Running a Large Trading Business is Hard: Surprise!

I feel for John Costas. I really do. Word this week that Dillon Read, the outsourced, hybrid proprietary trading/third-party asset management platform of UBS, will be winding up this week after suffering a loss didn't surprise me. Why? Because I know how hard it is to run one of these platforms, having run the DB Advisors organization which was similar in structure and spirit, and larger in AUM than Dillon Read. That said, I was fortunate to have been at the helm of an extremely profitable trading operation, even in the face of a high degree of complexity. And, like UBS, complexity was one of the reasons why we restructured the platform during my tenure. But at the end of the day only three things really matter:

1. Attracting and retaining top trading talent;
2. Creating and supporting a strong risk management culture; and
3. Possessing the psychological and economic wherewithall to withstand expected levels of volatility, even if the absolute numbers are, well, absolutely large.

Because if you lack any of these three things, you're toast. You are pre-ordinated to fail. And some of these things were clearly lacking at the intersection of the Dillon Read/UBS relationship.

Here is little extract from yesterday's article in the Financial Times:

UBS executives said the bank had underestimated the complexity of lifting the proprietary trading operation out of the investment bank and establishing it as a separate asset management business.

Peter Wuffli, UBS chief executive, said it had also “under- appreciated the synergies of a proprietary trading operation being directly integrated into the investment bank”.

But Mr Costas said returns from the $3.5bn proprietary fund had been at or above plan for 18 months until the subprime problems in the first quarter.

DRCM also struggled to raise money from external investors, attracting only $1.2bn for its first fund, which closed at the end of last year. This will be returned to investors.

Complexity of lifting out a proprietary trading operation? Depending upon the strategy or strategies being run, it can be truly mind-boggling. This is where my empathy kicks in. The first fund my team spun out of DB Advisors, QVT Financial, LP (which was running about $2.3 billion of assets at the time of spin-out) ran a large and complex multi-strategy book with hundreds of OTC derivatives positions (CDS, asset swaps, etc.), significant, concentrated illiquid asset positions and a raft of convertible bonds. They were (and still are) a top-performing fund with the rare combination of exceptional absolute returns and very low return variability. But theirs was not a plain-vanilla long/short book, to be sure. Their prime brokerage relationships were stunningly complicated. And they ran both proprietary and third-party money.

That said, we had a bunch of things working in our favor when it came time to spin them out:

1. Dan Gold, Managing Partner of QVT, is a super-smart, detail-oriented business builder that had a strong team to work on the spin-out process;
2. I had a great team working on my side to help with the legal and operational aspects of disentangling the QVT entity from the Deutsche Bank organization, including John Hitchon (one of the heads of Prime Brokerage at DB), Paul Bigler and Christine Morgan;
3. Dan and DB Advisors were able to undertake this year-long process - which was a HUGE distraction - without adversely impacting QVT's returns; and
4. Deutsche Asset Management, which was the fiduciary on the third-party monies run by the QVT team, worked hand-in-glove with DB Advisors, QVT and existing investors to make the transfer smooth and seamless.

This is what I said in the Financial Times about the DB Advisors platform at the time of spin-out:

DB Advisors was set up two years ago as a separate legal entity within Deutsche Bank and houses several internal hedge funds run by some of the bank's best traders.

External money is managed under the DB Global Masters programme and several single-manager funds.

Roger Ehrenberg, head of DB Advisors, said the departures were part of the "life cycle" of the business.

"We bring in top talent, provide capital to support varied investment strategies and, if desired by the manager, jointly execute a transition to independence with DB Advisors as a significant day one investor and strategic partner . . . we look forward to a long term mutually beneficial relationship."

But even in the best of cases this transition is a time-consuming, distracting, costly and gut-wrentching process. And the complexities of managing the legal and regulatory aspects of a hybrid proprietary trading/third-party asset management entity can be overwhelming, especially when you run a tight ship. I did it and and it is HARD. So in the UBS/Dillon Read case, the amount of the loss is likely not the driver of their folding, but the problems of performance (and, therefore, their inability to raise significant third-party assets) and the issues of managing such a complex organization. And these are good reasons for packing it in. Because if you don't have the demonstrated ability to attract and retain top talent, which enables you to build a diversified hedge fund trading platform, which enables you to produce attractive, low-volatility returns, which facilitates the raising of significant third-party money, you are just wasting your time. And this is what I am assuming my friends at UBS and Dillon Read concluded. It is a tough row to hoe, fellas. Just a little too tough, I guess.

