Algorithmic formulas are allowing quant trading to take over the financial capitals of the world. Math technologies are helping even the most novice traders conquer the stock market. But with so many trading software in the market, how do you choose the best one to use? The programming language on which the software is built is an excellent place to start.
Which Programming Language Is Best for Trading Software
The best programming language for trading is, by and large, determined by the transparency and ready-made features that the software built on it makes possible. Other things to consider are its strategy parameters, resiliency, general performance, and cost.
Excellent algorithmic trading software should include second-to-none research tools, execution engine, risk manager, and portfolio optimizer. Faulty software or one lacking the necessary features could be the reason you incur huge losses of your hard-earned cash. The following are some of the most preferred programming languages for trading software.
R programming language has been a choice language for statisticians and academics for over two decades. It is often the go-to programming language for statistical analysis. Primarily, R does what spreadsheets do, but faster and with greater ease.
What makes it stand out as a trading software is its benefits in data wrangling (tidying up data for use), data transformation (creating custom data sets), data analysis (executing statistical models), and practically all machine learning and visualization forms. R makes algorithmic trading a somewhat straightforward undertaking. That said, some intrinsic limitations show up as a trader’s needs increase.
Python easily stands out as a trading programming language because of the ease with which it can be deployed in automated trading systems and machine learning. It is quite easy and straightforward for beginners to learn. It also has exclusive library functions that make it easy to code strategies in algorithmic trading.
Many traders prefer Python over C because it is faster in evaluating mathematical models. Given the centrality of speed in high-frequency trading, the less trading strategy time that Python affords the trader is a big part of its allure. However, it is somewhat slower than C++.
Like R, MATLAB is a programming language of choice for quantitative traders and researchers. Because of its focus on technical computing, MATLAB is an excellent choice for automated trading. What’s more, MATLAB is an integrated development platform with a user-friendly interface and debugger.
MATLAB easily stands out in backtesting compared to Visual Basic or Excel because it has an extensive database of built-in functions that are extremely helpful mathematical computations. For traders analyzing a large number of stocks simultaneously, MATLAB’s matrix manipulation and processing make such calculations as easy as analyzing a single stock. That said, it can be restrictive and somewhat risky when it comes to availability.
MetaQuotes Language 5 (MQL5) is designed for algorithmic trading and is supported by a powerful community of helpful, highly skilled developers. It is an excellent programming language for creating utility applications, trading robots, and technical indicators that automate financial trading. Unlike other programming languages, MQL5 is designed primarily for financial trading. It, therefore, comes with an impressive list of built-in technical analysis functions and trade management features.
On top of its ease of use and extensive features, MQL5 is also fully compatible with R and Python. What that means is you can leverage the power of the most advanced programming languages within the MQL5 development environment. With that, you have the best of both worlds.
MQL5 makes it relatively easy to create automated financial trading and market analysis applications. Through the use of MLQ5 and other languages like R and Python, you can perform practically any type of data analysis and trade operation you can think of. On top of that, it makes it easy for traders to carry out trading operations and technical analysis in stock and forex exchange markets.
How to Choose the Best Trading Software
The best automated algorithmic trading software makes it easy to trade and increases profitability. Instead of creating custom trading software and platforms, the better approach is finding a trading application that checks all the necessary boxes to turn a profit. Here are some of the things to check for in trading software:
Supports all markets
The software you choose for financial trading should accept feeds in different formats, including FIX, Multicast, and TCP/IP. Go for algorithmic trading applications with the ability to process aggregated market feeds from an array of exchanges.
The best trading software should allow you to trade in different markets over multiple accounts while leveraging several strategies simultaneously. For instance, MetaTrader 5 enables hedge funds to diversify their trades and, as a result, spread their risk over many instruments and markets.
Offers data analysis tools
Traders have to keep tabs on the goings-on in the market in real-time. Without up-to-date information, the decisions you make as a trader could result in losses that could have been avoided. Go for trading software with data analysis tools that give you insights into what’s happening on trading floors live. Well-designed trading software like MetaTrader 5 goes a notch further; they show you visual trading representations through bars, broken lines, and Japanese candles.
Any trading software whose market and company data is not readily available for you to review is a no-go-zone. Algorithmic trading uses your hard-earned cash. You must ensure you know enough about the software you’re about to use for trading as well as the company that built it.
Go for trading software that values transparency. Work with a company that explains how they invest their money and the profit your investment is making—the ability to see the company data should be a built-in feature in the software.
Automated and fully prepared robots
The whole idea of leveraging mathematical technologies in trading is to make an otherwise tricky trading process possible and easy even for novice traders. Therefore, working with a trading platform with automated robots that do all the heavy lifting makes sense. For instance, MetaTrader 5 trading robots can analyze financial instruments quotes and execute trade operations on exchange and Forex markets.
The software also allows hedge funds to create, test, debug, implement, and optimize trading robots. And if the robots available are falling short of your requirements, there’s an option to order a trading robot to be custom-built for you.
Few things are as dreadful as investing money in an opaque trading platform where it’s impossible to tell where your money is and whether it’s returning a profit. To avoid the worry and uncertainty that such scenarios can bring, use trading software with one-click communications.
Trade with applications that make it easy to ask questions and get answers back. MetaTrader 5 goes a step further: it eliminates uncertainty by offering real-time fund performance with detailed reports to help you keep tabs on your algorithmic trading round the clock.
Building your own trading software is complex and often overwhelming, and most algorithmic trading software is costly. Yet, there are excellent options that live up to the pressures of exchange and forex trading and increase the chance that you’ll turn a profit. Few algorithmic trading software can match the power of MetaTrader 5 for hedge funds.
Users of this trading software can harness its capabilities by integrating it into practically any brokerage account. And with expert robotic advisors that implement automated strategies, the trading floor is open even for people with little or no programming and trading experience. In this highly competitive world, choosing the right mathematical technologies for trading is often the difference between making lots of money and wiping out your investment.