Choosing the Best Trading Algorithm Software

 

Algorithmic trading relies on traders placing their trust in their trading program. Because of this, it is critical to use the right computer software to ensure that trade orders are properly executed. The downside is that incorrect or missing features can result in massive losses in the fast-paced realm of algorithmic trading.

 

Algorithmic Trading: A Quick Overview

There are many different kinds of algorithms, but they all follow the same basic structure. An algorithm underlies all computer programs, from Pac-Man to spreadsheets with a bewildering array of options. Even simple games like Pac-Man may be addicting.

Computer programs that follow a predetermined set of instructions are used in algorithmic trading to place a trade order. Algorithmic trading programs are designed to detect profitable opportunities and place trades in order to earn profits at a rate and frequency that a human trader simply cannot compete with. Trading operations based on computer algorithms have grown enormously in popularity due to the advantages of increased accuracy and lightning-fast execution speed.

 

Algorithmic trading software is used by whom?

Hedge funds, investment banks, and proprietary trading organizations wield a disproportionate amount of power in algorithmic trading. For this reason, and since they have the resources, these companies often develop their own trading software and data centers and support teams.

Expert proprietary traders and quants utilize algorithmic trading on a smaller scale at home. Algorithmic traders who aren't as tech-savvy as proprietary traders can buy pre-made trading software. Both their brokers and third-party sources can supply the software. It is well knowledge that quants have a strong background in both trading and computer programming and the ability to create their own trading software.

 

Is It Better to Build or Buy Algorithmic Trading Software?

There are two ways to get your hands on algorithmic trading software: either building it yourself or purchasing it already built.

 

Purchasing ready-made software provides immediate access while making your own gives you the freedom to tailor it to your specific needs. Automated trading software can be expensive to acquire and may have numerous vulnerabilities that could result in losses if ignored. Software costs might significantly slash your earning potential from the algorithmic trading business. While designing your own algorithmic trading program requires time, effort, and a lot of knowledge, it may not be completely foolproof.

 

Algorithmic Trading Software's Most Important Features

Automated trading carries a high level of risk and the potential for huge losses. You need to know what you're getting yourself into regardless of whether you buy or create.

 

Affordability of Market and Firm Data

Data and price quotes are the primary inputs for every trading algorithm. To account for corporate fundamentals like earnings and P/E ratios, certain algorithms are also modified. A real-time market data stream and a company data feed are essential for any algorithmic trading software. It should either be built into the system or have the ability to be easily integrated from other sources.

 

Access to a Variety of Markets

In order to work across numerous markets, traders must understand that each exchange may give its data feed in a different format, including TCP/IP, Multicasting, or FIX. You should be able to take feeds in a variety of formats using your software. Bloomberg and Reuters are two examples of third-party data providers that may gather market data from a variety of exchanges and deliver it to end customers in a consistent way. Algorithmic trading software should be able to handle these streams as needed.

 

Latency

For algorithmic trading, this is the most critical aspect. Latency refers to the amount of time it takes for data to transit between applications. Here are some possible outcomes to consider: When you receive a price quote from the exchange, it takes 0.2 seconds for it to arrive at your trading software vendor's data center (DC), 0.3 seconds for the data center to reach your screen, 0.1 seconds for your trading software to process this received quote, and then 0.3 seconds for it to analyze and place a trade.

 

It took 1.4 seconds for the timer to run out of time.

 

The original price quote would have changed numerous times in this 1.4-second timeframe in today's dynamic trading market. In the world of algorithmic trading, any delay could spell the end of your business. In order to acquire the most up-to-date and correct information, one must keep this latency as low as feasible.

 

In order to keep latency as low as feasible, trading systems must make every effort to do so. As a result of these steps, latency can be reduced by as much as 0.1+0.3 = 0.4 seconds, or by eliminating the broker and directly delivering trades to the exchange.

 

The ability to alter and tailor the design to suit the needs of the user

Trade algorithms based on a crossover of the 50-day and 200-day moving averages (MAs) are common in algorithmic trading software. It is possible for a trader to experiment with the 20-day and 100-day MAs by switching. The trader may be confined by the built-in fixed functionality if the software does not allow for parameter customization. Regardless of whether the software is purchased or built, it should be highly customizable and configurable.

 

The ability to create your own software.

Trading software is typically written in Matlab, Python, C++, JAVA, and Perl. The majority of third-party trading software allows you to create your own unique programs. There is no limit to what a trader may do here. To have a choice in programming languages available is a definite plus.

 

Using Historical Data for Backtesting

Testing a trading technique using past data is known as backtesting. based on previous data, it certifies the strategy's viability and profitability (or failure or any needed changes). This must be complemented with the availability of previous data that can be used for backtesting purposes.

 

Incorporation of Trading Interfaces

Software that uses algorithms to place trades automatically is known as algorithmic trading. Direct contact with the exchange or broker network is required for placing trades, and the program should also have this capability.

 

With frequent trades, understanding fees and transaction costs with multiple brokers is essential in the planning process.

Effortless Consolidation

A trader may concurrently be utilizing a Bloomberg terminal for price analysis, a broker's terminal for placing trades, and Matlab software for trend analysis. Algorithmic trading software should be able to be easily integrated into a wide range of popular trading platforms, such as MetaTrader and MT4. This ensures scalability and integration.

 

Flexible, Cross-Platform Development

Dedicated platforms are required for a few computer languages. While Perl can be run on any operating system, some versions of C++ can only be executed on certain operating systems. When developing or purchasing trading software, platform-independent and platform-independent languages should be prioritized. It's impossible to predict how your trade will change in a few months.

 

The Stuff That's Hidden from View

According to an old adage, "Even a monkey can press a button to trade." It is important to remember that computers are not a substitute for human interaction. It is the trader's responsibility to know what's going on in the engine compartment. When purchasing trading software, one should request (and take the time to read) the extensive documentation that explains the algorithmic trading software's underlying logic. You should avoid any trading software that claims to be a secret moneymaking machine if it is completely black-boxed.

 

Don't be afraid to think about the worst-case scenarios for your software when you're coding. Be sure to do a lot of backtesting before putting your money on the line.

 

How Do I Get Started?

Automated trading software typically comes with a free trial edition or a limited trial period that includes all of the software's features. Before making a purchase, take advantage of these free trials to learn all about them. Make sure you thoroughly review all of the accessible documentation.

 

Quantopian, a free online platform for testing and developing algorithmic trading, is a wonderful place to start if you plan to construct your own system.

 

There are a number of ways in which individuals can experiment with current algorithms or build their own. Algorithmic trading software can be tested against the market data on the platform.

 

You can build your algorithmic trading software with Finage free API key.

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