Volatility Management in a Complacent World

Volatility has a corrosive effect on returns. Two cash flow streams that generate similar average returns, where one is more volatile than the other, can result in sharply divergent IRRs with the less volatile stream yielding the superior result. Therefore, it is clear that volatility reduction has a real and calculable value, but requires a probabilistic view of the world that is often difficult to quantify and harder to pay for. Further, sometimes the pressure for short-term returns can skew rational long-term thinking, causing an increase in the willingness to accept volatility that, in turn, further depresses the value of accepting such risks. And with this the cycle of complacency begins, is reinforced, and feeds on itself until the inevitable happens: event shock. And people will throw up their hands and say "Look at this tail risk; this is once-in-a-(decade/century/millennium) event." And those with a keen appreciation for such things will say - I told you so. "Fat tails" and "three sigma events" are now and have always been a relatively ordinary phenomenon. Tail risk is risk that can and should be priced and, depending upon your objectives and stakeholders, actively mitigated. But this requires discipline and cost, two things commonly lacking in those compensated for short-term objectives. And herein lies the issue.

The Economist has an interesting piece titled Sting in the Tail, positing whether low volatility is making the world too complacent about risk. There are some derivatives details in the article that I will address in a separate post that are either unclear or incorrect and, in my opinion, confuse the issue and muddy the picture unnecessarily. However, the questions raised by the article are spot on and important for investors and policy-makers to consider.

The International Monetary Fund's latest semi-annual Global Financial Stability Report is sanguine about concerns such as the American housing market. But it frets about a potential “volatility shock” in the financial system that could “precipitate sharp portfolio adjustments and a disorderly unwinding of positions,”—or, in other words, a panic.

The fund suggests the low volatility of recent years may be owing to greater economic stability, improved central-bank credibility or the better dispersion of risks around the financial system. But part of the explanation could also be cyclical, notably abundant liquidity, low borrowings by companies and high risk appetites.

********************

The IMF is unconvinced. It detects a worrying sign of complacency—“tail risk” in the options market. Ever since the crash of October 1987, when Wall Street fell nearly 23% in a day, investors have been sensitive to the risk of an extreme fall. They have been willing to pay a higher price (as measured by implied volatility) for extreme out-of-the-money options than for contracts that insure against smaller market declines. But this premium has been declining sharply in recent years. In other words, investors are becoming less worried about extreme events.

Since 2003, being blasé has been the most profitable strategy. Risky assets have performed well; for example, the spreads on emerging-market debt recently hit an all-time low. Market shocks have been subdued. Even February 27th's 400-point fall in the Dow Jones Industrial Average came low down the historical league table of percentage daily falls.

But what might cause risk appetite to change and volatility to soar? The simple answer is Harold Macmillan's phrase, “Events, dear boy, events”, perhaps some geopolitical incident or unexpected corporate failure. Emerging-market debt would be a big casualty of such a shift. The IMF reckons that, if volatility moved to two standard deviations above its post-1990 average, emerging-market debt spreads would more than double. Something to worry about indeed.

This interesting piece neatly raises at least five important issues that need to be considered as it relates to volatility and its relevance for investors and fund managers alike:

1. Have developments in the global financial markets - the rise of derivatives and risk dispersion, stronger, more competent central banks, and a more diversified base of economic power spread across countries, companies and currencies - conspired to reduce the "structural" level of market volatility?

I think the answer is yes. In general, diversification reduces the variability of outcomes, and with the increased diversification of both risks and economic power it must logically follow that some degree of variability has to have been stripped from the global financial markets. This doesn't mean that markets still can't get pushed out of whack or that exogenous, non-economic shocks (i.e., war, terrorism, etc.) don't have profound economic impacts that give rise to volatility. It only means that if one were to take a longitudinal view of global economic performance, that one would expect a less variable set of returns than previously generated in a world with greater concentration of risks and economic power. My only qualifier to this is: in a more complex, diversified world, does this possibly give rise to a third dimension of exposures related to the non-linear increase in the complexity of relationships managing the world's global economic resources? It was easy to navigate when you had a few economic superpowers and a few powerful financial markets. But what about now? The picture is painfully more complicated. And this might, in and of itself, effect the volatility landscape.

