Misconceptions About Algorithmic/High Frequency Trading

TLDR version: Algorithmic trading doesn’t cause market crashes, fear does.

The left keeps spreading the myth that high frequency trading/algorithmic trading is responsible for crashes when in fact there are many glaring holes in the anti-HFT argument. If the market were rigged, as the left insists it is, and you knew how it was rigged, couldn’t you just front-run the riggers and make money at their expense? If the fed is propping up the market market with QE, why not just buy bonds, knowing that you cannot lose with the fed having your back? Or maybe short bonds, knowing that the fed has ended QE? You can’t fail – oh wait – bonds have surged since the fed ended QE. But we cannot let facts and evidence get in the way the left’s unfounded belief that the market is rigged.

The absence of computers and trading algorithms didn’t prevent the many crashes and panics that occurred in the 1800’s and 1900’s. The crash of 1929, half a century before the development of computerized trading, saw the US stock market lose 20% of its value in just two days. It always boils down to greed and fear. Greed makes markets rise quickly. Fear makes them fall quickly. The left assumes you can only have high-frequency selling (in an intellectually dishonest manner, they only focus on the declines), but high-frequency buying also occurs although that seldom gets as much media attention as selling.

The left assumes high frequency traders try to create a feedback loop of panic selling, of high frequency traders piling on each other and forcing the market lower for their own profit. But this is not a good strategy. Consider a thought experiment where a group of high frequency traders conspire to short enough of the S&P 500 to bring the price from $100 to $99 (these are just made-up numbers). The average profit is .5% (some shorted at the top, some at the bottom). But because this decline was artificial and unrelated to news or fundamentals, there is no reason why it should stay that way. So then human traders see the sudden unjustified selling and pounce the opportunity to buy the depressed stock, which immediately rallies back to $100. The humans now have an average profit of .5% and the HFTs have a loss of .5%. The humans could fool the HFTs into shorting stock at a loss, by initially shorting to make the market fall a little (like .1% or .10$) to lure to the HFTs pile on and bring it down 1% (to $99), in which case the humans will intercede to bid it back up to $100 and repeat ad infinitum. Thus, feedback lops are unprofitable unless the market doesn’t bounce back or if the non-HFTs add to the selling. But if feedback loops were uncontrollable, the market would go to zero at the slightest provocation. Eventually, fundamentals step-in and provide a floor. No, you cannot have IBM fall from $160 to $4 (and stay at $4) when nothing has fundamentally changed.

There is mathematical argument for how HFT can make the market more stable. More trading volume means more stability and less volatility.

The May 6, 2010 flash crash, in which the DJIA (Dow Jones Industrial Average) almost fell 1,000 points that day, is thought to have been exasperated by HFT. Even if this were true, it was probably an unprofitable day for the HFTs because while the DJIA was at once point down 1,000 points, it ended the day only down 360 points, meaning that a lot of the short positions were covered at a loss on the way back up. Second, despite the media attention they generate, panics are still very rare, but were quite common in the late 90’s – a decade before HFT became a household word. Otherwise, the market has been remarkably stable; since 2011, there has yet to even be a 10% correction.

What high frequency trading does is it makes the market more efficient and less predictable (in the short term). It means that the market , through daily the ebbs and flows, is constantly adjusting to reflect new data and probabilities. You have an event with a theoretical price impact of $X and a probability of Y and the product $XY tells you how the market reacts. And this is done millions of times a day, so the price that you see is the product of a very large computerized ‘committee’ that is trying to determine the ‘right’ price, which is the very opposite of the clandestine ‘rigged casino’ that the left would have you believe Wall St. is. And these HFTs are not colluding against average retail investors such as you and me, but competing with each other. In April 2013 the S&P 500 briefly fell 1% on report of explosions in the White House, which was immediately revealed to be a hoax. The market’s initial reaction was based on the probability of the Tweet being authentic multiplied by the hypothetical economic impact if it were real, the result being an immediate 1% decline. It’s not that the HFTs are trying to ‘rig’ the market, they are calibrating the market to reflect the latest information, and for a brief moment America was supposedly under attack, to reflected in stock prices. After it was debunked, the probability became zero and the market immediately corrected itself back to the pre-hoax price. As shown by the thought experiment above, the high frequency traders who initially brought the market lower lost money in the ordeal.