From MarketWatch:
SAN FRANCISCO (MarketWatch) — The liquidation of a big hedge fund or investment-bank trading portfolio is wreaking havoc in some parts of the hedge-fund business, according to managers and investors.
Black Mesa Capital, a hedge-fund firm that uses computer models to track down investment ideas, said that at least one large hedge fund or investment bank is liquidating “massive” trading portfolios, according to a letter the Santa Fe, N.M.-based firm sent to investors Wednesday.
The warning is causing disruptions and triggering big losses among other so-called market-neutral hedge funds, Black Mesa said in its letter, a copy of which was obtained Thursday by MarketWatch.
“Clearly, something is amiss in the markets that few in our strategy, if anyone, have experienced before,” Black Mesa’s managers, Dave DeMers and Jonathan Spring, wrote. DeMers declined to comment Thursday.
The firm’s hedge fund, which has about $1.9 billion in long positions and $1.9 billion in short positions, was down roughly 7.5% this month through Aug. 7. Those losses could grow to as much as 10% for August so far, Black Mesa noted.
I love this quote: ‘Clearly, something is amiss in the markets that few in our strategy, if anyone, have experienced before.’
Something unanticipated is always amiss in the markets in these situations. That’s how these situations happen.
The MarketWatch article discusses big forced liquidations at highly leveraged hedge funds that trade according to finely tuned statistical models of market behavior. These models cannot anticipate every extreme chain of events. That is why such chains of events are called outliers. They happen more frequently in financial markets than naive analyses based on assumptions of statistical normalcy would predict. Every once in a while some risk event — in this case losses in marginal mortgage portfolios — triggers a perfect storm in some market or market sector. Less-alert, more-dogmatic and/or more-overleveraged fund managers get caught with sudden big losses and customer redemptions that force them to liquidate large portfolios, causing price losses in the underlying assets that lead to cascading liquidations from other holders of similar assets. The markets for the revalued assets eventually stabilize at lower price levels, firms go out of business and the process eventually repeats. Before it’s over, other types of assets may be affected in unpredictable ways (e.g., cattle futures prices declined sharply during the 1987 stock market crash as weak-handed stock investors liquidated unrelated futures positions to free cash for stock margin calls).
These events are difficult to foresee in particular but easy to anticipate in general, as was the case here. On the margin, professional fund managers buying securitized high-risk mortgage portfolios aren’t much different from ordinary people using easy credit to buy overpriced houses. Many people saw that the market was becoming overdone. The wiser fund managers, like the wiser home buyers, became cautious. The less-wise fund managers said, “We have this quant model for what we’re doing that shows a 25% annual return 99 out of 100 times in our simulation.” The problem is that models and simulations often understate risk; the “1-in-100” event happens in the thirtieth month, your fund is suddenly down 10% in a few weeks and your investors start asking for their money back. Repeat this scenario across the industry and pretty soon you have a big market event that few models would have predicted.
I am not arguing against quant models — far from it. I am merely pointing out that quantitative methods do not provide immunity against the weaknesses of human nature. Sometimes the model is wrong. Sometimes the model is OK but the fund manager needs to be wise enough to know when to override it. Market debacles will always be with us because there will always be people who aren’t wise or who use the latest methods to produce bad models.
The models used by rating agencies to evaluate the riskiness of pools of mortgages (and other forms of debt) represent an interesting case in point. Mortgage defaults, for example, are probably strongly (negatively) correlated with housing price trends. So there is a positive feedback loop (a vicious circle, with teeth) such that a temporary stall in price increases could lead to more defaults which leads to a further stall in price increases which leads to….
An article in a biz publication recently indicated that at least some of the models don’t even attempt to model the effect of price trends on defaults. Indeed, it’s not clear how one even could model this, without building a giant simulation that would also have to make assumptions about the credit policies of other mortgage providers.
Oh those rotten markets! They are not just sitting up, fetching, rolling over, and making me money! How can this be! My COMPUTER said to keep buying!
Ha.
A lot did not fit the bell curve today. Forced, or at a minimum, motivated liquidation. Likely a big long short “alpha” fund blowing its positions. One day people will wake up and ask “I’m paying 2 and 20 for this?”
It’s a joke on “investors” chasing performance. Same thing as in the past, different day.
This has been building up for a long time. For the last several years, the spreads between short-term and long-term, Treasuries and junk, have been at historic lows. In other words, some large classes of investors had become indifferent to risk.
Many hedge fund strategies have “short gamma” return distributions where the strategy makes steady money for years and then takes a big hit. The hits are exacerbated when more funds crowd into a trade and need to exit simultaneously, as happend in the stat arb strategies this past week. With more money continuing to pour into the HFs and the trades becoming more crowded the returns drop so the funds leverage the strategies further to make the same net returns. Couple this leverage with the Fund of funds phenomena which may lever their investments in other hedge funds up to 20X their capital and you get the possibility of a “great unwind”. Interesting times.
“Everybody” has known that house prices were too high for years … but like the 1996 exuberance in the dot.com market, waiting till after 2000 for the drop meant 12-15 quarters of steady upside before the drop.
The models are not yet predicting when the drop will happen, but nobody should be suprised that there is a drop. And hedge fund managers, in particular, should know about this — one main idea of a hedge fund is to make a low cost but high return bet counter to most of your investment, so that you have some upside to adversity. Insurance. Not high growth “low risk” speculation.
But, that’s what successful insurance has evolved into, in accordance with market evolution.