complexity and difficulty in marking means that they also can more easily hide losses. There should be extra concern if the fund has only recently decided to start using derivatives and swaps.

4. High level of secrecy.

Does the fund have a monolithic, scripted presence to outside investors? Does it obscure its approach with secret formulas and strategies? Does it invoke its need for secrecy to justify limiting access to essential risk information and to its production staff? If so, you might want to get ready for a Madoff moment.

5. Growth in headcount and lifestyle.

This is the firm’s equivalent of the trader’s lifestyle. The fund’s principles can stretch the envelope in terms of personal lifestyle, and, unlike their banker cousins, their firm is their own domain. They can get an “edifice complex”. If a firm has become bloated, if it has a growing cost base that forces it to be impatient, then it will be more desperate to swing for the fences.

6. Decline in assets under management.

This speaks to motive. The more assets have declined – or are projected to decline with expected redemptions – the greater the stress for the fund, and the more tempting to ratchet up the risk.

Related to this, is the fund far below high water mark? Hedge funds make money from fixed management fees based on assets under management and incentive fees based on the return they generate for their clients. Most hedge funds only start collecting the incentive fees after they get back to high water mark. If a hedge fund is thirty percent below high water market, it may need years of strong returns before any money starts ringing up in the incentive fee register.

7. Lackluster performance in recent years.

Most everyone was lackluster this past year. So you should look back at the recent performance before the 2008 debacle. A comparison of the performance over the past three to five years versus the performance in the more distant past can be an indicator of a failure of the fund’s inherent strategy. It could be that the space has become too crowded and competitive, that the fund has become too large to take advantage of inefficiencies, or that the inefficiencies the fund has focused on have closed down. This creates a pressure to reach. If things have been slowly petering out, if alpha has been diminishing, then more leverage and risk is needed to get back up to the target.

Or, in desperation, the fund might try something new. So a related phenomenon will be style drift or a move into new markets and strategies. Style drift can be an indication that the bread and butter strategy is not pulling its weight. Is there movement toward new markets, a.k.a. ‘new opportunities’. Is an equity fund hiring expertise to gear up in credit, is a macro fund starting to trade volatility?

Not everyone standing in the shadows is a mugger. And sometimes a cigar is just a cigar. Although "habits" like a lack of independent reporting are pretty obvious weaknesses, others, such as exploring new trading strategies, might be justifiable. But these are warning signs that justify deeper questioning and tighter oversight.

June 12, 2009

Citi 2015

June 12, 2009
The most exciting times in my career have not been when money was rolling in and everyone around the trading desk was sharing high-fives. It was when we were fighting to survive, when we were huddled in a boat in the middle of the stormy sea. That was the world of Salomon in the mid-1990s, when we were one step away from becoming non-investment grade. It was us against the world.

I visited Citigroup a few times over recent weeks and it reminds me of those times. Granted, it is not the world in which you would want to have found yourself. People have lost much of their wealth, in some cases they have had to make painful shifts in their lifestyle. They are seeing their compensation potential capped while competitors are being unshackled. They would be justified in feeling bitter for taking the brunt of all but criminal behavior by past management, head traders and risk officers.

But there are the seeds of a vibrant risk-taking culture. Not risk taking in the trading sense, but in the sense of moving beyond the complacency that comes with success, of being able to reinvent and create because they have to, and pulling together because there is no other way to survive. Taking the compensation out of the equation, I would take that over the gilded world of a bank that is doing everything right but is entrenched and self-satisfied. (I know someone is going to make an ‘other than that, how did you like the play, Mrs. Lincoln’ comment).

What will Citi look like in 2015? Using the Thomas Friedman approach, extrapolating out from a few random conversations in one corner of the firm, it looks like management is forcing a business focus that Citi has not had in the past. We also might see those who have lived through this crisis and stayed on forge working relationships, communication and determination that will change the core of the firm in a way that can’t be done with big pay checks. (More comments coming).

Right now the world is looking at the tactical issues, on where Citi will be in the next quarter or next year – will Citi stay alive and retain talent, cope with the psychological effects of life-altering economic losses. But looking out five or six years, I see the potential for Citi to be transformed. And in the process have a stock price that will greatly outperform its competition. For anyone who wants to put this in their calendar to remind me six years hence, my bet is that the stock price will be up over six-fold.

