Pick the Right Algorithmic Trading Software

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Pick the Right Algorithmic Trading Software

Traders that use algorithmic trading place their hard-earned money in the hands of their trading program. As a result, the proper piece of computer software is required to enable the efficient and exact execution of trading orders. On the other side, bad software—or software without the necessary features—can result in massive losses, particularly in the lightning-fast realm of algorithmic trading.

A Quick Primer on Algorithmic Trading

An algorithm is a specialized collection of step-by-step instructions for completing a given job. Whether it’s a simple-yet-addictive computer game like Pac-Man or a spreadsheet with a plethora of functionalities, each software follows a set of instructions based on an underlying algorithm.

Key Takeaways

  • Choosing the right software is critical when establishing an algorithmic trading system.
  • A trading algorithm is a collection of instructions that guides buy and sell orders step by step.
  • When trading financial markets, faulty software might result in significant losses.
  • You may get algorithmic trading software in two ways: purchase it or make it.
  • Ready-made algorithmic trading software usually offers free trial versions with limited functionality.

Algorithmic trading is the process of making a trade order using a computer program that follows a predefined set of instructions. The goal of an algorithmic trading software is to dynamically find attractive opportunities and conduct trades in order to earn profits at a pace and frequency that a human trader cannot match. Trading operations based on computer algorithms have grown in popularity due to the benefits of increased precision and lightning-fast execution speed.

Who Uses Algorithmic Trading Software?

Large trading businesses, such as hedge funds, investment banks, and proprietary trading organizations, dominate algorithmic trading. Given their vast scale and plenty of resources, such organizations often develop their own proprietary trading software, including big trading platforms with dedicated data centers and support personnel.

Individually, skilled proprietary traders and quants make advantage of algorithmic trading. For their algorithmic trading requirements, proprietary traders who are less tech-savvy may acquire ready-made trading software. The software is either provided by its brokers or obtained from third-party vendors. Quants often have a strong understanding of both trading and computer programming, and they create their own trading software.

Algorithmic Trading Software: Build or Buy?

There are two options for obtaining algorithmic trading software: construct or purchase.

Buying ready-made software provides fast and easy access, whilst creating your own gives you complete ability to tailor it to your specific requirements. The automatic trading program is often expensive to acquire and may have flaws that, if ignored, may result in losses. The expensive cost of the software may also reduce the practical profit potential of your algorithmic trading endeavor. Building your own algorithmic trading program, on the other hand, requires time, effort, and a deep understanding, and it may not be flawless.

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The Key Features of Algorithmic Trading Software

The risk associated with automated trading is substantial, which may result in big losses. Whether you opt to purchase or construct, it is critical to understand the essential characteristics required.

Availability of Market and Company Data

All trading algorithms are programmed to respond to real-time market data and price quotations. A few algorithms are also tailored to take into consideration firm fundamentals like as earnings and P/E ratios. A real-time market data stream, as well as a corporate data feed, should be included in any algorithmic trading program. It should be built within the system or have the ability to be readily integrated from other sources.

Connectivity to Various Markets

Traders who want to trade in numerous markets should be aware that each exchange may give its data feed in a different format, such as TCP/IP, Multicast, or FIX. Your program should be able to accept various feed formats. Another alternative is to use third-party data suppliers like as Bloomberg and Reuters, who collect market data from several exchanges and give it to end users in a consistent manner. These aggregatedfeeds should be processed as required by the algorithmic trading program.


This is the most crucial aspect of algorithm trading. Latency is the temporal delay produced when data points are sent from one application to another. Take a look at the following sequence of events. A price quote from the exchange takes 0.2 seconds to reach your software vendor’s data center (DC), 0.3 seconds from the data center to your trading screen, 0.1 seconds for your trading software to process this received quote, 0.3 seconds for it to analyze and place a trade, 0.2 seconds for your trade order to reach your broker, and 0.3 seconds for your broker to route your order to the exchange.

Image by Sabrina Jiang © Investopedia2020

Total time elapsed = 0.2 + 0.3 + 0.1 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 + 0.3 +

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In today’s volatile trading environment, the initial price quotation would have changed many times over this 1.4 second period. Any delay might be the difference between success and failure for your algorithmic trading endeavor. To guarantee that you obtain the most up-to-date and correct information without a time gap, this latency should be kept as low as possible.

Latency has been decreased to microseconds, and every effort should be made in the trading system to maintain it as low as possible. Having direct connectivity to the exchange to get data faster by eliminating the vendor in between; improving the trading algorithm so that it takes less than 0.1+0.3 = 0.4 seconds for analysis and decision-making; or eliminating the broker and directly sending trades to the exchange to save 0.2 seconds are some measures to improve latency.

Configurability and Customization

Most algorithmic trading software has typical built-in trade algorithms, such as those based on a crossing of the 50-day and 200-day moving averages (MAs). A trader may want to experiment by replacing the 20-day MA with the 100-day MA. Unless the program allows for such parameter customisation, the trader may be limited by the built-in fixed functionality. Whether purchased or built, trading software should be highly customizable and configurable.

Functionality to Write Custom Programs

The most frequent programming languages used to create trading software are MatLab, Python, C++, JAVA, and Perl. The majority of trading software supplied by third-party providers allows you to develop your own bespoke programs inside it. This enables a trader to test and experiment with any trading strategy. Obviously, software that allows you to code in the programming language of your choosing is desirable.

Backtesting Feature on Historical Data

Backtesting simulation is the process of testing a trading strategy against past data. It evaluates the strategy’s feasibility and profitability based on historical data, certifying it for success (or failure or any needed changes).This need must also be backed by the availability of previous data on which backtesting may be undertaken.

Integration With Trading Interface

Algorithmic trading software automatically executes transactions depending on the occurrence of the specified conditions. The software should have direct access to the broker(s) network for placing trades or to the exchange for sending trade orders.

Understanding fees and transaction costs with different brokers is critical in the planning phase, particularly if the trading strategy relies on many transactions to achieve profitability.

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Plug-n-Play Integration

A trader may be utilizing a Bloomberg terminal for price analysis, a broker’s terminal for trade placement, and a Matlab application for trend analysis all at the same time. Depending on individual requirements, algorithmic trading software should include simple plug-and-play integration and API access to frequently used trading tools. This guarantees scalability and integration.

Platform-Independent Programming

A few computer languages need their own platforms. Certain versions of C++, for example, may only run on certain operating systems, but Perl may run on any operating system. When developing or purchasing trading software, select platform-independent trading software that supports platform-independent languages. You never know how your trade may change in a few months.

The Stuff Under the Hood

“Even a monkey can click a button to conduct a trade,” as the cliché goes. Computer dependency should not be taken lightly. The trader should be aware of what is going on behind the hood. When purchasing trading software, one should request (and take the time to read) extensive documentation that demonstrates the underlying logic of a certain algorithmic trading program. Avoid any trading program that is a full blackbox and promises to be a hidden moneymaker.

When developing software, be realistic about what you’re doing and be aware of the failure situations. Before utilizing actual money, thoroughly backtest the strategy.

Where to Begin?

Ready-made algorithmic trading software often provides free trial versions with restricted capability or limited trial periods with full functionality. Before purchasing anything, thoroughly investigate them throughout these trials. Don’t forget to thoroughly review the accessible documentation.

The Bottom Line

Algorithmic trading software is expensive to buy and complex to create on your own. Purchasing ready-made software provides rapid and timely access, whilst creating your own gives you complete ability to tailor it to your requirements. However, before engaging in algorithmic trading with real money, you must thoroughly comprehend the trading software’s essential functions. Failure to do so might result in significant losses.

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