Why You Shouldn't Use Python for Algorithmic Trading (And Tradestation Instead) - [Easylanguage] (2024)

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Last Updated on 18 May, 2023 by Samuelsson

Algorithmic trading is becoming increasingly popular, and many financial professionals are turning to Python to make it easier and more efficient. While Python is a powerful language that can be used to create sophisticated trading strategies, it is not necessarily the best choice for algorithmic trading. In this article, we will discuss why Tradestation’s Easylanguage may be a better choice for algorithmic trading, and how it can provide more efficient and effective strategies than Python. We will also look at the advantages and disadvantages of both languages, and why Tradestation’s Easylanguage may be the right choice for experienced traders.

When traders look into learning algorithmic trading, they have to choose not only a trading platform, but also a programming language. There are many options on the market, and while some use their own platform specific coding language, others use python or C++.

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So why should you then not use python in algorithmic trading? Well, the answer is quite simple. You should not use python in algorithmic trading because finding trading strategies isn’t about how complex things you build, but rather how many ideas you have time to test. There are alternatives to python on the market that will let you build strategies far quicker.

These also come with the benefit of being very easy to learn for beginners, while still offering all the features most traders will ever need.

Let’s have a closer look at why we believe that you should go for another option than python, when beginning your algorithmic trading career!

Trading Strategies Don’t Require Complexity!

One of the most common misconceptions among new traders is that a good strategy is a complex strategy. Traders who have come to a stage where they are profitable, know that reality is quite the opposite. In other words, they don’t need an advanced coding language like Python!

The best strategies, more often than not, are those that are very simple. When you design a trading strategy, you want to use as few conditions as possible. Complex strategies with numerous conditions are far more prone to curve fitting than simple strategies. This means that a simple strategy continues to work in out of sample more often than a complex strategy.

In fact, some of our best strategies consist of as few as one or two rules, sometimes not even optimizable! These types of edges exist for sure, and finding them is only a matter of testing enough ideas! This means that for these types of strategies, python adds very little value, since it can be coded much more easily, and quicker, with an easier coding language.

Examples of Simple Strategies

Just to give you a better idea of what you can do with as little as 2 conditions in a trading strategy, have a look at these two trading strategies! The first one trades the RB futures market, while the second trades the S&P 500!

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Why You Shouldn't Use Python for Algorithmic Trading (And Tradestation Instead) - [Easylanguage] (3)

Hopefully, these images succeed in getting the message across!

The Importance of Speed – Python VS Easylanguage

As we already have touched on, you really want to be able to test as many ideas as you possibly can. Finding edges that can form algorithmic trading strategies is hard, but not impossible. It requires that you continue testing idea after idea until you eventually find an edge!

This is where speed comes into play! An easy coding language that’s faster than python enables you to quickly jot down ideas without wasting time on complicated coding exercises. The time that would have been spent on programming can now be spent on testing more strategies, yielding more trading strategies for you to trade in the long run!

In fact, this is especially crucial when it comes to new traders, who don’t have strategies to trade. They need to be able to run through as many tests as they can, to quickly find strategies that can start generating money for them. Algorithmic trading is hard as it is, and making it even harder by imposing an additional barrier in the form of a somewhat heavy coding language, is unnecessary!

Python trading strategies

If you are a good coder you can find a lot of interesting trading strategies here written in plain English and TradeStation code. If you are a good coder you will probably quite easily code the trading strategies from plain English to a Python trading strategy. If you are interested in python trading strategies you can read more here.

Python Leads to Wrong Focus for New Traders

As a new trader, you need to take in many new concepts and facts. And if that wasn’t enough, you often need to tackle emotionally challenging experiences, such as drawdown and loss of faith in trading itself. If you don’t know python well from the beginning, your main focus, in the beginning, will probably become learning how to code. This removes attention and focus from the other areas of trading that are critical for your success.

In this regard, python isn’t the best choice for a new trader. While it is comparably easy to learn when compared coding languages like C++, it will take a lot of time to master!

In the end, it does not matter how hard you made it to code the strategy. What matters is the logic that you coded, and that is made more easily in other coding languages.

The Best Coding Language for Algorithmic Trading

So what is the best programming language for algorithmic trading? The goal of this article isn’t to make the point that python is a substandard or a bad coding language. It’s not!

However, we believe that there are better alternatives to python when it comes to algorithmic trading.

According to us, the best coding language for algorithmic trading right now is Easylanguage, which comes with the TradeStationtrading platform. This is a coding language that most of our students in our algorithmic trading course use, and it has enabled them to learn to trade much faster, since they haven’t had to struggle too much with learning how to code!

Easylanguage

Why You Shouldn't Use Python for Algorithmic Trading (And Tradestation Instead) - [Easylanguage] (4)

As its name implies, Easylanguage is very easy to learn. Someone new to it will be able to learn to code their ideas very fast, and will soon build their own strategies.

However, the simplicity of Easylanguage doesn’t mean that you are confined to only basic ideas. While Python sure has greater capabilities, you will hardly miss anything if you choose to go with Easylanguage. We use Easylanguage ourselves, and find that it does close to anything we want from it!

Not Limited to One Platform

If you know Easylanguage, you also know Powerlanguage!

Powerlanguage basically is the same as Easylanguage, and both languages are cross-compatible. The difference lies in that Powerlanguage is used by Multicharts, which is another great trading platform.