The Citi of the Weill era brings to mind visions of Jabba the Hutt. Indeed, I devoted a chapter of A Demon of Our Own Design to the inevitability of crisis at Citigroup. And it could have stayed that way for years to come. Surrounded by a sycophantic Board, a stock price languishing and opportunities passed by. Until, maybe decades into the future it would have finally, somehow, sunk under its own weight.

But now Citi has the opportunity to reach back into its genetic pool and emerge with the scrappiness and focus that Salomon had in its heyday. And it has something Salomon never had: a tremendous reach and franchise.

June 6, 2009

Tasks for the Systemic Risk Regulator

June 06, 2009
As policymakers look to establish systemic-risk regulators, information is the key to success.

Note: This article was published in Institutional Investor magazine.

The more we understand about our wrecked financial system, the greater the clamor for a systemic-risk regulator. We want someone to save us from ourselves — or from the financial engineers who could blow the whole thing up again a few years down the road. Demand for a risk regulator, an idea that arose from the Treasury Department early last year, has now been embraced by the Group of 20 nations. Everyone wants a cop on the beat. But what would such a regulator do that the hodgepodge of current regulators cannot?

To answer that question, let’s first understand what we mean by systemic risk, and why it needs to be monitored. Systemic risk is driven largely by leverage. Leverage — borrowed money — is the force that amplified risk in the meltdown. Investment banks that once borrowed $10 for every dollar of equity were allowed to boost that to more than $30. As for hedge fund leverage, well, we can only guess. When a market downturn forces such highly leveraged investors to sell to meet their margin requirements, a crisis can cascade quickly. Selling pushes prices down, leading in turn to more forced selling.

The downward momentum is just the start of the problem. Many of those under pressure discover they no longer can sell in the market that is under stress. If they can’t sell what they want to sell, they have to sell whatever else they can, which leads to a downward spiral. This phenomenon explains why a crisis that started in the hinterland of subprime mortgages spread through the credit markets generally.

This contagion can expand beyond natural economic links. When the silver bubble burst in 1980, for example, the price of cattle suddenly came under pressure. Why? Because when the Hunt family had to meet margin calls on their silver positions, they sold whatever else they could. And they happened also to be invested in cattle.

To regulate systemic risk, then, we must understand systemic leverage, crowding (that is, when many speculators move into the same trade, pushing up prices in the process) and aggregated position holdings. Whatever their own risk-management capabilities, individual institutions cannot protect against systemic risk because they do not have this broader information. It is as if each player is sitting in a theater unaware of the others who might run for the exit.

Under current arrangements, regulators also lack the data to monitor systemic risk. They cannot track the concentration of investors by assets or by strategies, nor can they assess the risks inherent in the huge swaps and derivatives markets. Thus, they cannot map out how a failure in one market might multiply into others.

To solve this problem, financial products should be monitored the same way that food and drugs are. When salmonella was found in a peanut factory in Georgia in January, the Food & Drug Administration identified the contaminated products and tracked them all the way to the store shelf. This was possible because consumer products are tagged with a bar code. Why don’t we do the same for financial products? Require tags — bar codes if you will
to be attached to financial products so that regulators know what products are being held by each bank and hedge fund. This step would allow us to understand the potential for crisis events to have systemic consequences and help us anticipate — and hopefully prevent — the course of a systemic shock. It would allow us to identify situations where investors, even though they might be acting prudently on an individual level, are posing systemic risk through their aggregate positions.

Regulators also need to hold bank risk officers accountable. Why financial institutions ended up in such a mess is not much of a mystery. It was not the malfunction of sophisticated risk models or some 100-year flood that swamped the risk controls, it was a huge and unrelenting inventory buildup of illiquid and often complex securities — a buildup that was there to be seen and corrected. How did so many people miss this elephant in the room?

One likely factor is that the problem was passed up the chain of command until it got high enough to be ignored. In other words, the risk management failure within the banks was largely organizational; it had to do with incentives, lack of communication and plain old-fashioned bureaucracy.

To deal with this potential source of failure, the systemic-risk regulator must have direct lines of communication to the chief risk officers of major financial institutions. The regulator can act as the CRO’s ombudsman, an outside voice with the power to get things done if the risk officer’s own voice is not being heard within the firm. Having a link with the CROs of major banks and hedge funds would also allow the systemic-risk regulator to discern "flavor of the month" strategies and instruments that might portend crowding.