2. Are the perceptions of risk and, therefore, volatility, cyclical?

The answer is unquestionably yes. People and markets have short memories, and that is a fact. Which means that if liquidity is plentiful, spreads are tight and investors are looking everywhere for returns, spreads will continue to tighten as previously risky assets are no longer viewed as risky (i.e., high-yield debt, emerging markets debt and equities, etc.). This also means that those buying insurance are few and those selling insurance are plentiful, further depressing volatility and only amplifying the effects of a complacent market psychology.  Then seemingly out of nowhere - bang! Emerging markets debt spreads move from 200 bps to 1000 bps, equity markets drop 10-20%, and risk premia magically expand to meet the heightened anxiety and uncertainty. And this will persist for a while. Until people forget about the shock and it's once again business as usual. This is how it always has been and this is how it always will be. Will the current liquidity-fueled securities-buying boozer persist indefinitely? Of course not. It is just a matter of time.

3. Are the costs of insuring against tail risk relatively expensive?

Yes. And they always will be. Selling out-of-the-money put options is a risky business, and the implied volatility that is required to buy these instruments is generally very high. In fact, broker/dealers are not the ones best positioned to sell such instruments. While the implied volatility charged the buyer is relatively high the cost of the option is absolutely cheap, due to its out-of-the-moneyness and the low probability of its being exercised. Therefore, the broker/dealer selling the option is not making a whole lot of money even when charging high implied volatility, and the dynamic hedging (usually "delta hedging" - the probability-weighted amount of the hedge underlying that needs to be held based upon the spot price of the underlying and the remaining time to maturity) that needs to take place is subject to "gap risk." This basically means that when the dealer most needs to sell to adjust its hedge it will be forced to sell at progressively less attractive prices in a market meltdown. This is how dealers can lose hundreds of millions of dollars very, very quickly. However, insurance companies and others with durable, ultra-long dated asset portfolios can sell these options as a vehicle for enhancing returns (the flip side of covered call writing) without the need for dynamic hedging. Bottom line, implied volatility will always be high for these types of instruments, and necessarily so.

4. Can one generate seemingly superior short-term returns by avoiding the costs of insuring long-term risk?

Absolutely. Whether the investor is buying risky assets at progressively tighter spreads or selling optionality as a vehicle for collecting premium it hopes never to have to pay back (and then some), these activities generate returns that are relatively attractive when compared to common benchmarks. However, Mr. Market ensures that investors don't get something for nothing, so when that "unexpected" shock occurs - spreads blow out, markets drop and margin calls come knocking - the benefits associated with making short-term numbers look good are generally far outweighed by the costs associated with the unwinding of these risky asset/short-option positions. Messrs. Meriwether and Niederhoffer know all about this. So let's just say that investors should look pretty carefully at fund documents before investing, because often these documents give managers tremendous amounts of latitude, and one will need to dig pretty deep to properly analyze the quality of a fund's earnings. Is it due to good securities selection or an increase in portfolio risk? This is the question the needs to be answered.

5. Has complacency driven this historical tightening of risk premia across markets, to the point where it is poised to explode in the face of said tail events?

Oh, yes. I think liquidity is a great thing, except when it causes investors to make irrational decisions. Chasing returns. Getting away from a fund's mission. Assuming risks that are properly absorbed by those better able (and more appropriately positioned) to take them. And when the time comes, no amount of liqudity is going to buttress what looks like an inexorably declining market. Changes in market psychology can be abrupt and harsh. People and governments will move to the sidelines until the detritus is cleared, and this will take exactly how long? Who knows.

