Quant Funds; What Are They, and How Did Things Go So Wrong?

The Wall Street credit crisis. Its now infamous for anyone with any ear for market updates and news. The media can use it to explain anything, a minor slide on the ASX, or even predict the RBA’s next move. In short, investment banks have had to write off a lot of money in order to keep the books balanced. This causes panic in the market place, and stifles capital injection into markets. The cost of debt not only rises, but there’s also a reduction in leverage; i.e, the amount that a business can borrow per dollar of asset. People start fearing a recession. Fund managers trim their portfolios. But the overall economic outlook is good; emerging markets are strong, just about every other business is thriving. People are optimistic, in general. Its not time to start panic selling yet, not for everyone, anyway.

What are quant funds? Instead of taking the pain and effort of writing my own second rate summary, I’ll just steal it from InvestorsInsight:

Like stock fund managers, there are various breeds of hedge fund managers. Among equities, fund investments may be concentrated in companies or indexes of a particular growth stage, industry, or geographic area, such as Growth vs. Value, Tech vs. Consumer stocks, International vs. Domestic, etc. Many hedge funds also specialize in a particular field and are typically categorized as Global/Macro, Long/Short, Distressed, Quantitative, Market Neutral, etc.

Licensed for use from the New Yorker Magazine.

In the hedge fund world, the label “quant fund” has a distinct meaning, quite different than your plain vanilla long/short fund. But unless you knew better than most, differences may have been hard to distinguish until this fateful August.

The funds that got the most press were market neutral quant funds characterized by the “statistical arbitrage” or “algorithmic trading” models they used. These models allow a computer to scour historical price data for relative value inefficiencies between stocks, futures, currencies, or fixed income securities.

To better explain what happened to quant funds, I will tell a fictional story that is roughly based on the facts as we understand them at Altegris. I will change the names to protect the innocent (and avoid any litigation!).

Let’s create a hypothetical quant fund called the PhD Fund. The fund is owned by a big name Wall Street firm and is marketed on the street to wealthy individuals and institutions under the banner of a “market neutral” fund. This means that the net exposure for the fund is zero, or, in other words, the dollar amount of long positions in the portfolio is offset by the dollar amount of short positions.

The PhD Fund employs dozens of “propeller heads” (a hedge fund moniker for our mathematically inclined friends in quant shops). They build computer-based models that try to find and trade overvalued and undervalued stocks. Some of these models are longer term but some are short term, and so in order to trade in and out of these markets, these funds need to trade large, liquid positions.

The PhD Fund chooses to play in the US stock market because of this market’s breadth and depth of securities. Let’s assume that PhD Fund has dozens of measures for stocks in certain sectors and their models are constantly being built and augmented. They have income models that look at EBITDA, quarterly earnings, growth and more. They have balance sheet models that look at debt to equity ratios and book value, among other figures. They have technical models that look at short term momentum, daily volume, open interest and daily tic-by-tic trade data. You get the picture. These funds employ highly paid Gepettos, pulling the strings on computer models and trying to create money out of historical data.

So, how did it go wrong, exactly? I read a fantastic article today at InvestorsInsight that explained much more eloquently the details than I ever could. To paraphrase, the Quant funds started becoming over crowded. Many traded with the same strategies as each other. In other words, they were all piling on certain positions, causing a disruption in the supply/demand, thus eroding their profit margins from each individual trade. Its not unlike any other market; as soon as something becomes sought after, its harder and harder to make a profit as more people enter and disrupt the pricing. To compensate for this, Quant funds over leveraged themselves (e.g, borrowed too much money) to keep profits high. Still, on these eggheads whiteboards and super computers, this increase in risk was fine. Historically, there would have been no problem, they said. Nothing but the perfect storm could bust them. And they were right.

Enter a perfect storm. The credit crisis. The financial markets are unique, because they touch everyone. Absolute every business needs financing. You can’t run anything beyond a mom and pop set up without access to debt and capital investment.  When the financial sector in the US had a virus that had already spread and lay dormant through the rest of the world, everyone was affected. Suddenly, a key characteristic of the algorithm used by these Quant funds to price the assets they buy or sell has been tainted. Uncertainty reins. This causes fund managers and debt holders make some bizarre moves, causing a huge amount of volatility (think August, which I was unfortunately on holiday for. I would have loved to have watched it in real time). Quant funds, highly leveraged, are now facing a melt down. They can’t make money anymore. And the only thing worse then losing your ability to earn, is losing your ability to pay back those who you have promised to earn for. Funds were now posting huge intra-month losses left, right, and center. Major stakeholders, like the investment banks, even forced some of them to fully liquidate and recover what they could. The risk was just too great.

But as InvestorsInsight explains, not all funds were hit hard. The more vanilla funds, e.g. the funds who didn’t over leverage and properly assessed risk, managed to come out relatively unscathed. They posted a different story on the balance sheet:

Meanwhile, across town, a competing quant fund called the Braniac Fund feared the market would worsen and hit the reset button, liquidated all positions and went to cash. They lost faith in their models and believed they could easily lose more money. In an effort to get some breathing room and reassess, they overrode their model: human intervention. The Braniac Fund posted a -30% loss for August and were lambasted by their peers for lack of faith in the computers.

And the Vanilla Fund…well, they lost -8% intra-month. After their risk management kicked in, they posted a -6% month for August. No red lights, no panic, no excess leverage, just prudent risk management. They are now easing back into stocks, and welcoming the volatility.

You, as an investor, are mercifully unaware of any of this. You had no idea that mid-August the PhD Fund was down 30% and the propeller heads were levitating and on the verge of implosion. All you know is at month end the PhD Fund posted a -1% loss and you find out the Vanilla Fund posted a -6 % month. You mumble on the way to your foursome that you are glad you didn’t invest in Vanilla, and you are reassured when you receive a letter from the PhD Fund that, although they fired their CFO, they hired four new propeller heads.

As you can see, thanks to some tricky accounting, some ‘book cooking’, and asset movements,  the PhD fund can boast a return thats untrue. But the scars still remain, and the lesson, still needs to be sunk in. HedgeFund Blog says it best:

For those funds of hedge funds and pension funds intent on redeeming from good quant hedge funds it is worth recalling that after the October 1987 crash statistical arbitrage produced excellent returns in the following months. Statistical arbitrage has been around over 20 years and has had several difficult periods along the way as with EVERY investment style. However this overdue shake out will ultimately be a positive for good systematic hedge funds. No matter what happens I’d rather bet on alpha than beta. Before people get too hysterical about hedge funds they should remember the much larger amounts at risk in unhedged long only.

The truly strong funds use this as an opportunity to re-evaluate theories, and take advantage of a less crowded playing field. Like I always say, in a years time, we’ll know. Remember, any questions, feel free to leave a comment and I’ll explain everything in the plainest bad english I can!