Wall Street’s robots are not out to get you

Putting high-frequency trading into perspective.

ABOVE by Lyfetime, on FlickrTechnology is critical to today’s financial markets. It’s also surprisingly controversial. In most industries, increasing technological involvement is progress, not a problem. And yet, people who believe that computers should drive cars suddenly become Luddites when they talk about computers in trading.

There’s widespread public sentiment that technology in finance just screws the “little guy.” Some of that sentiment is due to concern about a few extremely high-profile errors. A lot of it is rooted in generalized mistrust of the entire financial industry. Part of the problem is that media coverage on the issue is depressingly simplistic. Hyperbolic articles about the “rogue robots of Wall Street” insinuate that high-frequency trading (HFT) is evil without saying much else. Very few of those articles explain that HFT is a catchall term that describes a host of different strategies, some of which are extremely beneficial to the public market.

I spent about six years as a trader, using automated systems to make markets and execute arbitrage strategies. From 2004-2011, as our algorithms and technology became more sophisticated, it was increasingly rare for a trader to have to enter a manual order. Even in 2004, “manual” meant instructing an assistant to type the order into a terminal; it was still routed to the exchange by a computer. Automating orders reduced the frequency of human “fat finger” errors. It meant that we could adjust our bids and offers in a stock immediately if the broader market moved, which enabled us to post tighter markets. It allowed us to manage risk more efficiently. More subtly, algorithms also reduced the impact of human biases — especially useful when liquidating a position that had turned out badly. Technology made trading firms like us more profitable, but it also benefited the people on the other sides of those trades. They got tighter spreads and deeper liquidity.

Many HFT strategies have been around for decades. A common one is exchange arbitrage, which Time magazine recently described in an article entitled “High Frequency Trading: Wall Street’s Doomsday Machine?”:

A high-frequency trader might try to take advantage of minuscule differences in prices between securities offered on different exchanges: ABC stock could be offered for one price in New York and for a slightly higher price in London. With a high-powered computer and an ‘algorithm,’ a trader could buy the cheap stock and sell the expensive one almost simultaneously, making an almost risk-free profit for himself.

It’s a little bit more difficult than that paragraph makes it sound, but the premise is true — computers are great for trades like that. As technology improved, exchange arb went from being largely manual to being run almost entirely via computer, and the market in the same stock across exchanges became substantially more efficient. (And as a result of competition, the strategy is now substantially less profitable for the firms that run it.)

Market making — posting both a bid and an offer in a security and profiting from the bid-ask spread — is presumably what Knight Capital was doing when it experienced “technical difficulties.” The strategy dates from the time when exchanges were organized around physical trading pits. Those were the bad old days, when there was little transparency and automation, and specialists and brokers could make money ripping off clients who didn’t have access to technology. Market makers act as liquidity providers, and they are an important part of a well-functioning market. Automated trading enables them to manage their orders efficiently and quickly, and helps to reduce risk.

So how do those high-profile screw-ups happen? They begin with human error (or, at least, poor judgment). Computerized trading systems can amplify these errors; it would be difficult for a person sending manual orders to simultaneously botch their markets in 148 different companies, as Knight did. But it’s nonsense to make the leap from one brokerage experiencing severe technical difficulties to claiming that automated market-making creates some sort of systemic risk. The way the market handled the Knight fiasco is how markets are supposed to function — stupidly priced orders came in, the market absorbed them, the U.S. Securities and Exchange Commission (SEC) and the exchanges adhered to their rules regarding which trades could be busted (ultimately letting most of the trades stand and resulting in a $440 million loss for Knight).

There are some aspects of HFT that are cause for concern. Certain strategies have exacerbated unfortunate feedback loops. The Flash Crash illustrated that an increase in volume doesn’t necessarily mean an increase in real liquidity. Nanex recently put together a graph (or a “horrifying GIF“) showing the sharply increasing number of quotes transmitted via automated systems across various exchanges. What it shows isn’t actual trades, but it does call attention to a problem called “quote spam.” Algorithms that employ this strategy generate a large number of buy and sell orders that are placed in the market and then are canceled almost instantly. They aren’t real liquidity; the machine placing them has no intention of getting a fill — it’s flooding the market with orders that competitor systems have to process. This activity leads to an increase in short-term volatility and higher trading costs.

The New York Times just ran an interesting article on HFT that included data on the average cost of trading one share of stock. From 2000 to 2010, it dropped from $.076 to $.035. Then it appears to have leveled off, and even increased slightly, to $.038 in 2012. If (as that data suggests) we’ve arrived at the point where the “market efficiency” benefit of HFT is outweighed by the risk of increased volatility or occasional instability, then regulators need to step in. The challenge is determining how to disincentivize destabilizing behavior without negatively impacting genuine liquidity providers. One possibility is to impose a financial transaction tax, possibly based on how long the order remains in the market or on the number of orders sent per second.

Rethinking regulation and market safeguards in light of new technology is absolutely appropriate. But the state of discourse in the mainstream press — mostly comprised of scare articles about “Wall Street’s terrifying robot invasion” — is unfortunate. Maligning computerized strategies because they are computerized is the wrong way to think about the future of our financial markets.

Photo: ABOVE by Lyfetime, on Flickr


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