Algorithmic trading is a method of automatically executing trades on the stock market using pre-defined trading rules which leverages the speed and computational resources of computers relative to a human. In recent years, algorithmic trading has been gaining popularity with both retail and institutional traders. Algorithmic trading is widely used by investment banks, pension funds, mutual funds, and hedge funds that may need to spread out the execution of a larger order or perform trades too fast for human traders to react to. A study performed in 2019 showed that around 92% of the trading operations in major stock markets is performed by algorithmic trading “machines” and automated trading systems.
The term algorithmic trading is often used synonymously with automated trading system. These encompass a variety of trading strategies, some of which are based on formulas and results from mathematical finance, and often rely on specialized software.
Algorithmic trading is a process for executing orders utilizing automated and pre-programmed trading instructions to account for variables such as price, timing, and volume. An algorithm is a set of directions for solving a problem.
Algorithmic trading systems use backtesting to verify the probability of future success which is likely to be achieved by the automated trading system in the near trading future. Backtesting is a process of verifying the trading algorithm by re-running it on past data from the stock exchange or broker. The data for backtesting includes stock price movements and trading volume. This is called price-action which is used in day trading as well.
Inferiority of Manual Trading and associated limitations
- Naturally, distribution of human attention is limited to just one or two financial instruments at a time. This means that any individual who is trading manually (day-trading or swing trading) can either trade very few stocks at the same time or to trade with very large position which is significantly increases his risk.
- As we all studied in the trading course, diversification over several positions and markets is essential for risk reduction for any portfolio over 20K$. For larger portfolios it is critical.
- Due to the human limitation, the diversification on larger trading portfolios becomes impossible with one or two traders, and there is a need for start hiring a professional trading team, which is a challenge and risk on its own.
- In addition to all mentioned – Manual trading is always subject to human emotions and mistakes.
Algorithmic Trading and Automated Trading Systems
- Algorithmic Trading, a highly efficient tool in the stock markets today, used mainly by institutions, hedge funds and proprietary trading companies.
- More than 92% of global trading volume is traded by computers and algorithms.
- Despite the above, 90% of all trading accounts (by number) still belong to retail traders which are not yet using automated trading systems.
- Algorithmic Trading technologies and tools were not available till now to retail investors, due to its complexity, but now thanks to advanced technologies now the algorithmic trading is available to all investors.
AlgoEdge labs DBATE Algorithmic Trading platform is used by both retail traders and institutional investors as an advanced and sophisticated tool for automated trading without the need to write any code. DBATE is a simple technical analysis tool which can automate trade execution within minutes.