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Automated trading, should it replace hands-on active trading?
Can Algorithmic Trading Continue to Expand?
(Note: companies that could be impacted by the content of this article are listed at the base of the story [desktop version]. This article uses third-party references to provide a bullish, bearish, and balanced point of view; sources are listed after the Balanced section.)
The use of algorithmic robots to trade stocks has grown rapidly in recent years. Algorithmic trading refers to transactions that allow investors to establish specific trading rules that are automatically executed by computer. A report by Trading Type estimates that the global algorithmic trading market will increase by 11% annually between 2019-2024 reaching a level of $18.8 billion. Select USA estimates that roughly 75% of shares traded on U.S. stock exchanges come from automatic trading systems. Once relegated to buy and sell limit orders, algorithmic trading has expanded into data mining algorithms that turn news events into trades in real time. An increase in news reports with the words “trade tension”, for example, could result in an automatic order to sell U.S. stocks with a large exposure to China. Is algorithmic trading an investment tool that can allow individual traders to quickly take advantage of market inefficiencies? Or, does algorithmic trading make the market less stable and in fact create market inefficiencies?
Algorithmic trading is efficient and
inexpensive. One of the primary advantages of computer trading is that it is done automatically without the need of a broker, research analysts, or human traders. There is little human interaction meaning a more accurate system. The trading is done quickly which can result in better pricing.
Minimalizes emotional investing. Algorithmic trading uses predetermined rules. There is no room for investors to get affected by their emotions. Computers do not fall in love with stocks and hold onto them when they should be sold. Trades can’t be second guessed.
Investors can backtest results. Trading strategies are typically backtested against historical data. They can be adjusted and fine-tuned to achieve the best results. While past performance is no guarantee of future performance, it is often an indicator of trends.
Diversification. Algorithmic trading allows investors to spread themselves across numerous accounts, strategies and investment instruments. Automated computer trading rules can be applied to almost any publicly traded exchanges. Trading can be done across different platforms so that trading patterns are less obvious to other investors.
Increased market volatility and market
irrationality. The increased use of computers to perform trades increases the volumes and speed of trades. This, in turn, can lead to increased stock price movement. A CFTC report concluded that automated trading contributed to the Flash Crash of 2014 by accelerating the pace at which trading was completed. Increased market volatility could lead to increased trader panic and further market volatility. At times, the market acts irrationally. This could mean that trading algorithms that have been proven through thorough backtesting no longer work.
Not all strategies can be automated. Algorithms require concrete rules surrounding the trade. Believing that a Republican victory will be good for investors may be a sound investment strategy, but it must be converted into a specific trading algorithm. Which election victory? When will a victory be measured? What stocks will benefit? Will the transaction be completed even if stocks have risen?
Dependency on technology. Algorithmic trading is reliant on a computer system. This may mean that trades may not be completed if there is a power outage or a loss in Internet service. Knight Capital experienced a software glitch in its trading system causing the firm to lose $440 million. Computer security becomes more important with increased use of robotic trading.
Algorithmic trading requires monitoring. Algorithmic trading rules need to be constantly monitored as the intended effects may become ineffective over time. The system does not leave room for traders to override the rules should the rules not work as expected and result in large losses. The Robust Trader estimates that 98% of all algorithms have a very short lifespan, implying the need for constantly creating new algorithms. Nasdaq recommends that traders use both visual and audible alerts when monitoring automated trading.
Algorithmic trading is expanding both in terms of frequency and the manner in which the trading is being done. It is unclear whether such trading increases or decreases overall market efficiency. Individual investors should be aware of the growing impact of robot trading and the pros and cons of using automated trading as part of their investment strategies. Investors employing algorithmic trading should be aware that it is not a substitute for active trading and requires constant monitoring and frequent adjustments.
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https://finance.yahoo.com/news/why-stock-market-traders-should-be-terrified-of-robots-in-the-next-decade-130024382.html, Brian Sozzi, Yahoo Finance, January 2, 2020
https://education.howthemarketworks.com/pros-cons-algorithmic-trading/, Edward Roebuck, How the Market Works
https://www.investopedia.com/articles/trading/11/automated-trading-systems.asp, Jean Folger, Investopedia, May 12, 2019
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https://www.economist.com/schumpeter/2012/08/03/desperate-times, Schumpeter, the Economist, August 3, 2012.
https://www.mordorintelligence.com/industry-reports/algorithmic-trading-market, Mordor Intelligence
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