The financial market applications and trading have seen a staggering boom with technology advancement in all industries. Around the globe, all exchanges have started to set their sight on high-frequency trading and algorithmic (algo) trading.
It has become one of the standard trading methods in developed markets and is branching out to developing economies. Currently, 75% of the global trades and 30-50% of developing economies are executed through Algo trades. It naturally set off the development of integrated Algo trading platforms like QuantTerminal.
Before you take the plunge into the trade, it’s essential to learn every aspect of algorithmic trading to come out successfully. Here are a few basics of algo trading:
What you can expect in this article:
The Basics Of Algo Trading
Algorithmic trading is known by different names like algo trading, black-box trading, and automated trading. This method uses computer programs, codes, and chart analysis to enter and exit trades according to defined parameters like volatility levels and price movements.
It can subdue human traders when it comes to frequency and speed in which it generates trade profits. This is because it takes into consideration the set of defined instructions like price, timing, quantity, and many other complex mathematical models.
Algo trading helps bring down losses due to human error as it rules out the impact of human emotions during the trading process. Along with this, many algorithmic trading platforms like QuantTerminal simplifies your trading experience.
How Does It Work In Practice
To understand how Algorithmic trading works, let’s start with a simple example. Assume that you give these two instructions to your trading software.
Firstly, acquire 50 shares when the stock’s 50-day moving average increases beyond the 200-day moving average. Secondly, sell the shares when the 50-day moving average goes below the 200-day moving average.
When you predefine these simple instructions, the program will monitor the stock and place the orders when the conditions are met.
You can take time off from constantly monitoring live prices, graphs, and the entire manual trading process. Algo trading takes the front wheel and does the job more efficiently with extra care and scrutiny.
Advantages of Algo Trading
More & Better Opportunities
As you can easily choose and create algorithms according to your strategy in platforms like QuantTerminal, it maximizes your exposure to profit and opportunities in the trading market.
Helps With Your Existing Strategy
Apart from creating new strategies with Algo trading, you can use algorithms to tune risk management factors in your existing trading strategy. You can implement limits and stops according to your requirement.
Easy To Backtest
With Algo trading, you can easily backtest and refine the algorithms by comparing them to historical data. With this, you can establish and develop a better combination of parameters to predefine for buying and selling.
Reduces Human Error
As human emotions take a back seat in Algorithmic trading, it gets out of the way of figuring out profits and cutting off losses.
If you take up Algo trading, all you have to do is set up your algorithms on a schedule and let them trade accordingly. It can even be round the clock.
What Do You Need For Algo Trading
You would already have a strategy for trading. All you have to do is transform it into an integrated digital process using a computer program. Some of the technical requirements for Algorithmic trading are,
- Well-versed in computer programming or investment in any automated trading platform like QuantTerminal.
- Good network connectivity to access trading platforms
- The tools to backtest the system as a trial before going live in real markets
- Ways to access market data feeds for the algorithm to monitor
- Sources of historical data for backtesting
As you learn more about Algo trading, you will become a seasoned trader who can come up with better trading strategies. As this is a more systematic approach, it has more advantages than traditional trading methods.