like to lose to a machine? In 1997 the world’s best chess player, Garry Kasparov, was beaten by Deep Blue, a $10m super-computer made by. Twenty years later he wrote “Deep Thinking”, a book about the experience. What comes across vividly is how exhausting each game was. Chess players, even great ones like Mr Kasparov, get tired and frustrated. Doubts begin to creep in. By contrast, Deep Blue just needed the occasional reboot.
Quants rely on history. If something happens that is without precedent, such as a vaccine in a pandemic, they have a problem. No doubt a few quant hedge funds are nursing heavy losses. And perhaps a few discretionary funds have made a killing. The terrain on which human traders can beat the machines is much diminished. But November 9th shows it is still possible. Chalk it up as a small victory for the species.
A lot of long-short strategies, including momentum, rank stocks by a particular attribute and then buy the top decile of the group and sell the bottom one. This requires machines. Sorting through thousands of securities quickly is beyond the meagre talents of a living, breathing portfolio manager. It requires algorithms that first establish and then fine-tune the optimal period over which to do the sorting. And it needs speedy and seamless access to automatic trading platforms and market data.
But why were the moves in prices so dramatic? A good rule of thumb, says one quant guru, is that the faster you trade, the less capacity there is for your strategy. A speedy trading strategy, such as momentum, relies on liquid markets to keep turnover costs in check. The strategy can become crowded. And when the quants suffer losses, they may be forced by risk-management rules to close their positions. As everyone rushes to get out at the same time, it makes for extreme price movements.
You mean the ones responsible for 2009 that found employment in network opinion polls?
Quant managers are not all the same. They all have different investment processes. Some have performed quite well in 2020. To lump them all together as if they all perform the same is to truly not understand true quantitative investing.
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