The Hedge fund as a stop-loss order

A stop loss order is an instruction given to a broker to trade a security to “limit” the loss in a position. So if you hold a share of Google and you don’t want to bear a loss greater than Google stock dropping below $400/share you could place a stop loss order with your broker to sell the shares if the price drops below $400/share. This limits your downside in the position though it can be a naïve trade. There is an analogous instruction you can do for a stop-loss for a short position you might hold.

There’s been a fair amount of research on the liquidity effects of stop-loss orders in aggregate. Notably the ’87 crash is attributed to wholesale program trading where a large number of stop-loss orders aggravated the crash. As asset prices fell on the exchange, algorithms at various trading houses kicked in to automatically sell holdings to prevent further loss. The tremendous selling pressure of all these algorithms acting at once caused prices to continue their precipitous fall resulting in a single 1-day drop in the Dow of 22%. In the aftermath academics and market big-wigs argued about the extent to which stop-loss orders were responsible for the ’87 crash and what remedies / safe guards should be put in place.

Hedge funds have been described as all sorts of things ranging from market-neutral, shareholder activists, the brain-trust of Wall Street and what not, including “liquidity providers.” When people think of hedge funds as liquidity sources, they have in mind the strategy where a hedge fund provides liquidity to the market by being a buyer of illiquid assets. For instance one of the strategies of hedge funds is to buy off the run treasury bonds say 28.5 years to maturity, and sell the on the run T-bond (freshly issued, actively traded). This strategy stays essentially risk neutral (with some term risk that I am sure they hedge cleverly) and provides liquidity to the market because otherwise the 28.5 year bond might trade unreasonably low in price (the liquidity premium acting here).

But I’m thinking of hedge funds as a liquidity sink rather than their other claims as market participants. A hedge fund raises some money, called equity, and borrows huge multiples against that equity and uses this pool of cash to make investments. When the fund’s strategies are working out, this leverage is helpful. It magnifies the returns of the hedge fund. When the returns are poor, it causes plenty of distress for the fund and if the distress is widespread, it hurts other market participants too. When the hedge fund is sitting on losing positions, it has to post margin in the form of cash to its lenders. This cash comes from equity. When the firm runs out of equity the lenders seize the assets and sell them (if the fund doesn’t do it first). You can now see how this is like a huge stop-loss order. The positions are deteriorating and the fund has to sell them in distress en-masse causing a further drop in asset prices. From the standpoint of a hedge fund investor, his hedge fund is like a stop-loss order; he makes an equity investment say $100 million and the fund borrows say $1 billion against that equity. When that equity is all blown away, the investor simply says “alright liquidate the fund, I don’t want to lose anymore money.” That’s your stop-loss order on an institutional scale. Add up enough of these happening over a matter of days and weeks and you have your liquidity crisis.

Correlations on returns on assets are an interesting topic in a liquidity crunch. There’s all kinds of research, published or not, on the correlations of various assets. The idea here is that investors want to feel diversified because they feel less exposed to risk that way. So researchers aggregate all kinds of market data, assemble returns (daily price changes in assets) and do correlation analyses on them. But naïve analysis like that misses the point. Diversification is most needed on the way down. It turns out correlations are not stationary (not fixed over time to put it simply). Asset returns frequently get more correlated when markets are falling. You can see how this might happen due to an imploding hedge fund. The fund has exhausted its equity and is taken over by its lenders. They look at the book and start unloading the most liquid assets to recover whatever money they can and work down to less liquid assets. So while the hedge funds losses may have been due to sub-prime mortgage assets it was holding, the first thing the lenders sell is stock holdings because they can readily be sold. The stocks may be in anything, a oil services company in Oklahoma, a textile company in China, whatever. Now all these stocks that have no apparent connection with the real estate industry experience a crash because they are being dumped on the market in spades. The investor who thought he was diversifying his risk watches all his assets go down together just when he needed the diversification. Hedge funds are of course not the only ones responsible here, but they are a big part of it.

Could you profit from it? Perhaps. If you keep spare, invest able cash and know what you want to buy you can wait around for a liquidity crisis. Whatever happened this month of August 2007 was described laughably by Goldman Sachs as a 25 sigma event that assuming normal distributions happens once is 1000000……… years. The naïve, perhaps irresponsible and mischievous assumption here is that such market outcomes are subject to normal distributions. This is written about eloquently by Nicholas Taleb in “Fooled by Randomness” and “The Black Swan” and reviewed very nicely here:
http://econophysics.blogspot.com/2007/05/black-swan-well-thats-life.html

In any case, these once in 1000+ year events seem to happen more like every 5-10 years. So if you do your homework and have the stomach to buy when everyone else is selling you could make a handsome profit. Or may be not…