So where we are today is at a time when the costs of insurance are both relatively and absolutely low yet the urge is for investors to sell it, not buy it. Because short-term performance considerations (which directly drive most fund managers' compensation, as well as the ability to gather additional assets to manage) can often drive sub-optimal portfolio decisions. And this is certainly not good for fund investors. And it is at times like these when the smart, savvy, long-term oriented managers with an appreciation for history take a contrarian position. And I might wager that this is precisely what is happening. We'll see the wheat separated from the chaff in short order. Just wait and see.

Black Box Trading: Panacea or Promotion?

Without question, quantitative trading approaches - carrying names such as "black box trading," "algorithmic trading" and "statistical arbitrage" - are all the rage. Lumped in with these mysterious-sounding approaches are high-IQ terms like "pattern matching," "genetic algorithms" and "neural networks." At the essence of these strategies are two distinct features: (1) humans aren't involved in the decision-making process; and (2) models are designed to either "learn" like humans or to detect non-intuitive relationships among a sea of data that can't be readily seen by humans. Basically, creating models and approaches that are, ultimately, better than humans because they can act faster, trade more cheaply, make decisions dispassionately, process more information and see things humans simply can't due to the limits of our ceberal cortex.

An interesting article in Saturday's New York Times raises an array of interesting issues and uses a new hedge fund started by one of the brainiacs of all-time, Ray Kurzweil, as the vehicle for exploring this fascinating topic. For context, it should be noted that rocket-scientist types running hedge funds is not new: figures such as David Shaw (DE Shaw) and Jim Simons (Renaissance Technologies) have been using higher-order math and computer science to extract value from market data for the last three decades. These skills are now being more broadly applied to news feeds, government filings and other data pools where entities can be extracted, sentiment gleaned and metadata created and analyzed. Other hedge funds as well as both buy- and sell-side firms are using similar technologies and approches in their businesses.

The computerization of trading and investment is a logical and noble pursuit. However, attempts such as these are not without their pitfalls for a variety of reasons. Statistical arbitrage strategies have become progressively less and less attractive as more capital has flowed into the area. Where a super-smart quantitative manager could once design a high frequency, quasi-market making strategy that was both very profitable, required little capital and entailed a small degree of market risk, they now need to extend signal horizons and seek to generate returns by doing what everybody else does when they reach for return - take on more risk and accept greater variation in returns. Further, these high frequency strategies are often not very scalable, a real hinderance for a manager that wants to grow and leverage their brand into a multi-billion dollar operation. Returns in the various statistical arbitrage strategies display asymptotic profiles, where early alpha generation is eventually squeezed to zero as more brains and assets focus on the strategy in question. Managers innovate, enjoy attractive returns for a period after which they need to move on and develop the next set of algorithms. It may appear to a layperson that a black box trading strategy would be great - few PMs with huge egos, relatively modest investment in programmers and hardware to build a scalable platform and a nimble, easy-to-adjust model to adapt to changing market conditions. This, my friends, is simply not the case.

Consider the two black box managers with the most successful long-term records and asset growth - the aforementioned DE Shaw and Renaissance. They both have armies of PhD.s of all stripes - computer scientists, mathematicians, physicists, biologists, chemists, linguists, etc. This is not exactly the cheap and scalable infrastructure many have in mind. It takes a lot of money, relentless and effective recruiting and a culture to support the degree of innovation required to succeed. I think about it as the "cycle of the 4 M's:"

1. Man, who develops the
2. Model, which is operated by the
3. Machine, which executes the Model in the
4. Market, which generates returns, results in feedback interpreted by Man, who modifies the Model, etc.

It is usually not the cute, campy story of a smart technician with his trusty computer building a successful and scalable hedge fund. Few have done it well, and it remains to be seen whether Ray Kurzweil and his lot will be able to make it into the pantheon of black box gurus like David and Jim. Do these new entrants have brains? Yes, and often in spades. But success ultimately requires A LOT more than brains, like:

1. Managerial skill
2. Risk management skill
3. Recruiting skill, and
4. Business-building skill, to name a few.

So let's turn to the NYT story for their take on things. Some interesting excerpts from the NYT story are as follows.

But in recent years, as algorithms and traditional quantitative techniques have multiplied, their successes have slowed.

