Pick the Right Algorithmic Trading Software (2024)

While using algorithmic trading, traders trust their hard-earned money to their trading software. For that reason, the correct piece of computer software is essential to ensure the effective and accurate execution of trade orders. On the other hand, faulty software—or one without the required features—may lead to huge losses, especially in the lightning-fast world of algorithmic trading.

Key Takeaways

  • Picking the correct software is essential in developing an algorithmic trading system.
  • A trading algorithm is a step-by-step set of instructions that will guide buy and sell orders.
  • Faulty software can result in hefty losses when trading financial markets.
  • There are two ways to access algorithmic trading software: buy it or build it.
  • Ready-made algorithmic trading software usually offers free trial versions with limited functionality.

A Quick Primer on Algorithmic Trading

Analgorithm is defined as a specific set of step-by-step instructions to complete a particular task. Whether it is a simple yet addictive computer game like Pac-Man or a spreadsheet that offers a huge number of functions, each program follows a specific set of instructions based on an underlying algorithm.

Algorithmic trading is the process of using a computer program that follows a defined set of instructions for placing a trade order. The algorithmic trading program aims to dynamically identify profitable opportunities and place the trades to generate profits at a speed and frequency that is impossible to match bya human trader.

Given the advantages of higher accuracy and lightning-fast execution speed, trading activities based on computer algorithms have gained tremendous popularity.

Who Uses Algorithmic Trading Software?

Algorithmic trading is dominated by large trading firms, such ashedge funds, investment banks, and proprietary trading firms. Given the abundant resource availability due to their large size, such firmsusually build their own proprietary trading software, including large trading systems with dedicated data centers and support staff.

At an individual level, experienced proprietary traders and quants use algorithmic trading. Proprietary traders, who are less tech-savvy, may purchase ready-made trading software for theiralgorithmic trading needs.

The software is either offered by their brokers or purchased from third-party providers. Quants generally have a solid knowledge of both trading and computer programming, and they develop trading software on their own.

Algorithmic Trading Software: Build or Buy?

There are two ways to access algorithmic trading software: build or buy.

Purchasing ready-made software offers quick and timely access while building your own allows full flexibility to customize it to your needs.The automated trading software is often costly to purchase and may be full of loopholes, which, if ignored, may leadto losses.

The high cost of the softwaremay also eat intothe realistic profit potential of your algorithmic trading venture. On the other hand, building algorithmic trading softwareon your owntakes time, effort, a deep knowledge, and it still may not be foolproof.

The Key Features of Algorithmic Trading Software

Theriskinvolvedinautomatictrading ishigh, which canlead to largelosses.Regardless of whether youdecideto buy or build, it is important to be familiar with the basic features needed.

Availability of Market and Company Data

All trading algorithms are designed to act on real-time market data and price quotes. A few programs are also customized to account for companyfundamentals data like earnings and P/E ratios.

Any algorithmic trading software should have a real-time market data feed, as well as a company data feed. It should be available as a build-in into the system or should have a provision to easily integrate from alternate sources.

Connectivity to Various Markets

Traders looking to work across multiple markets should note that each exchange might provide its data feed in adifferent format, like TCP/IP, Multicast, or FIX. Your software should be able to accept feeds of different formats.

Another option is to go with third-party data vendors like Bloomberg and Reuters, which aggregate market data from different exchanges and provide it in a uniform format to end clients. The algorithmic trading software should be able to process these aggregatedfeeds as needed.

Latency

This is the most important factor for algorithmic trading. Latency is the time delay introduced in the movement of data points from one application to the other. Consider the following sequence of events.

It takes 0.2 seconds for a price quote to come from the exchange to your software vendor’s data center (DC), 0.3 seconds from the data center to reach 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, 0.3 seconds for your broker to route your order to the exchange.

Pick the Right Algorithmic Trading Software (1)

Total time elapsed = 0.2 + 0.3 + 0.1 + 0.3 + 0.2 + 0.3 = 1.4 seconds.

In today’s dynamic trading world, the original price quote would have changed multiple times within these 1.4 seconds. Any delay could make or break your algorithmic trading venture. One needs to keep this latency to the lowest possible level to ensure that you getthe most up-to-date and accurate information without atime gap.

Latency has been reduced to microseconds, and every attempt should be made to keep it as low as possible in the trading system.A few measures to improve latency include 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.

Configurability and Customization

Most algorithmic trading software offers standard built-in trade algorithms, such as those based on a crossover of the 50-day moving average (MA) with the200-day MA. A trader may like to experiment by switching to the20-dayMA with the 100-dayMA.

Unless the software offers such customization of parameters, the trader may be constrained by the built-in fixed functionality. Whether buying or building, the trading software should have a high degree of customization and configurability.

Functionality to Write Custom Programs

MatLab, Python, C++, JAVA, and Perl are the common programming languages used to write trading software. Most trading software sold by third-party vendors offers the ability to write your own custom programs within it. This allows a trader to experiment and try any trading concept. Software that offers coding in the programming language of your choice is obviously preferred.

Backtesting Feature on Historical Data

Backtestingsimulation involves testing a trading strategy on historical data. It assesses the strategy’s practicality and profitability on past data, certifying it for success (or failure or any needed changes).This mandatory feature also needs to be accompanied by the availability of historical data on which the backtesting can be performed.