In addition, the regulator needs the capacity to learn from market crises. Imagine if the National Transportation Safety Board did not bother to investigate crash sites or review flight recorders. Yet that is where we are in the financial sphere. In the aftermath of a market crisis, regulators must analyze the firm-level details of what has occurred. They also must eyeball new financial products for their systemic-risk potential. Does a new product increase the complexity or leverage in the marketplace? Does it make the market more opaque? This gets back to data: You can’t manage what you can’t measure, and you can’t measure what you can’t see.

Finally, for a systemic-risk regulator to be successful, we must change the mind-set behind regulation. Marching into a bank with a subpoena in one hand and a 60-page questionnaire in the other is not the way forward. Systemic-risk regulation is rocket science — and is probably beyond the experience of even the best lawyers at the Securities and Exchange Commission and bank supervisors at the Federal Reserve Board. We need to entice market professionals into government service. It might cost some Wall Street–type money to get them on board, but the bill will be way south of the $1 trillion or so we’ll spend on the bailout.

Adopting this strategy will not be pleasant; it will mean stepping on a lot of toes. But it doesn’t have to be tackled all at once. The first step — getting the data — is the critical one. Data can be collected efficiently and maintained securely by the regulator, starting first with the largest banks, then gradually moving to other banks and the larger hedge funds. The process of collecting the data can provide the inroads for connecting with the CROs and amassing industry expertise. And if we let the data speak, we will learn more about how to pursue the other tasks.

June 5, 2009

Derivatives Reform -- My Senate Testimony

June 05, 2009
I testified before the Senate yesterday in the hearing "Regulatory Reform and the Derivatives Markets". This is my written testimony. It was a well-constructed hearing with good representatives for a number of views and good questions from the Senators.

The testimony was treated at length in the New York Times.

Here is my previous testimony to the Senate and to the House.

Note: For those who are not familiar with the regulatory structure in the U.S., the Agriculture Committee historically has had oversight for the CFTC, because up until a few decades ago all futures were agricultural commodities. Because of that, they also have oversight for derivatives. There is constantly talk about merging the CFTC and the SEC for efficiency of regulation, but there also is value in having them separate, so that we have diversification in oversight. The new Chariman for the CFTC is Gary Gensler (yet another former Goldman Sachs person), who has strong support from the Committee, so I expect this corner of our market regulation will be in good hands.

May 15, 2009

The Flight to Simplicity in Derivatives

May 15, 2009
Complexity is one of the demons that makes our financial markets crisis prone. Much of the complexity arises in the specter of derivatives and other “innovative” products. To reduce the risk of crisis we must exorcise this demon. We need a flight to simplicity.

Geithner’s proposal for new derivatives regulations, which includes centralized clearing and exchange trading for standardized derivative products, moves us toward this goal. A stated objection to this proposal is that the door remains open for complex OTC versions of swaps and derivatives. Or worse, that having the standardized products out in the light of day will only accentuate the demand for the more shadowy and opaque versions of the products.

I don’t think that is the way things will play out. More likely is that this proposal, properly executed, will be a major step forward in improving the transparency and efficiency of the market place, and will shore up the market against the structural flaws that derivative-induced complexity have created.

Assume we get to the point of standardized swaps and derivatives instruments that are exchange traded and backed by a clearing corporation. These instruments will create a high hurdle for any non-standard OTC product a bank wants to put into the market. The OTC product will have worse counterparty characteristics, will not be as liquid, will have a higher spread (which helps explain why the banks will decry this proposal) and will have inferior price discovery. To overcome these disadvantages, the specialized OTC product will have to demonstrate substantial improvement in meeting the needs of the investor compared to the standardized products.

Furthermore, the thought-leaders on the buy side will add their own hurdles to the more complex OTC products. I would not be surprised if many investors require derivatives taken on their behalf be of the standardized, exchange traded form, or that if an alternative is presented, it has to be approved by their firm’s CIO or risk manager. If this comes about, there won’t be too many instances where a complex OTC is pushed forward, because for most legitimate purposes the standardized products, on their own or in combination, will be found to do the trick.

Which gets us to the illegitimate purposes. Many of the complex innovative products are used for what might charitably be called non-economic purposes. Like allowing firms to lever when they aren’t supposed to lever, take exposure in markets where they are not supposed to take exposure, or avoid taxes that they are supposed to pay. I have discussed this more in an earlier post, My “Non-testimony” on the Regulation of Swaps and Derivatives.

