Algorithmic trading, also known as automated or black box trading, involves using computer programs to make trades based on predetermined rules or algorithms. These rules can be based on a variety of factors, such as the price of a security, the volume of trade, or the time of day. Algorithmic traders use these rules to make trades automatically, without the need for human intervention.
Algorithmic trading can be faster and more accurate than discretionary trading. Since the trades are made by a computer program, there is no risk of human error or emotional bias influencing the trade. Algorithmic traders can also analyze large amounts of data and make trades based on that analysis in a much shorter time frame than a human trader.
Why algorithmic trading?
Algorithmic trading can execute trades much faster than a human trader, which is especially useful in fast-moving markets.
Algorithmic traders can use historical data to test their trading strategies and see how they would have performed in the past. This can help traders improve their strategies and make more informed decisions about their trades.
Algorithmic trading follows the same rules every time it makes a trade, which can lead to more consistent results compared to discretionary trading.
Since trades are made based on predetermined rules, there is less risk of human error or emotional bias influencing the trade. This can lead to more accurate trade execution.
Large Volumes: 90%
Algorithmic trading can handle large volumes of trades more efficiently than a human trader, making it well-suited for large institutions and hedge funds.
Algorithmic trading can potentially reduce trading costs by reducing the need for human traders and associated expenses such as salaries and benefits.