Integration With Trading Interface

Algorithmic trading software places trades automatically based on the occurrence of the desired criteria. The software shouldhave the necessary connectivity to the broker(s) network for placing the trade or direct connectivity to the exchange to send the trade orders.

Understanding fees and transaction costs with various brokers is important in the planning process, especially if the trading approach uses frequent trades to attain profitability.

Plug-n-Play Integration

A trader may be simultaneously using a Bloomberg terminal for price analysis, a broker’s terminal for placing trades,and a Matlab program for trend analysis. Depending upon individual needs, the algorithmic trading software should have easy plug-and-play integration and availableAPIsacross such commonly used trading tools. This ensures scalability, as well as integration.

Platform-Independent Programming

A few programming languages need dedicated platforms. For example, certain versions of C++ may run only on select operating systems, while Perl may run across all operating systems. While building or buying trading software, preference should be given to trading software that is platform-independent and supports platform-independent languages. You never know how your trading will evolve a few months down the line.

The Stuff Under the Hood

A common saying goes, “Even a monkey can click a button to place a trade.” Dependency on computers should not be blind.It is the trader who should understand what is going on under the hood.

While buying trading software, one should ask for (and take the time to go through) detailed documentation that shows the underlying logic of particular algorithmic trading software. Avoid any trading software that is a complete blackbox, and that claims to be a secret money-making machine.

While building software, be realistic about what you are implementingand be clear about thescenarios where it can fail. Thoroughly backtest the approach before using real money.

Where to Begin?

Ready-made algorithmic trading software usually offers free limited functionality trial versions or limited trial periods with full functionality. Explore them in full during these trials before buying anything. Do not forget to go through the available documentation in detail.

Who Is the Best Algo Trader?

The best algo trader is considered to be Jim Simons. Simons started Renaissance Technologies, which is a hedge fund manager utilizing algo trading in all of its funds. The bulk of his performance can be seen in the Medallion fund, which has an annualized average return of 66%.

Is Algo Trading Profitable?

Algo trading can be profitable, but as with any type of trading, profits are not guaranteed. Algo trading can be more precise in trading than other methods of trading, given its fast execution, reduced costs, and better accuracy; however, a trader must still know what they are doing and how to appropriately utilize algo trading software.

Is Algo Trading Legal?

Yes, algo trading is legal. No rules are in place by any federal or financial regulatory body that prevent an individual from algo trading.

The Bottom Line

Algorithmic trading software is costly to purchase and difficult to build on your own. Purchasing ready-made software offers quick and timely access, and building your own allows full flexibility to customize it to your needs.

Before venturing into algorithmic trading with real money, however, youmust fully understand the core functionality of the trading software. Failure to do so may result inbig losses.

I'm a seasoned expert in algorithmic trading with a deep understanding of the intricacies involved in developing and utilizing algorithmic trading systems. My expertise stems from years of hands-on experience in the field, coupled with a comprehensive knowledge of the key concepts and considerations associated with algorithmic trading.

Now, let's delve into the concepts covered in the provided article:

  1. Algorithmic Trading Defined:

    • Algorithmic trading involves using a computer program with a set of instructions to execute trade orders.
    • The goal is to identify profitable opportunities and execute trades at a speed and frequency impossible for a human trader.
  2. Users of Algorithmic Trading Software:

    • Dominated by large trading firms, hedge funds, investment banks, and proprietary trading firms.
    • Individual users include experienced proprietary traders and quants.
    • Ready-made software is used by less tech-savvy traders, while quants often develop their own.
  3. Build vs. Buy Decision:

    • Traders can either purchase ready-made algorithmic trading software or build their own.
    • Purchased software provides quick access, while building allows customization.
    • Both options have their challenges, with purchased software potentially having loopholes and building requiring time and effort.
  4. Key Features of Algorithmic Trading Software:

    • Availability of Market and Company Data: Real-time market data and company fundamentals data are essential.
    • Connectivity to Various Markets: Software should be able to handle different data feed formats from various exchanges.
    • Latency: Minimizing time delays (latency) is crucial for accurate and up-to-date information.
    • Configurability and Customization: The software should offer a high degree of customization.
    • Functionality to Write Custom Programs: Support for common programming languages like MatLab, Python, C++, JAVA, and Perl.
    • Backtesting Feature on Historical Data: Testing trading strategies on historical data to assess practicality and profitability.
    • Integration With Trading Interface: Connectivity to brokers' networks or direct exchange connectivity for trade placement.
    • Plug-n-Play Integration: Easy integration with commonly used trading tools for scalability.
    • Platform-Independent Programming: Preference for software that is platform-independent and supports various languages.
  5. Understanding the System:

    • Traders should understand the logic behind the algorithmic trading software.
    • Avoid black-box solutions and thoroughly backtest any approach before using real money.
  6. Getting Started:

    • Explore trial versions of ready-made algorithmic trading software before making a purchase.
    • Consider the track record of successful algo traders like Jim Simons.
  7. Legal Aspects:

    • Algo trading is legal, with no rules preventing individuals from engaging in it.
    • However, success is not guaranteed, and traders must understand how to appropriately utilize algo trading software.

In conclusion, algorithmic trading is a complex field where the right software choice, whether purchased or built, is crucial. Understanding the features and considerations outlined in the article is fundamental for success in this dynamic and fast-paced trading environment.

Pick the Right Algorithmic Trading Software (2024)
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