Automated Trading Popularity
Automated trading has been a pillar of Wall Street traders for decades, but it’s still a fairly new tool for retail investors.
Since the 70s, Wall Street traders have been using some version of automated trading. By the 90s, models were available for purchase. It wasn’t until 2008 that a free service finally became available for retail investors.
As technology advanced, so did the capabilities and popularity of automated trading. In 2003, automated trades accounted for just 15% of market trading volume.
Analysts now estimate that 60-75% of all trading volume in the US stock market is generated through automated trading.
Despite its popularity and advancements, automated trading models are not magical, know-all systems. They’re not guaranteed to grow your money.
These models are only as good as the programmers’ design. There are some models out there that are very useful, some that are so-so and some you should avoid altogether.
The Rise of Automated Trading
Automated trading emerged with the advancement of the internet in the late 80s and early 90s. But it wasn’t until 1998 that the US Securities and Exchange Commission (SEC) authorized electronic exchanges.
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That was the beginning of computed, high-frequency trading (HFT) going mainstream.
The ability to program computers with trading instructions accounting for timing, price, volume, and other technical indicators quickly became popular among Wall Street institutions.
These strategies are turned into code, or algorithms, that tell a computer when to buy and sell a security.
There are several strategies that a trader can employ in their automated systems. But perhaps the biggest advantage of automated trading is that it leverages a computer’s blinding speed and its ability to tirelessly operate 24/7.
The completion of the US Decimalization process in 2001 marked another milestone in the adoption of automated trading. Decimalization changed the minimum “tick size” from 1/16 of a dollar ($0.0625) to $0.01 per share. That in turn altered the market structure by allowing for much more granular differences (the “spread”) between bid and offer prices.
Since then, trade prices have been expressed in the decimal format rather than in fractions. This has made it much easier for programmers to tell computers what to do.
The next big set of regulations that would propel the future of automated trading was the Regulation National Market System (Reg NMS) that was developed in 2005, but not implemented until 2007.
The Reg NMS was a series of initiatives mandating that exchanges transmit real-time data to a centralized entity and requiring that exchanges and brokers accept the most competitive offer when matching buyers and sellers.
This changed the way firms operated and was a tremendous boon to HFT.
The final major piece of the automated trading puzzle was the creation of “Pandas.” Developed at AQR Capital Management in 2008, Pandas is a data manipulation and analysis software package for the Python computer code. Its strength is in performing quantitative research on financial data at fast speeds.
The Automated Trading Boom
Those three key developments made the technology for automated trading easier to operate, more accurate, and far more diverse. Institutions now had hundreds of ways to utilize the new technology and Wall Street fully adopted algorithmic trading.
In the early 2000s, algorithmic trading accounted for less than 10% of equity orders. By the end of 2009, algorithmic trades accounted for 70% of trading in the US securities markets.
The New York Stock Exchange (NYSE) estimates that between 2005 and 2009, automated trading volume grew by 164%.
In this time there was also a significant decrease in trade execution time.
In 2001, HFT trades had an execution time of several seconds. By 2010, execution time took just milliseconds. Today that time has dropped to nanoseconds.
The development of nano trading technology by Fixnetix’s microchip created a cascade of programs designed for automated trading.
There are platforms programmed to identify “micro-trends'' in the news. There are platforms that detect linguistic patterns across the more than 340 million daily Twitter messages. And on and on…
There’s a lot to consider when thinking about using automated trading, especially if you’re new to it. So it’s worth understanding the pros and cons.
Pros of Automated Trading
The popular phrase, “plan the trade, then trade the plan,” is much easier to execute with an automated system consistently executing your plan. Trouble is, too many retail traders start with a plan, only to forget about it or ditch it over time.
So the ability to pinpoint certain trade settings (the plan), and have those settings remain in place, is an extremely useful tool.
Unlike humans, the computer will not waiver from whatever strategy they’re programmed to employ.
This saves retail investors a world of anxiety. You don’t have to think twice.
It also helps to take much of the guesswork out of trading by allowing you to “backtest” a prospective trading methodology or idea. (Backtesting is when an investor looks to see how a particular set of conditions would have performed over a stretch of time in the past.)
The entire history of market data is available for automated systems, and with a click you’re able to see how a trading plan would have worked. This insight can give you a measure of confidence that the same plan will work going forward.
You’ve been hearing all about the importance of diversification since you picked up your first Wall Street Journal.
Another benefit of automated trading is that it can help investors stay diversified.
Of course, trading is about maximizing profits while minimizing risk. Algorithms help traders do this much quicker and with much less margin for human error.
The market scanning capabilities that come with automated trading systems also allow investors to trade multiple accounts and deploy multiple strategies simultaneously, identifying different profit and loss opportunities in less than seconds.
All of that said, automated trading is not without its drawbacks.
Cons of Automated Trading
If too many people adopt automated trading methods, the system will leave volume footprints in the market.
In May of 2010, a computer-driven, automated trade worth $4.1 billion triggered just that. The May Flash Crash caused the Dow Jones to plummet 1,000 points in a single trading day, wiping out nearly $1 trillion its market value in all of five minutes.
An abnormal news story has been known to trigger automated trading systems too. On April 23, 2013, the Associated Press erroneously reported that two explosions in the White House had injured President Barack Obama. The “story” leaked on twitter and caused panic on Wall Street. The Dow plummeted 143 points in 3 minutes.
And there is always the possibility of user error. For all their power, algorithms are still just tools that need to be wielded by an intelligent operator. If the user doesn’t know how to use the tools, they’re essentially useless. Or worse, they can be actively dangerous.
Finally, when all is said and done, nothing beats skill and experience when it comes to navigating the market – especially the kind of bear market we’re in right now.
Founder and CEO, True Market Insiders