Everything You Need to Know About Algorithmic Trading
In the financial markets, stock market traders typically need manual intervention to place orders, as full automation is not a common industry practice. This limits their trading capacity as they will have to spend screen time observing the markets, finding the trade, and executing the orders (put buy, sell, or stop loss orders). Also, their trade execution speed is limited. However, there is a solution to these limitations - algo trading.
What is Algorithmic Trading?
In the world of financial markets, the use of algorithms to generate buy or sell signals has become increasingly popular. These algorithms, also known as trading strategies, are created by users and are designed to analyze market data and make trading decisions based on predefined rules.
How does algorithmic trading work?
- Monitor the stock price in real time.
- Identify the highest price reached over a specified lookback period (e.g., the highest price in the last 10 trading days).
- Place a buy order when the current price surpasses this recent high.
- Monitor the lowest price reached over the same lookback period.
- Place a sell order when the current price falls below this recent low.
Six Major Components of Algo Trading
Algorithm Development: Creating mathematical models and rules that guide the decision-making process in trading.
Data Analysis: Understanding market trends, identifying patterns, and making informed investment decisions.
Automated Trade Execution: Efficient and timely execution of trades based on predefined rules.
Risk Management: Minimizing potential losses and protecting investment capital.
Backtesting: Validating trading strategies using historical data.
Strategy Optimization: Adjusting strategies to align with prevailing market dynamics.
How Algo Trading Platforms Empower Retail Traders and HNIs?
Algo eliminates the advantage gap institutions have compared to retail investors.
Traders can participate more actively in the trading markets while remaining passive.
Reduction in emotional bias and impulsive decisions.
Benefit from diversification and risk management.
Backtested strategies for favorable outcomes.
While every strategy carries inherent risks, properly tested algorithms can enhance efficiency and precision in execution. Today, majorly 70-80% of trading volume in the USA is done via algorithms (institution to retail level), even for routine buy-sell orders. Trading through a platform that has proper risk mitigation mechanisms and multi-layered risk management systems is critical for safe algo-based trading.