What Is Algorithmic Trading?
Algorithmic trading (also called automated trading, black-box trading, or algo-trading) uses a computer program that follows a defined set of instructions (an algorithm) to place a trade. The trade, in theory, can generate profits at a speed and frequency that is impossible for a human trader.
The defined sets of instructions are based on timing, price, quantity, or any mathematical model. Apart from profit opportunities for the trader, algo-trading renders markets more liquid and trading more systematic by ruling out the impact of human emotions on trading activities.
Advantages and Disadvantages of Algorithmic Trading
Algo-trading provides the following advantages:1
- Best Execution: Trades are often executed at the best possible prices.
- Low Latency: Trade order placement is instant and accurate (there is a high chance of execution at the desired levels). Trades are timed correctly and instantly to avoid significant price changes.
- Reduced transaction costs.
- Simultaneous automated checks on multiple market conditions.
- No Human Error: Reduced risk of manual errors or mistakes when placing trades. Also negates human traders; tendency to be swayed by emotional and psychological factors.
- Backtesting: Algo trading can be using available historical and real-time data to see if it is a viable trading strategy.
There are also several drawbacks or disadvantages of algorithmic trading to consider:
Regulation: Algorithmic trading is subject to various regulatory requirements and oversight, which can be complex and time-consuming to comply with.High Capital Costs: The development and implementation of algorithmic trading systems can be costly, and traders may need to pay ongoing fees for software and data feeds.Limited Customization: Algorithmic trading systems are based on pre-defined rules and instructions, which can limit the ability of traders to customize their trades to meet their specific needs or preferences.Lack of Human Judgment: Algorithmic trading relies on mathematical models and historical data, which means that it does not take into account the subjective and qualitative factors that can influence market movements. This lack of human judgment can be a disadvantage for traders who prefer a more intuitive or instinctive approach to trading.
- Latency: Algorithmic trading relies on fast execution speeds and low latency, which is the delay in the execution of a trade. If a trade is not executed quickly enough, it may result in missed opportunities or losses.
- Black Swan Events: Algorithmic trading relies on historical data and mathematical models to predict future market movements. However, unforeseen market disruptions, known as black swan events, can occur, which can result in losses for algorithmic traders.
- Dependence on Technology: Algorithmic trading relies on technology, including computer programs and high-speed internet connections. If there are technical issues or failures, it can disrupt the trading process and result in losses.
- Market Impact: Large algorithmic trades can have a significant impact on market prices, which can result in losses for traders who are not able to adjust their trades in response to these changes. Algo trading has also been suspected of increasing market volatility at times, even leading to so-called