If someone writes a history of innovative products, it will start with the golden era, when options and other derivatives were introduced to help investors better meet their investment objectives, allowing them to mold returns or, in the parlance of academics, to span the space of the states of nature. Then, somewhere along the line, an investor came to an investment bank and said, “Hey, I got a problem. You think you can help me out here.” His problem was something along the lines of, “My boss, he won’t let me trade mortgages, but I want to get my portfolio into these mortgages.” The ever-accommodating investment bank came back with an index amortizing swap.

Then – or maybe at the same time – the innovations went from "problem" solving to problem creating. Investment banks found clever ways to give their clients an extra twenty-five or fifty basis points by having them take on tail risks. These risks were subtle and infrequently occurring; most of the time things worked out. But every now and then, there were the blow ups; the likes of Orange County and P&G.

April 21, 2009

The Arms Race in High Frequency Trading

April 21, 2009
If the calls I am getting from headhunters are any indication, the hot area now is high frequency trading. And no wonder. There are two areas that were spared in the 2008 debacle: macro and high frequency trading. Macro funds on average were up ten percent or so last year because most of them skirted the edge of the major dislocations; their strategies focus on liquid instruments and are not oriented toward credit. High frequency trading did well because it thrives in an environment of high volatility and demand for liquidity, and 2008 was a hot house for both. Every year, people pile on to whatever strategy did well the previous year – this tendency is worth a book or two on its own – and so this year high frequency is destined to be the darling of the fund of funds.

But I think the days for high frequency trading are numbered. For one thing, high frequency trading is capacity constrained like few other strategies. The high frequency trader is basically a stand-alone market maker; he is sitting there to provide liquidity to others. And one way he provides it is to pull in the positions that others will shortly be demanding – thus the need for speed. If the footprint for high frequency traders gets too large, they become liquidity demanders themselves, and the gig is up. The Renaissances of the strategy will make their way through, but generally we will see a lot of shooting stars.

A second reason is that high frequency trading is embroiled in an arms race. And arms races are negative sum games. The arms in this case are not tanks and jets, but computer chips and throughput. But like any arms race, the result is a cycle of spending which leaves everyone in the same relative position, only poorer. Put another way, like any arms race, what is happening with high frequency trading is a net drain on social welfare.

In terms of chips, I gave a talk at an Intel conference a few years ago, when they were launching their newest chip, dubbed the Tigerton. The various financial firms who had to be as fast as everyone else then shelled out an aggregate of hundreds of millions of dollar to upgrade, so that they could now execute trades in thirty milliseconds rather than forty milliseconds – or whatever, I really can’t remember, except that it is too fast for anyone to care were it not that other people were also doing it. And now there is a new chip, code named Nehalem. So another hundred million dollars all around, and latency will be dropped a few milliseconds more.

In terms of throughput and latency, the standard tricks are to get your servers as close to the data source as possible, use really big lines, and break data into little bite-sized packets. I was speaking at Reuters last week, and they mentioned to me that they were breaking their news flows into optimized sixty byte packets for their arms race-oriented clients, because that was the fastest way through network. (Anything smaller gets queued by some network algorithms, so sixty bytes seems to be the magic number).

If we get out of the forest and look at what is going on, some questions come to mind. Does anyone really get a benefit in having the latency of their trade cut by milliseconds – except for the fact that their competitor is also spending the money to cut his latency? Should anyone care if a news event hits market prices in twenty-nine milliseconds rather than thirty milliseconds? Does it do anything to make the markets more efficient? Does it add any value to society?

We usually do not think about trading in terms of social value, but trading often does have social value, and it should. The objective of trading is to provide liquidity to the market, and to make sure that prices best reflect all available information – the usual efficient market argument we all grew up with. The solution? How about having everyone agree to standards in terms of hardware and related configurations. A high-frequency arms limitation treaty. We could call it HALT.

April 1, 2009

Measuring the value-added of hedge funds

April 01, 2009
The co-heads of Goldman’s Global Alpha hedge fund, Messrs. Carhart and Iwanowski, are calling it quits. A few years ago I was running a hedge fund at FrontPoint Partners and we were bought out by Morgan Stanley just in time to attend MSIM’s annual managing directors meeting. All they talked about at that meeting was what MSIM could do to be more like Goldman’s Global Alpha. It was a fierce machine, the gold standard. And it had some years of stellar returns. They rode their hedge fund up to a peak of $12 billion a couple of years ago. Since then they have seen it shrink to $2 billion.