“Now it’s an arms race,” said Andrew Lo, director of the Massachusetts Institute of Technology’s Laboratory for Financial Engineering. “Everyone is building more sophisticated algorithms, and the more competition exists, the smaller the profits.”

So investment firms have increasingly begun exploring mathematics’ furthest edges and turning to people like Mr. Kurzweil, who became an expert in pattern recognition building a reading machine for the blind.

********************

So Mr. Kurzweil and others took a different tack: instead of creating sequential rules to instruct a computer to read, they thought, why not create thousands of random rules and let the computer figure out what works?

The result was nonlinear decision making processes more akin to how a brain operates. So-called “neural networks” and “genetic algorithms” have become common in higher-level computer science. Neural networks permit computers to create new rules and automatically change underlying assumptions by experimenting with thousands of random sequences and processes. Genetic algorithms encourage software to “evolve” by letting different rules compete, and combining the most successful outcomes.

Wall Street has rushed to mimic the techniques. Because arbitrage opportunities disappear so quickly now, neural networks have emerged that can consider thousands of scenarios at once. It is unlikely, for instance, that Microsoft will begin selling ice-cream or I.B.M. will declare bankruptcy, but a nonlinear system can consider such possibilities, and thousands of others, without overtaxing computers that must be ready to react in milliseconds.

********************

“The downside with these systems is their black box-ness,” Mr. Williams said. “Traders have intuitive senses of how the world works. But with these systems you pour in a bunch of numbers, and something comes out the other end, and it’s not always intuitive or clear why the black box latched onto certain data or relationships.”

********************

“Right now, everyone basically has access to the same data,” said John Bates, a Progress Software executive. “To get an edge, we want to give investors the ability to immediately turn news into numbers. We want to automate what before required human analysis.”

But as these new techniques proliferate, some worry that promotion is outpacing reality. These techniques may be better for marketing than stock picking.

“Investment firms fall over themselves advertising their latest, most esoteric systems,” said Mr. Lo of M.I.T., who was asked by a $20 billion pension fund to design a neural network. He declined after discovering the investors had no real idea how such networks work.

“There are some pretty substantial misconceptions about what these things can and cannot do,” he said. “As with any black box, if you don’t know why it works, you won’t realize when it’s stopped working. Even a broken watch is right twice a day.”

So what are some of the key themes? There is an

1. Arms race, being led by the development of
2. Better models, though
3. Machines lack human intuitition, but can benefit from
4. Digitization of data, which reduces the need for humans, but
5. Is the hype around black box strategies outstripping the reality?

The arms race has been going on for decades. This is nothing new. It is simply the nature of the arms race that has changed. The last leg of the race was largely played with hardware and platforms, with FTP, execution costs being driven towards zero, competitive, low-latency platforms, real-time architectures fueled by incomprehensible processing power and "smart" trade execution systems. But the arms race is changing, with the next leg being driven by highly intelligent software and models. Programs that can take in feeds across different formats, analyze (and possibly create) the metadata at lightning speed, look for statistical and linguistic relationships among elements in the data set, and "learn" from history through enhanced algorithms leading to better performance. Ok, I get it. But it still doesn't answer the question of whether or not these new entrants will have the stuff to generate consistent, sustainable performance across a progressively larger asset base without killing returns and/or blowing up.

I wonder if this new-found emphasis on black box trading will, over time, drive alpha back towards the fundamental bottoms-up strategies. And I'm really not sure if neural networks, genetic algorithms and other ultra high-IQ approaches really change the calculus of how the markets and investor behavior works. Capital tends to flow from the "cold" strategies to the "hot" strategies, which naturally causes hot strategies to become cold and vice versa. Anyone remember convertible arbitrage? What was a darling in 2000-03 was a dog in 2004-05 and a darling once again in 2006. This is an inexorable game of "asset allocation tennis" that has taken place (and likely will continue) for time immemorial. So does it really matter if ever-more sophisticated tools and techniques are used? Or is Ray Kurzweil's knowledge base and its application to the markets so differentiated that he will enjoy a competitive advantage for a material amount of time that would enable him to build a true hedge fund firm with a lasting legacy? Maybe, but I'm cynical. No knock on Ray (he is clearly one of the most brilliant thinkers of our generation), but I think there are enough brilliant minds working in enough related areas with enough access to capital to make any demonstrable advantage fleeting at best. Call me a cynic, but after 20 years kicking around the markets and with a sense of history it takes a lot more than a few good years to convince me that a new paradigm is upon us. Only time will tell.

