The top 10 resources for algorithmic trading

A brief introduction to the most useful resources for developing a trading algorithm. We have compiled our 10 best tools for you. From new ideas for strategies to portfolio analysis and visualization, everything is included. If you have any questions or remarks, you can reach us at any time via the contact form or the chat.

The top 10 ressources in overview


One of the best places to get the development of your algorithm started. Here you can find explanations to all relevant questions as well as inspirations for your own algorithms and much more. In essence, Investopedia is the Wikipedia for investors and covers almost everything in this area. In the linked article you will find examples for strategies next to advantages of algorithmic trading for optimizing your return.

Portfolio Analyze

There are a number of tools for analyzing your own portfolio. Quantopian in particular provides some open source solutions like Pyfolio. There you can get some visualization options, different degrees of uncertainty can easily be added to a static set of data points. Note Pyfolio is written in Python. A library written in JavaScript promises similar functions on GitHub.

Data analysis and manipulation

Pandas is a Python tool used by some of the largest Quant-funds. Specially created by AQR Capital Management to manipulate numerical tables and time series data. It promises high performance and easy usability. Pandas is continuously being developed by a growing community.   


The free open source software from Google. It offers individually programmable applications for many use cases. Inputs can be processed in different levels of abstraction to generate the desired output by means of machine learning algorithms or neural networks. For the Trump2Cash strategy, for example, the sentiment analysis can be used.  

Current Open-Source Research

Hudson&Thames is building the library MlFinLab with the goal to make the most up-to-date quantitative research available to everyone. MlFinLab helps portfolio managers and traders alike to harness the power of machine learning in an easy to use, reproducible tool. They believe that scientific methods are the best way to approach asset management or wealth accumulation. What should we say against this. 


Backtrader helps you spend more time developing strategies than maintaining infrastructure. Simple examples of strategies like the Simple Moving Average Crossover Strategy and many more features help you to test and optimize strategies. In combination with the live testing of this is a powerful weapon for your success. Of course completely open source on GitHub. 


Community platforms

No neutral article on quantitative investing can avoid Quantopian. The largest platform for crowdsourcing of profitable strategies. Just like its competitors QuantInsti or Quantconnect, Quantopian attracts with extensive data and tools for the back testing of strategies. However, this data cannot be streamed or downloaded for personal use. 

More data sources

There are some interesting providers for historical data. In the Americans, this is next to the Yahoo Finance API, rumor has it still works, especially Quandl. A service from Nasdaq, which provides a whole range of other alternative data packages for private users. These are exciting data on the number of cars sold in the USA, the activities of companies on the job market and the expenditure of publicly listed companies. You just need to find the right correlation and are good to go.

Charting Tools

With Tradingview we introduce you to one of the most innovative charting tools. There you can develop small automations in their own script language as well as trade with technical indicators. They offer a great variety of indicators and charts, but at the moment there is still a lack of brokers for the European market.

Order Execution

Our Focus is on providing you a REST-API that enables to create and execute orders at the stock market as well as retrieving market data in real time to equip you with the tools for building your own strategy.