When using algorithmic trading, traders entrust their hard-earned money to their trading software. Therefore, the correct computer software is essential to ensure effective and accurate execution of trading orders. On the other hand, defective software-or software without the required features-can cause huge losses, especially in the lightning-fast algorithmic trading world.
Quick start to algorithmic trading
An algorithm is defined as a set of specific step-by-step instructions to complete a specific task. Whether it’s a simple but addictive computer game like Pac-Man or a spreadsheet that provides a large number of functions, each program follows a specific set of instructions based on the underlying algorithm.
- Choosing the right software is essential for developing an algorithmic trading system.
- The trading algorithm is a set of step-by-step instructions to guide buy and sell orders.
- When trading in financial markets, defective software can cause huge losses.
- There are two ways to access algorithmic trading software: buy or build.
- Off-the-shelf algorithmic trading software usually provides free trial versions with limited features.
Algorithmic trading is the process of placing trading orders using a computer program to follow a set of defined instructions. The goal of an algorithmic trading program is to dynamically identify profit opportunities and trade in order to generate profits at a speed and frequency that human traders cannot match. Due to the advantages of higher accuracy and lightning-fast execution speed, trading activities based on computer algorithms have gained great popularity.
Who uses algorithmic trading software?
Algorithmic trading is dominated by large trading companies such as hedge funds, investment banks and proprietary trading companies. Due to their large scale and abundant resources, these companies usually build their own proprietary trading software, including large trading systems with dedicated data centers and support staff.
At the personal level, experienced proprietary traders and quantitative traders use algorithmic trading. Proprietary traders who do not know much about technology may purchase off-the-shelf trading software to meet their algorithmic trading needs. The software is either provided by their broker or purchased from a third-party supplier. Quantitative traders usually have solid knowledge in trading and computer programming, and they develop trading software by themselves.
Algorithmic trading software: build or buy?
There are two ways to access algorithmic trading software: build or buy.
Buying off-the-shelf software provides quick and timely access, while building your own software allows you to customize it completely flexibly according to your needs. The purchase cost of automated trading software is usually high and may be full of loopholes. If these loopholes are ignored, losses may result. The high cost of software may also erode the actual profit potential of your algorithmic trading business. On the other hand, building algorithmic trading software on your own requires time, energy, and deep knowledge, and it may still not be foolproof.
Main features of algorithmic trading software
Automated trading involves high risks and may result in large losses. Whether you decide to buy or build, it’s important to be familiar with the basic functions you need.
Availability of market and company data
All trading algorithms are designed to act based on real-time market data and quotes. Some procedures have also been customized to consider company fundamentals, such as earnings and price-to-earnings ratio. Any algorithmic trading software should have real-time market data feeds as well as company data feeds. It should be provided as a built-in component of the system, or there should be a clause that can be easily integrated from other sources.
Connect various markets
Traders who wish to work in multiple markets should be aware that each exchange may provide its data feed in a different format, such as TCP/IP, multicast, or FIX. Your software should be able to accept feeds in different formats. Another option is to work with third-party data providers such as Bloomberg and Reuters, which aggregate market data from different exchanges and provide them to end customers in a unified format. Algorithmic trading software should be able to process these aggregated feeds as needed.
This is the most important factor in algorithmic trading. Latency is the time delay introduced when a data point moves from one application to another. Consider the following sequence of events. Quotation takes 0.2 seconds from the exchange to the data center (DC) of your software provider, 0.3 seconds from the data center to your trading screen, and 0.3 seconds for your trading software to process the received quotation. It is used for analysis and downloading. Single, your trading order needs 0.2 seconds to reach your broker, and your broker needs 0.3 seconds to send your order to the exchange.
Total elapsed time = 0.2 + 0.3 + 0.1 + 0.3 + 0.2 + 0.3 = total 1.4 seconds.
In today’s dynamic trading world, the original quote will change many times within 1.4 seconds. Any delay may accomplish or destroy your algorithmic trading business. This delay needs to be kept as low as possible to ensure that you get the most up-to-date and accurate information without time gaps.
The delay has been reduced to microseconds, and every effort should be made to keep it as low as possible in the trading system. Some measures to improve latency include directly connecting to the exchange to obtain data faster by eliminating intermediate suppliers; improving the trading algorithm so that the analysis decision time is less than 0.1+0.3=0.4 seconds; or by eliminating the broker and sending the transaction directly to So the transaction saves 0.2 seconds.
Configurability and customization
Most algorithmic trading software provides standard built-in trading algorithms, such as an algorithm based on the crossover of a 50-day moving average (MA) and a 200-day moving average. Traders may like to experiment by switching from the 100-day moving average to the 20-day moving average. Unless the software provides such parameter customization, traders may be restricted by built-in fixed functions. Whether buying or building, trading software should be highly customizable and configurable.
The function of writing custom programs
Matlab, Python, C++, JAVA and Perl are commonly used programming languages for writing trading software. Most trading software sold by third-party vendors provide the ability to write your own custom programs in them. This allows traders to experiment and try any trading concept. Software that provides coding in the programming language of your choice is obviously the first choice.
Historical data backtest function
Backtesting simulation involves testing trading strategies based on historical data. It evaluates the practicability and profitability of the strategy based on past data and proves its success (or failure or any required changes). This mandatory feature also needs to be accompanied by the availability of historical data that can perform back-testing.
Integration with trading interface
Algorithmic trading software automatically conducts transactions based on the appearance of required standards. The software should establish the necessary connection with the broker’s network for trading or directly connect with the exchange to send trading orders.
It is important to understand the fees and transaction costs of various brokers during the planning process, especially if the trading method uses frequent transactions to make a profit.
Plug and play integration
Traders may use the Bloomberg terminal for price analysis, the broker terminal for trading, and the Matlab program for trend analysis. According to personal needs, algorithmic trading software should have simple plug-and-play integration and available APIs across these commonly used trading tools. This ensures scalability and integration.
Some programming languages require dedicated platforms. For example, some versions of C++ may only run on selected operating systems, while Perl may run on all operating systems. When constructing or purchasing trading software, preference should be given to trading software that is platform-independent and supports platform-independent language. You never know how your trading will develop in a few months.
Stuff under the hood
As the saying goes, “Even monkeys can click buttons to trade.” Reliance on computers should not be blind. Traders should understand what is happening behind the scenes. When purchasing trading software, you should request (and take time to read) detailed documents showing the underlying logic of a particular algorithmic trading software. Avoid using any trading software that is completely black box and claim to be a secret money machine.
When building software, be realistic about what you are implementing, and be aware of scenarios where it might fail. Test the method thoroughly before using real money.
Where to start?
Ready-made algorithmic trading software usually provides a free trial version with limited functions or a limited trial period with full functions. Before buying anything, please fully explore them during these trial periods. Don’t forget to read the available documents in detail.
If you plan to build your own system, Quantopian is a great free resource for exploring algorithmic trading. It provides an online platform for testing and developing algorithmic trading.Individuals can try to customize any existing algorithm or write a completely new algorithm. The platform also provides built-in algorithmic trading software, which can be tested based on market data.
Algorithmic trading software is expensive to purchase and difficult to build by yourself. Buying off-the-shelf software can provide quick and timely access, while building your own software can be completely flexible to customize it to your needs. However, before using real money for algorithmic trading, you must fully understand the core functions of the trading software. Failure to do so may result in huge losses.