More on Derivatives - Necessity vs. Novelty

First of all, I'd like to thank the folks over at the FT for taking my somewhat tough post concerning MSM's depiction of Wall Street trading risk so seriously. They put up a post in their blog, Alphaville, about my emotional (passionate?) missive in Information Arbitrage yesterday. I had to crack up when their lead-in was as follows:

In the blogosphere, the mainstream media, the FT included, has got Information Arbitrage’s Roger Ehrenberg, the former head of Deutsche Bank’s fund of hedge funds and president of Monitor110, all hot under the collar.

********************

“A $120 million loss on a trading desk, unless the loss was the result of poor controls or a rogue trader, is neither a show stopper nor something that warrants intense eyebrow-raising and upset stomachs.”

Message received loud and clear, Roger.

Bottom line: they heard me. That's pretty cool - thanks, Alphaville. I don't know whether or not it was coincidence, but the FT had two very interesting stories yesterday on the issue of derivatives that I believe warrant discussion. But before that, let me tell you my view of the evolution of the derivatives marketplace since the early 1990's.

My 2 Cent Perspective on Derivatives History

I think the early-mid 1990's could be characterized as the wild, wild west period of the derivatives markets. A bit of a gold rush mentality prevailed across most asset classes. Interest rates were low, companies frequently viewed their Treasury operations as profit centers and people sold crazy, crazy instruments to banks. Sales of naked options - principally variations on interest rate puts. Leveraged derivatives (does anyone remember the LIBOR-cubed swaps?). Pure punts via "index amortizing swaps" calibrated to a particular rate view. Risky and massive mortgage books that served to underlie MBS pools. At the same time, banks built huge portfolios of complex correlation risks while the risk management systems themselves weren't yet sufficiently evolved to deal with these mounting exposures. You can think of the risks inherent in this market environment as something akin to a Ferrari attempting to traverse the cobblestone streets of Rome at 140 mph. Someone is going to hit the wall. It was inevitable.

Then came the Fed's 300 bps increase in rates starting in early 1994. The party was over, and the derivatives speculators (note that I use this word and not the word "hedgers"), in general, were caught off-guard. This includes both corporate sellers of volatility who were simply trying to collect premium they thought (and hoped) they wouldn't give back (which they did, in spades) and trading desks that were also poorly positioned for the flattening yield curve environment. MBS buyers also got clobbered as duration was extended in a rising rate environment. And all of this happened in the face of one of the steepest yield curves in history, with short rates pegged at 3% and the long bond trading at 8%. Remember why a yield curve slopes upward? The interest rate market's expection of higher future rates. Did this scare people? No way - sell forward optionality! Harness that steepness to collect premium today which hopefully won't have to be paid back later. And this is why things got really ugly when the Fed took the punch bowl away.

First came the P&G/Bankers Trust debacle. A corporation taking a $200 million trading loss on a "hedge?" Sure, a "hedge" that had a duration of 125 years (which offsets precisely what exposure in the business?). Then Air Products. Then Gibson Greetings. And countless other corporations of scale who lost hundreds of millions of dollars when they had to mark these derivatives to market but who suffered in silence when the losses hit. And, of course, the corporations blamed the banks for fleecing them (which is a bunch of crap, to be sure, but hey, you gotta blame somebody other than yourself). Bottom line - a little bit of the luster came off of the derivatives market, but even if corporate use of these tools slowed during the 1994-1996 period, institutions and governments continued to use these tools in quantity.

