Security trading can be a very profitable venture if you do it right. However, getting it right is no easy task, which is why most traders lose money trading stocks. To become a successful trader, you must not only master various trading techniques but also work on improving your training psychology. You need to train your mind to adhere to the rules and make the right decisions promptly. However, even seasoned traders find it challenging to master that facet. The aforementioned challenges paved the way for algo-trading. This article will tell you everything you need to know about algo-trading basics, with the help of a few examples.
Table of Contents
Algo-Trading Meaning
Algo-trading, an abbreviation for algorithmic trading, is a technique to trade using computer programs that follow fixed instructions to execute trades in the capital markets. Since algo-trading is carried out entirely by a computer program, it is also called automated trading. Algorithmic trades solely follow pre-defined instructions, which is why they are free of human error. At the same time, the computer can simultaneously monitor multiple metrics. Hence, algo-traders have higher profit efficiencies than human traders.
A human trader will find it very challenging to generate profits at the rate at which an algo-trader does. The algo-trading computer follows instructions based on mathematical models and constitutes a number of metrics like price, time, quantity, etc. The trader finds the precise metrics by carrying out backtesting. Backtesting involves evaluating a trading strategy by finding its efficiency based on historical data. Backtesting can also be performed with the help of a computer program.
Algo-Trading Example
To develop a more comprehensive understanding of algo-trading, let us look at an example.
Let us assume that, from backtesting, a trader finds that the stock price of a particular stock generally begins an upward trend when the 20-day moving average cuts above the 50-day moving average. The trend reverses when the same 20-day moving average cuts below the 50-day moving average. So, an algorithmic trader creates a trading algorithm based on the behaviour of two simple moving averages. The first moving average is the 20-day moving average, and the second is the 50-day moving average.
1. Buying Order Instruction
The algorithm places a buy order to buy 100 shares of a stock when its 20-day moving average cuts above the 50-day moving average.
2. Selling Order Instruction
The algorithm places a sell order to sell 100 shares of a company when the 20-day moving average crosses below the 50-day moving average.
For the sake of simplicity, in the above example, the algorithm placed orders based on one specific condition: the behaviour of two moving averages. However, a well-constructed algorithm would consider several conditions before placing orders. High-frequency trading (HFT) is one of the most common algo-trading examples you will find in the real market. This algo-trading strategy places multiple orders at rapid speeds based on multiple metrics across many markets.
Discover the advantages of algo-trading over traditional manual trading.
Technical Requirements for Algorithmic Trading
Now that you know about algo-trading basics, let us learn about the technical requirements you must possess to start algo-trading. An algorithmic trader uses backtesting to identify recurring trends in the price of multiple securities in the past. Then, they construct a set of rules based on their recordings to automate their trades using computer software. Hence, if you wish to start algo-trading, first and foremost, you must have access to a computer system and be well-versed in interpreting price charts. Only if you are capable of interpreting price charts will you be able to enter the right commands to design the algorithm. Besides those, the following requirements are also essential to carry out algo-trading:
- Knowledge pertaining to computer programming and software development, or the ability to hire talent with the said skillset to program the trading strategy.
- A trading infrastructure like a trading platform and robust network connectivity to execute trades.
- Historical data to backtest the instructions implemented in the algorithm.
- Skill to perform the backtesting once the programme has been designed before you can utilise it in the live markets
- Live market data that the algorithm can scan to identify opportunities and execute them effectively
Conclusion
Algo-trading helps scan, execute, and manage several trades simultaneously. The human eye can never keep track of multiple metrics and securities at the same time. Hence, institutional investors like mutual funds, pension funds, insurance companies, and hedge funds primarily trade in the capital markets using algo-trading software. Since algo-trades involve high trading volumes, they also help to maintain liquidity in the markets. As an individual trader, you can utilise algo-trading if you possess the software and other technical skills. It will help you trade using a systematic, disciplined approach rather than that dominated by human emotion and instinct.
