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When using algorithmic trading, traders trust their hard-earned money to their trading software. For this reason, the right computer software is essential to ensure efficient and accurate execution of trading orders. On the other hand, a faulty software, or one without the required features, can lead to huge losses, especially in the lightning fast world of algorithmic trading.
An algorithm is defined as a specific set of step-by-step instructions for completing a specific task. Whether it’s a simple but 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.
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Algorithmic trading is the process of using a computer program that follows a set set of instructions to submit a trade order. The goal of the algorithmic trading program is to dynamically identify profitable opportunities and place trades in a way that generates profits with a speed and frequency that cannot be matched by a human trader. Given the advantages of increased accuracy and lightning speed of execution, trading activities based on computer algorithms have gained immense popularity.
How Much Does It Cost To Develop An Automated Trading System?
Algorithmic trading is dominated by large trading firms such as hedge funds, investment banks and proprietary trading firms. Given the abundant availability of resources due to their large size, such firms typically build their own proprietary trading software, including large trading systems with dedicated data centers and support staff.
On an individual level, experienced proprietary traders and quants use algorithmic trading. Proprietary traders, who are less tech-savvy, can purchase off-the-shelf trading software for their algorithmic trading needs. The software is offered by their brokers or purchased from third party vendors. Quants generally have a good understanding of both trading and computer programming and develop trading software themselves.
Buying off-the-shelf software gives you fast and timely access, while creating your own allows you the flexibility to customize it to your needs. Automated trading software is often expensive to buy and can be full of loopholes which, if ignored, can lead to losses. The high cost of the software could also reduce the realistic profit potential of your algorithmic trading business. On the other hand, building algorithmic trading software yourself takes time, effort, deep knowledge, and may not be foolproof anyway.
The risk involved in automated trading is high, which can lead to large losses. Regardless of whether you decide to buy or build, it’s important to know the key features you need.
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All trading algorithms are designed to act on real-time market data and prices. Some programs are even customized to take into account company fundamentals such as earnings and P/E ratios. Any algorithmic trading software should have a real-time market data feed as well as a business data feed. It should be available as built into the system or should have provision for easy integration from alternative sources.
Traders wishing to work on multiple markets should keep in mind that each exchange may provide its data stream in a different format, such as TCP/IP, Multicast or FIX. Your software should be able to accept data streams of different formats. Another option is to turn to third-party data providers such as Bloomberg and Reuters, which aggregate market data from different exchanges and deliver it in a unified format to end customers. Algorithmic trading software should be able to process these aggregate streams as needed.
This is the most important factor for algorithm trading. Latency is the delay introduced in moving data points from one application to another. Consider the following sequence of events. It takes 0.2 seconds for a quote from the exchange to reach the software provider’s data center (DC), 0.3 seconds from the data center to the trading screen, 0.1 seconds for the trading software to process this quote received, 0.3 seconds for you to analyze and execute a trade, 0.2 seconds for your order to reach your broker, 0.3 seconds for your broker to indicate your order on the exchange.
In today’s dynamic trading world, the initial price quote would change many times during this 1.4 second period. Any delay could make or break your algorithmic trading venture. You need to keep this latency as low as possible to ensure you receive the most up-to-date and accurate information without time lag.
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Latency 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 connecting directly to the hub to receive data faster, eliminating the vendor in between. Improve the trading algorithm so that it takes less than 0.1 + 0.3 = 0.4 seconds to analyze and make decisions. or eliminating the broker and sending trades directly to the exchange to save 0.2 seconds.
Most algorithmic trading software offers built-in standard trading algorithms, such as those based on the intersection of a 50-day moving average (MA) with a 200-day MA. A trader may want to experiment by switching the 20-day MA with the 100-day MA. Unless the software offers such customization, the trader may be limited by the built-in fixed functionality. Whether it is buying or manufacturing, trading software should have a high degree of customization and configurability.
MatLab, Python, C++, JAVA and Perl are the common programming languages used to write trading software. Most trading software sold by third-party vendors offer the ability to write your own custom programs in it. This allows a trader to experiment and test any trading concept. Software that offers coding in the programming language of your choice is obviously preferred.
Simulated backtesting involves testing a trading strategy on historical data. Evaluate the practicality and profitability of the strategy against past data, certifying success (or failure or any necessary changes). This mandatory feature must also be accompanied by the availability of historical data that can be audited retrospectively.
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Algorithmic trading software automatically places trades based on the occurrence of desired criteria. The software should have the necessary connectivity to the broker network to place the trade or connect directly to the exchange to send trade orders.
Understanding the commissions and costs of trading with various brokers is important in the planning process, especially if your trading approach uses frequent trades to achieve profitability.
A trader can simultaneously use a Bloomberg terminal for price analysis, a broker terminal for trading, and a Matlab program for trend analysis. Depending on the individual needs, the algorithmic trading software should have easy plug-and-play integration and API available to all these widely used trading tools. This ensures scalability and integration.
Some programming languages require dedicated platforms. For example, some versions of C++ can only run on certain operating systems, while Perl can run on all operating systems. When building or purchasing trading software, trading software that is platform-independent and supports platform-independent languages should be preferred. You never know how your trading will turn out in a few months.
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A common saying goes: “Even a monkey can click a button to make a transaction.” Computer addiction should not be blind. It’s the dealer who needs to understand what’s going on under the hood. When purchasing trading software, you should ask for (and take the time to review) detailed documentation that shows the underlying logic of a particular algorithmic trading software. Avoid any trading software that is a complete black box and claims to be a secret money making machine.
When building the software, be realistic about what you’re implementing and be clear about the scenarios in which it might fail. Test the approach carefully before using real money.
Ready-made algorithmic trading software usually offers free trials with limited functionality or limited trial periods with full functionality. Explore them fully during these tests before buying anything. Don’t forget to read the available documentation in detail.
Algorithmic trading software is expensive to buy and difficult to build yourself. Buying software out of the box gives you quick and timely access, and building your own allows you the flexibility to customize it to your needs. However, before you start algorithmic trading with real money, you need to fully understand the basic functionality of the trading software. Otherwise, heavy losses may occur.
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