As the late 1990s/early 2000s rolled around, there was a key theme that precipitated the exponential growth of the derivatives marketplace: the blurring of the lines between debt and equity. First the equity derivatives marketplace really exploded, with an amazing amount of innovation benefiting investors and issuers alike. Structured convertible bonds that lowered issuance costs for corporations, equity hedging strategies that created extremely flexible, cash-efficient share buyback programs, private convertible instruments to monetize appreciated stock positions, portable alpha strategies for pension funds, and on and on and on. At the same time, the concept of "capital structure arbitrage" was born, emerging from either the convertible trading desks or the credit trading operations of the large Wall Street firms. This strategy of trading the different strips of the capital structure was facilitated by an innovative but very straight-forward tool - the credit default swap (CDS). CDS allowed credit buyers and sellers to use derivatives in lieu of the actual instruments to create a position. It was this emergence that, to me, accelerated the blurring of distinction between debt and equity. Artificial barriers would no longer be tolerated. How can you optimize the trading of equity without taking advantage of the information and liquidity inherent in the debt? And this, in turn, set in motion the innovation we have continued to witness over the past five years.

CDS, LCDS, CBOs, CDOs, CLOs - these tools have emerged to help buyers and sellers get what they want, either in terms of risk transfer or portfolio return objectives. As these markets have grown they have become more standardized, and issues of weak documentation are being dealt with aggressively by Wall Street trading desks and their counterparties alike. I am sure, by now, you are completely nauseated by my little missive on derivatives history, but I have done this to prove a point - when instruments are created that generate real value, the markets explode. When they are mere gimmicks that fail to materially enhance one's ability to either make money or manage risk, they falter. And it is here that I'd like to turn to the two stories in the FT.

When Derivatives are Necessary - A Market Emerges

Richard Beales' article drives home the point that innovation has been rapid and has created real benefits, but not without some concerning arising from fears over how the markets will handle stress and unacceptable levels of undocumented trades:

The pace of financial innovation is quickening. Products that barely existed a few years ago are already multi-billion-dollar markets.

Derivatives and structured instruments have evolved particularly quickly across the capital markets, especially in the worlds of credit, equities and commodities.

Many of these innovations benefit the financial system because they help disperse risk more widely, analysts and regulators say. But there are concerns as they have come at a time of economic growth, low interest rates and low volatility.

********************

Other novel instruments are also designed to serve a practical purpose. Loan-only credit default swaps (LCDSs) allow lenders to hedge exposure by buying a type of insurance or protection against the borrower's default – though they also allow hedge funds and others to take positions without owning the underlying debt.

The LCDS market is an offshoot of the still rapidly growing market for basic credit default swaps, the most common credit derivatives. While CDSs enable market participants to buy and sell protection against default on unsecured bonds, LCDSs are designed to track the credit of secured loans.

********************

Innovation brings challenges for regulators. In the credit derivatives world, US and European regulators have also had a hand in encouraging the finance industry to put its house in order. Last month was the anniversary of an initiative to clean up paperwork problems and increase automation in the industry.

The Federal Reserve Bank of New York, which hosted a meeting of 16 dealer banks and their regulators, welcomed progress in cleaning up the backlog, which a year earlier had been seen as a potential threat to the stability of the financial system.

But in a sign of the pace of innovation, the regulators' attention is shifting to other parts of the derivatives world, such as equity derivatives.

"We look forward to seeing the industry improve the automation and standardisation of over-the-counter equity derivatives trading and reduce the current levels of unconfirmed trades," said the New York Fed.

********************

Sure, when you are building a trillion dollar market there will be bumps in the road. But when you look at the ability for issuers and investors alike to:

1. Benefit from enhanced liquidity;
2. Transfer risk to those best able to absorb it; and
3. Access a vehicle for taking a holistic view of the capital structure and to express a view in a variety of different manners and market

It is hard to underestimate the value of this innovation.

When Derivatives are a Novelty - The Market Flounders

Saskia Scholtes also had an interesting piece on the equity default swap (EDS) market, which has has languished since its development in 2003:

Of the many ideas thrown at the wall by investment banks eager to develop the latest must-do derivative, not all stick that well.

One product that appears to have been consigned to the derivatives larder for now is the equity default swap.

********************

Launched in 2003, when memories of the bursting stock market bubble were still painfully fresh, the concept was logical, say investors.

But equity market volatility has subsided and the attraction has waned. Protection against a fall in share prices is also easily achieved with a simple put option. The promised growth in EDS trading volumes may be on hold, at least until the next bear market.

