Choose the best algo trading software – tools you need to take a decision

Traders who use algorithmic trading put their hard-earned cash in the hands of their trading software. Because of this, successful and precise execution of trading orders requires the use of the appropriate piece of computer software. On the other side, malfunctioning software—or one without the necessary features—could result in enormous losses, particularly in the lightning-fast realm of algorithmic trading. Let’s see what tools in algo trading one may need to make a decision on what software he or she can use to succeed. 

Who uses software for algorithmic trading? 

Large trading companies, including hedge funds, investment banks, and proprietary trading firms, are the dominant players in algorithmic trading. Due to the abundance of resources, they have access to as a result of their scale, such companies typically develop their own proprietary trading software, including sizable trading platforms with dedicated data centers and support personnel.

Quants and seasoned proprietary traders utilize algorithmic trading on an individual basis. Less tech-savvy proprietary traders can buy pre-made trading software to meet their needs for algorithmic trading. Their brokers either provide the software or they buy it from outside vendors. The majority of quants are proficient in both trading and computer programming, and typically create their own trading software. 

Buying vs. building algorithmic trading software? 

Software for algorithmic trading can be obtained in two ways: by building it or by purchasing it.

When compared to constructing your own, buying ready-made trading software offers rapid and timely access while giving you complete customization options. The cost of purchasing automated trading software is frequently high, and the software itself may have many flaws that, if disregarded, could result in losses. The high price of the software can also lower the realistic profit margins that can be expected from your algorithmic trading business. On the other side, creating algorithmic trading software from scratch requires a lot of time, work, and in-depth understanding, and it might need to be more reliable. 

Algorithmic trading software’s core characteristics 

The high level of risk associated with automated trading might result in significant losses. It’s critical to be aware of the fundamental qualities required, whether you want to buy or build. 

Access to market and corporate data 

Every trading algorithm is built to react to current market information and price quotes. A few systems have also been modified to take into consideration business-related information like earnings and P/E ratios. Any algorithmic trading software should include a real-time market data feed and a company data feed. It should be integrated into the system as a built-in feature or have a feature that makes it simple to integrate from outside sources. 

Connection to a variety of markets 

Each exchange may give its data feed in a different format, such as TCP/IP, Multicast, or FIX, which traders wishing to work across several markets should be aware of. Your software should support several feed formats. The use of third-party data suppliers, such as Bloomberg and Reuters, who compile market data from several exchanges and offer it to end users in a standard format, is an additional choice. These aggregated feeds should be able to be processed by the algorithmic trading software as required. 

Latency 

For algorithmic trading, this is the most crucial aspect. The temporal delay that is introduced when data points are transferred between applications is known as latency. Think about the following progression of things. A price quote takes 0.2 seconds to travel from the exchange to your software vendor’s data center (DC), 0.3 seconds to get 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 get to your broker, and 0.3 seconds for your broker to send your order to the exchange. 

Total time spent = 0.1 + 0.3 + 0.2 + 0.3 + 0.4 = 1.4 seconds.

Given the dynamic trading environment of today, numerous price changes would have occurred during this 1.4 second time frame. Your algorithmic trading project could succeed or fail based on any delay. To guarantee that you receive the most current and correct information available without a lag, one must minimize this latency to the absolute minimum.

Since latency has been cut to microseconds, the trading system should make every effort to keep it there. Having direct connectivity to the exchange will allow you to access data more quickly by cutting out the vendor in the middle. You can also reduce latency by optimizing your trading algorithm so that analysis and decision-making take no longer than 0.1+0.3 = 0.4 seconds. Finally, you can cut out the broker and send trades directly to the exchange to reduce latency by 0.2 seconds. 

Personalization and configurability 

The majority of algorithmic trading platforms come with common built-in trade algorithms, like those based on a crossover of the 50-day and 200-day moving averages (MA). A trader might try switching from the 100-day MA to the 20-day MA as an experiment. The trader might be limited by the software’s preset functionality if the parameters can’t be customized. The trading software should be very customizable and configurable, whether it is purchased or created. 

The ability to create original programs 

MatLab, Python, C++, JAVA, and Perl are the most frequent programming languages used to create trading software. The majority of trading software offered by third-party providers allows you to create your own unique program within it. This enables a trader to test out any trading idea. The best software is undoubtedly that which allows you to code in the programming language of your choosing. 

Historical data backtesting feature 

A trading strategy is tested using past data in a backtesting simulation. It evaluates the strategy’s viability and profitability based on historical data, certifying its success (or failure or any needed changes). The availability of previous data on which to do backtesting must also be present in conjunction with this essential aspect. 

Use of the trading interface 

When the appropriate criteria are met, algorithmic trading software automatically places transactions. The program needs to be connected to the broker(s) network to place the trade, or it can connect directly to the exchange to send the trade. 

Integration via plug-and-play 

A trader might utilize a broker’s terminal for placing trades, a Bloomberg terminal for price analysis, and a Matlab application for trend analysis all at once. The algorithmic trading program should have simple plug-and-play integration and accessible APIs across such widely used algo trading tools, depending on individual demands. This guarantees both scalability and integration. 

Independent platform programming 

Some programming languages require specific platforms. For instance, some versions of C++ might only function on a few different operating systems, whereas Perl might work on all of them. Platform-independent trading software that supports platform-independent languages should be prioritized when developing or purchasing trading software. A few months from now, you have yet to learn how your trade will change. 

The underhood information 

According to a proverb, even a monkey can click a button to make a trade. It should not be blind to depend on computers. The trader is the one who needs to comprehend how things work. When purchasing trading software, one should request (and take the time to review) thorough documentation that demonstrates the fundamental reasoning behind a specific algorithmic trading program. If a trading program claims to be a top-secret money-making machine and is an absolute black box, stay away from it.

Being realistic about the solutions you are implementing and being aware of the potential failure situations are important while developing software. Before spending actual money, thoroughly backtest the strategy. 

Where do I start? 

The majority of ready-made algorithmic trading software offers free trial versions with restricted capability or brief trial periods with full functionality. Before making a purchase, fully explore them during these trials. Don’t forget to review the documentation that is accessible carefully. 

The conclusion 

Software for algo trading is expensive to buy and challenging to create on your own. Buying pre-made software provides rapid and timely access and creating your own gives you complete freedom to tailor it to your needs. But you need to be well familiar with the fundamental features of the trading software before engaging in algorithmic trading with actual money. Big losses could arise from failing to do so. In this article we made an effort to understand what tools in algo trading one may need to succeed.