Algorithmic trading has revolutionized the way most investors and financial institutions trade in the stock market.
Rather than having to rely on hand-in-hand decision making, algorithms are used to analyse market data to place trades in accordance with the rules.
At its simplest, an algorithm is a set of instructions. In trading, these instructions may be based on things like price movements, trading volume, market trends, timing and technical indicators.
If these conditions are met, the system will automatically generate a buy or sell order.
How does Algorithmic trading work
Algorithmic trading starts with a trading strategy. A trader or financial institution sets rules that determine when a position should be opened or closed. The rules are then converted to computer code.
For example, a strategy may tell a system to buy a stock when it goes above a certain average price and sell it when it falls below another level. The software monitors market data and reacts faster than a human watching a trading screen.
Algorithms can also be designed to split up a big order into smaller transactions. This may let traders execute large orders gradually rather than a big order at once.
Why do traders use algorithms
Speed is one of the biggest advantages of algorithmic trading. Computers can process huge amounts of market information and execute orders within fractions of a second.
Automation can also reduce the influence of emotions. Fear, greed and hesitation can affect manual trading decisions, while an algorithm follows the instructions programmed into it.
Another advantage is efficiency. Algorithms can monitor the market and stock market conditions simultaneously, something that a trader in the market can’t do manually.
What are the risks
Algorithmic trading is not a sure way to get some profit. A strategy that works well in a set of market conditions may fail when the markets change.
Programming errors, incorrect trading rules, technical failures and unexpected market movements can also lead to serious losses. Rapid automated trading may sometimes increase market volatility, particularly when many systems react to the same event at the same time.
For this reason, algorithms generally need testing, monitoring and appropriate risk-management controls before they are used with real money.
Algorithmic trading vs Manual trading
Manual trading requires investors to analyse the information and place their orders. Algorithmic trading moves much of this to computer systems that follow pre-determined rules.
But algorithms do not eliminate all of the human involvement in these tasks. Traders and financial professionals need to create strategies, assess performance and risk management, and as market conditions change, they need to adapt their systems.
The Bottom Line
Algorithmic trading combines financial strategies with computer technology to automate parts of the trading process.
Its speed of execution, consistency and ability to process huge volumes of information have made it a key component of the contemporary financial markets.
For individual investors, it is helpful to understand how algorithmic trading works and how markets operate today.
But automated trading still has huge risks, and technology can’t eliminate them.
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