********************

The idea was to allow banks and investors to fine-tune their positions further. But one credit hedge fund manager suggests that this added level of complexity may have been "one step too far" for broad-based market adoption.

The key take-away here is that innovation for innovation's sake simply doesn't work, even in the "arcane and esoteric" world (needless to say, I am being extremely sarcastic) of derivatives. The market knows what it needs, and when smart people come up with smart ideas there is rapid adoption followed by exponential growth. It is good to know that there is a self-policing mechanism in place called Mr. Market which makes sure necessary ideas are rewarded while others fall by the wayside. This is the way it should work, right?

Pricing Event Risk and the CDS Market

Much has been written lately about those getting smashed in the credit derivatives market, particularly in the wake of several recent corporate reorganizations that have introduced new and unexpected volatility into the marketplace - spin-offs, split-offs, new financing entities, subsidiary IPOs, etc. The ball kind of got rolling with VNU's subsidiary financing, and has picked up steam in light of Verizon's announced spin-off of its directories unit. Bloomberg issued a story today that highlighted some of the heated emotions over this issue:

Hedge Fund Nightmare

The predicament is akin to battling a rare disease because of the more than 1,000 companies with credit-default swaps bought or sold this year, fewer than 3 percent triggered price swings related to a change of corporate control, or so-called succession event, according to data from Frankfurt-based Deutsche Bank AG.

For hedge funds, unregistered pools of capital where managers participate substantially in the profits of the money invested, the volatility of credit-default swaps is a ``nightmare,'' said Simon Ballard, head of research in London at ARC Securities Ltd., a fixed-income broker. ``Credit derivatives have underpinned the evolution of the hedge fund community for the last few years.''

New York Fed

Even the International Swaps and Derivatives Association, the trade group that has championed credit-default swaps as tools to reduce risks in the debt market, is concerned that increased volatility shows the hazard that the contracts no longer reflect the value of assets they're mimicking.

These ``new problems'' are causing widespread confusion, said Kimberly Summe, ISDA's legal counsel in New York. Summe, who helps set the standards for credit-default swap contracts, coordinates a twice-monthly conference call with 150 bankers, investors and lawyers to tie the contracts more closely to a company's credit risk.

So far, regulators aren't voicing concerns. Last August, the Federal Reserve Bank of New York chastised some of the biggest financial firms, including New York-based JPMorgan Chase & Co., the third-biggest U.S. bank, and Goldman Sachs Group Inc., the most profitable securities firm, for allowing 150,000 credit-default swap contracts to remain uncompleted, leaving traders unsure of their obligations.

First of all, a 3% probability is neither akin to the risks of contracting a rare disease nor is it a "tail event." While there is surely improvement to made to the ISDA credit derivatives template, the bottom line is that this (the risks to CDS prices in the wake of corporate reorganizations) is part of the game. Credit risk is not a static measure, and the derivatives marketplace needs to incorporate the probabilities of restructurings and reorganizations into their prices for these instruments. Whining has no place in the markets, folks. People made boatloads of cash on the ride up, and as markets mature and time passes the ride occasionally gets bumpy. Sorry, that's life.

This reminds me of my days in equity derivatives in the go-go late 1990's, when M&A events and spin-offs of dot-com subsidiaries were all the rage. Say we were long some vega (optionality) on a stock (either by owning puts through a synthetic share buyback program or through a short put/long call sold as hedge of an investment position), and the company underlying our position announces a spin-off of its internet subsidiary. What happens? All of a sudden we have positions on two stocks instead of one. So what? The volatility of the basket of two stocks is less than that of the single stock that spawned the two, rendering our long vega position less valuable. Totally sucks, right? Right. But we survived and that was part of the game. The fact is that this potential outcome needed to be factored into our pricing when we initially provided the hedge.

I am glad to hear that regulators aren't freaked about the current situation. They shouldn't be. They were right to be concerned about the massive number of unconfirmed trades, a matter on which the Street has made tremendous progress over the past year. But regulators shouldn't be stepping in where market forces are designed to take care of the problem. Traders can price event risk. They do it every day. If swap spreads need to widen to take these risks into account, ok. But if they don't, all I can say is caveat emptor - and no whining, please.