If you are Carhart and Iwanowski, or for that matter AQR’s Asness or Citadel’s Griffin and have a really bad year, at least you can gain some solace by saying to yourself, “Things didn’t roll my way this year, but still, since inception I have on average delivered 15% returns.” Or putting the same sentiment differently, “Even though this has been a hard year, if you had invested $10,000 with me when I started, it would still be worth $300,00 today.”

Actually, no. If you use those benchmarks to define your career as a hedge fund manager, you are doing it wrong. Because hardly any of your investors did put their money with you way back when. In fact, most of them put their money with you over the past three or four years, years where returns moved from hum-drum to disastrous.

I have a hypothesis that would be easy to test with the right data: Some of the large hedge funds that have drawn down substantially in the past year or two have on net lost money for their investors since inception. This, even though they have collected huge fees and have decent average annual returns. The reason I think this might be the case is that in the current downturn they had a lot more money under management, and so had more dollars to lose per unit of poor performance, than when they were knocking the cover off the ball in their early years. Some of the hedge funds that are on the ropes grew larger and larger over time, reaching elephantine size just in time to implode. Some of these were starting to stumble under their own weight in the years before that.

A performance statistic to gauge the overall economic value-added for hedge funds is capital-weighted annualized returns. It would help to answer the question of a hedge fund’s – or the hedge fund industry’s – life-time economic value added; it would be useful even for large hedge funds that have not struggled the way that Global Alpha has. I don’t really care as much about what a $20 billion dollar fund did ten or fifteen years ago when it had $1 billion than how it did in the more recent years when it was trying to put these larger levels of capital to work.

March 20, 2009

Collective Punishment for AIG

March 20, 2009
I have heard the argument that those at AIG should not get bonuses because they destroyed the firm, or because they destroyed the firm and in doing so helped precipitate the current economic calamity to boot. This sort of argument doesn’t make sense to me. The vast majority of those in the bonus pool at AIG had nothing to do with precipitating the firm’s failure. They were marketing insurance products, managing call centers to handle customer inquiries, and other exciting stuff like that. They just happened to live in the same corporate city-state as the evil-doers. Pulling their bonuses based on such an argument is collective punishment.

A more reasonable argument is that without the government assistance, AIG would have gone bankrupt. And if it had gone bankrupt, those who are pulling in bonuses not only would have had no bonus, they likely would have had no job. So then, the argument goes, why should the government’s bailout money – which of course is tax payer money – go to give out-sized bonuses?

That makes sense. But then we come to some follow-up questions.

One is why Paulson didn’t include compensation controls as one of the terms for keeping AIG afloat. You could ask the same thing of Geithner, who frankly is taking on far more grief than he deserves, but the time to have done this was back when the government bought the majority stake in the company.

A second is why the argument stops with the boundaries of AIG. We should ask who beyond AIG would have gone bankrupt if the government did not keep AIG from default, and make the same demands on bonuses that are being paid there.

Think of it this way: If time had not been so tight, the creditors would also have been in the bailout meetings. These creditors would have include those on the hook in the event of default due to their CDS exposure. The meeting would have started off with Paulson saying, "We can pull AIG from the brink. It will take a lot of taxpayer money to do so. We want concessions all around, both from AIG and from its creditors, and especially from those creditors that will go under with it.

That is the correct route to collective punishment. A route that starts with questions like this:

True or False: If AIG had gone into default, Goldman Sachs would also have failed.