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While Tradestation is a trading platform, broker, and data provider, Multicharts only is a trading platform. However, that means that you are free to choose your broker as well as data provider, and can customize your experience to your liking!

In other words, contrary to what you might have believed, learning Easylanguage does not mean that you are at the whim of the developers at one trading platform only! You may switch from TradeStation to Multicharts, and keep all your strategies as they are! Issues seldom arise when moving code from one platform to the other!

Conclusion

As a new trader, you shouldn’t focus on coding! Nobody will build a strategy simply because of their great coding skills. Instead what counts, is how fast and efficiently you are able to test and discard ideas.

While python is a great coding language, it cannot hold up with the speed of Easylanguage/Powerlanguage, since the latter is so much easier!

If you are interested in algorithmic trading we recommend that you have a look at our MASSIVE 10 000 words long guide to algorithmic trading!

Here you can read more about algotrading in our archives.

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Why You Shouldn't Use Python for Algorithmic Trading (And Tradestation Instead) - [Easylanguage] (2024)

FAQs

Is Python good for algorithmic trading? ›

Python has the most comprehensive and mature ecosystem of libraries for data science, which makes it a perfect programming language for algorithmic trading. Most strategies rely on technical indicators, time series models, or machine learning algorithms, and Python is the ideal language for implementing them.

What is the best language for algorithmic trading? ›

If you want to get a job in systematic trading, two coding languages have long been the key: Python and C++, but a new and non-scientific study of languages used to write open source trading algorithms suggests there's another possibility: Javascript.

Is Python better than R for algo trading? ›

Python is better for Algo trading. Although R has good statistical support, Python has advantage in terms of interface, object oriented programming and parallel processing.

What is the problem with algorithmic trading? ›

Other Risks of Algorithmic High-Frequency Trading

Volatility swings worsened by algorithmic HFT can saddle investors with huge losses. Many investors routinely place stop-loss orders on their stock holdings at levels that are 5% away from current trading prices.

Is Python trading profitable? ›

You can expect 0.6-1% of profitability in a low volatility market. In that case, you can expect to earn around 20% every month. This means, by investing US$10,000 money, you can earn US$2,000 every month with the help of Python stock trading bots.

Which platform is better for algorithmic trading? ›

Interactive Brokers

It's one of the most popular platforms for paper trading, allowing access to 150 markets. It's also one of the best brokers for algorithmic trading with affordable pricing.

What is the best language for high frequency trading? ›

C++ C++, a middle-level programming language, is a blessing for traders as the components of High-Frequency Trading (HFT), which are latency-sensitive, are usually developed in C++. This is because C++ is extremely efficient at processing high volumes of data.

What is the best programming language to build a trading bot? ›

There are many programming languages that can be used for building trading bots, including Python, Java, C++, and more. Python is a popular choice due to its simplicity and availability of libraries and frameworks specifically designed for financial analysis and trading.

Which programming language is best for crypto trading? ›

C++ C++, introduced back in 1985 by Bjarne Stroustrup, is the best programming language for cryptocurrency development. The language follows OOPs methodology and is highly used for developing cryptocurrencies like Bitcoin, Litecoin, Ripple, Stellar, and EOS.

What are the disadvantages of algo trading? ›

Disadvantages of Algo Trading
  • Knowledge of the programming language- Formulating complex algorithms requires extensive know-how of coding software such as C+, C++, Java, Python, R, etc. ...
  • Dependence on technology - Faulty algorithms have the potential to result in insurmountable losses for the trader.

Which machine learning algorithm is best for trading? ›

Some popular reinforcement learning algorithms used in trading include Q-learning and Monte Carlo Tree Search (MCTS). These algorithms are commonly used to optimize trading strategies, identify patterns in market data, and make buy or sell decisions.

What is the best Python for trading? ›

Best Python Libraries for Trading
LibraryDescriptionAdvantages
ta-libtechnical indicators– Fastest library available (backend in C)
backtesting.pybacktesting framework– Intuitive event-driven approach – Actively maintained
vectorbtbacktesting framework– Easy to deploy to live-trading – Fast execution times
4 more rows

Why do Algo traders fail? ›

There are many reasons why Algo trading fails like the algorithm strategy is not being tested properly before the implementation. Or accurate data is not used to develop the stock trading algorithm software that fails to give profits to traders, let's find out more.

Has anyone made money from algorithmic trading? ›

Yes, it is possible to make money with algorithmic trading. Algorithmic trading can provide a more systematic and disciplined approach to trading, which can help traders to identify and execute trades more efficiently than a human trader could.

Can you make a living with algorithmic trading? ›

Yes, you can make money with automated trading (also known as algorithmic trading), but like in any other form of trading, most traders fail to make money with it. Trading is hard, so you need to put in a lot of hours to have a chance at making money.

What is the best Python framework for algo trading? ›

  • Pandas. Pandas is a machine learning library in Python. ...
  • Scikit-Learn. Scikit-Learn is a machine learning library built on NumPy, SciPy, and Matplotlib. ...
  • Numpy. Numerical Python (Numpy) is a fundamental library for performing numerical calculations with Python.

Do quant traders use Python? ›

Python, MATLAB and R

All three are mainly used for prototyping quant models, especially in hedge funds and quant trading groups within banks. Quant traders/researchers write their prototype code in these languages. These prototypes are then coded up in a (perceived) faster language such as C++, by a quant developer.

Can Python help in stock market? ›

Python is a powerful programming language that offers a wide range of tools and libraries for retrieving, analyzing, and visualizing stock market data.

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