Algorithmic trading is a form of trading that involves the use of computer-based algorithms to devise and execute automated trading strategies. By harnessing an automated system, trading transactions are sometimes executed faster and reliably than with human traders. By utilizing algorithmic trading, novice traders have the opportunity to improve their overall trading strategies, enhance performance, and gain a better understanding of the financial markets.
Understanding Algorithmic Trading
Algorithmic trading, also referred to as “algo-trading” or “automated trading,” is a computerized system that executes trading decisions based on predetermined criteria. Utilizing programmed algorithms, the system places orders on the basis of defined criteria. This approach to trading has become increasingly popular in recent years, driven in part by the increased availability of sophisticated trading software as well as access to high-speed networks and servers.
Using Automation to Enhance Performance
While the use of algorithmic trading can provide an advantage to the trading process, it is important to understand the different factors that can affect performance. Expected benefits include greater speed and accuracy in executing orders, a reduction in transaction costs and the ability to execute orders according to pre-determined measurements of risk. Additionally, algorithmic trading eliminates much of the emotional and human error associated with manual trading decisions, which can be beneficial for novice traders.
Comparing Relevant Strategies
For novice traders, there are a number of algorithmic trading strategies available for consideration. News-based Strategies, Rule-based Strategies, Behavioral Strategies, and AI-driven Strategies are some of the most common.
News-based Strategies utilize timely market news including company announcements, updates and corporate earnings to guide trading decisions. Rule-based Strategies use a set of predetermined conditions to control order execution, such as “if X, then Y” conditions. Behavioral Strategies react to large-scale market changes using specific, predetermined rules to respond accordingly. Lastly, AI-driven Strategies use a combination of artificial intelligence, natural language processing, historical market data and other inputs to generate automated trading decisions.
Bottom Line
By taking advantage of algorithmic trading, novice traders have a number of options to enhance their trading strategies and improve overall performance. While understanding the various strategies available is the first step, it is important to understand the various factors that can affect performance, as well as the advantages and risks associated with each strategy. By doing so, novice traders can improve their overall trading strategies and gain a better understanding of the financial markets.