March 10, 2009

The Fat-Tailed Straw Man

March 10, 2009
My Time article about the quant meltdown of August, 2007 started with “Looks like Wall Street’s mad scientists have blown up the lab again.” Articles on Wall Street’s mad scientist blowing up the lab seem to come out every month in one major publication or another. The New York Times has a story along these lines today and had a similar story in January.
There is a constant theme in these articles, invariably including a quote from Nassim Taleb, that quants generally, and quantitative risk managers specifically, missed the boat by thinking, despite all evidence to the contrary, that security returns can be modeled by a Normal distribution.
This is a straw man argument. It is an attack on something that no one believes.
Is there anyone well trained in quantitative methods working on Wall Street who does not know that security returns have fat tails? It is discussed in most every investment text book. Fat tails are apparent – even if we ignore periods of crisis – in daily return series. And historically, every year there is some market or other that has suffered a ten standard deviation move of the "where did that come from" variety. I am firmly in the camp of those who understand there are unanticipatable risks; as far back as an article I co-authored in 1985, I have argued for the need to recognize that we face uncertainty from the unforeseeable. To get an idea of how far back the appreciation of this sort of risk goes in economic thought, consider the fact that it is sometimes referred to as Knightian uncertainty.
Is there any risk manager who does not understand that VaR will not capture the risk of market crises and regime changes? The conventional VaR methods are based on historical data, and so will only be an accurate view of risk if tomorrow is drawn from the same population as the sample it uses. VaR is not perfect, it cannot do everything. But if we understand its flaws – and every professional risk manager does – then it is a useful guide for day-to-day market risk. If you want to add fat tails, fine. But as I will explain below, that is not the solution.
So, then, why is there so much currency given to a criticism of something that no one believes in the first place?
It is because quant methods sometimes fail. We can quibble with whether ‘sometimes’ should be replaced with ‘often’ or ‘frequently’ or ‘every now and again’, but we all know they are not perfect. We are not, after all, talking about physics, about timeless and universal laws of the universe when we deal with securities. Weird stuff happens. And the place where the imperfection is most telling is in risk management.
When the risk manager misses the equivalent of a force five hurricane, we ask what is wrong with his methods. By definition, what he missed was a ten or twenty standard deviation event, so we tell him he ignored fat tails. There you have it, you failed because you did not incorporate fat tails. This is tautological. If I miss a large risk – which will occur on occasion even if I am fully competent; that is why they are called risks – I will have failed to account for a fat tailed event. I can tell you that ahead of time. I can tell you now – as can everyone in risk management – that I will miss something. If after the fact you want to castigate me for not incorporating sufficiently fat tailed events, let the flogging begin.
I remember a cartoon that showed a man sitting behind a desk with a name plate that read ‘risk manager’. The man sitting in front of the desk said, “Be careful? That’s all you can tell me, is to be careful?” Observing that extreme events can occur in the markets is about as useful as saying “be careful”. We all know they will occur. And once they have occurred, we will all kick ourselves and our risk managers and our models, and ask “how could we have missed that?”
The flaw comes in the way we answer that question, a question that can be stated more analytically as “what are the dynamics of the market that we failed to incorporate.” If we answer by throwing our hands into the air and saying, “well, who knows, I guess that was one of them there ten standard deviation events”, or “what do you expect; that’s fat tails for you”, we will be in the same place when the next crisis arrives. If instead we build our models with fatter and fatter tailed distributions, so that after the event we can say, “see, what did I tell you, there was one of those fat tailed events that I postulated in my model”, or “see, I told you to be careful”, does that count for progress?
So, to recap, we all know that there are fat tails; it doesn’t do any good to state the mantra over and over again that securities do not follow a Normal distribution. Really, we all get it. We should be constructive in trying to move risk management beyond the point of simply noting that there are fat tails, beyond admonitions like “hey, you know, shit happens, so be careful.” And that means understanding the dynamics that create the fat tails, in particular, that lead to market crisis and unexpected linkages between markets.
What are these dynamics?
One of them, which I have written about repeatedly, is the liquidity crisis cycle. An exogenous shock occurs in a highly leveraged market, and the resulting forced selling leads to a cascading cycle downward in prices. This then propagates to other markets as those who need to liquidate find the market that is under pressure no longer can support their liquidity needs. Thus there is contagion based not on economic linkages, but based on who is under pressure and what else they are holding. This cycle evolves unrelated to historical relationships, out of the reach of VaR-types of models, but that does not mean it is beyond analysis.
Granted it is not easy to trace the risk of these potential liquidity crisis cycles. To do so with accuracy, we need to know the leverage and positions of the market participants. In my previous post, "Mapping the Market Genome", I argued that this should be the role of a market regulator. But even absent that level of detail, perhaps we can get some information indirectly from looking at market flows.
No doubt there are other dynamics that lead to the fat tailed events currently frustrating our efforts to manage risk in the face of market crises. We need to move beyond the fat-tail critiques and the ‘be careful’ mantra to discover and analyze them.