High Frequency Trading on the Coinbase Exchange

I’ve recently started trading bitcoins algorithmically on the new Coinbase exchange. After reading about High-Frequency-Trading in the book Flash Boys by Michael Lewis, I decided I’d give it a shot myself, albeit in a clumsier, more amateurish way.

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Behind the technology at a High Frequency Trading (HFT) stack

Collocation

The first step in High Frequency Trading (HFT) is to place the systems where the exchanges are. Light passing through fiber takes 49 microseconds to travel 10,000 meters, and that’s all the time available in many cases. In New York, there are at least six data centers you need to collocate in to be competitive in equities. In other assets (foreign exchange, for example), you need only one or two in New York, but you also need one in London and probably one in Chicago. The problem of collocation seems straightforward:

  1. Contact data center.
  2. Negotiate contract.
  3. Profit

The details, however, are where the first systems problem arises. The real estate is extremely expensive, and the cost of power is an ever-crushing force on the bottom line. A 17.3-kilowatt cabinet will run $14,000 per month. Assuming a modest HFT draw of 750 watts per server, 17 kilowatts can be taken by 23 servers. It’s also important to ensure you get the right collocation. In many markets, the length of the cable within the same building is a competitive advantage. Some facilities such as the Mahwah, New Jersey, NYSE (New York Stock Exchange) data center have rolls of fiber so that every cage has exactly the same length of fiber running to the exchange cages.

via Barbarians at the Gateways – ACM Queue. A fascinating look at the technology stack behind High Frequency Trading (HFT) companies.

Tracking sentiment for automated HFT

I’m interested in starting HFT. More importantly, I’m interested in tracking sentiment in social networks and news feeds to try and run automated software to trade for me.

Here is my research to date:

  1. Trend or No Trend: A Novel Nonparametric Method for Classifying Time Series by Stanislav Nikolov, S.B., Massachusetts Institute of Technology (2011)
  2. Semantic-Based Sentiment analysis in financial news by Juana María Ruiz-Martínez , Rafael Valencia-García, Francisco García-Sánchez, Facultad de Informática. Universidad de Murcia
  3. Twitter sentiment analysis using Python and NLTK by Laurent Luce.
  4. SharpNLP vs NLTK called from C# review by Sami Badawi (AI Computer Vision).
  5. Machine Learning: Stamford University Online Course.
  6. IAMA 100% automated independent retail trader. I trade around 800k to 1.5 million shares a day and make 2cents/trade on average. AMAA via Reddit
  7. The 500-Millisecond advantage – Flash Orders
  8. T4 Desktop Trading platform (with programmable API for automated trading).
  9. Trading Technologies APIs and FIX Adapter for automated trading.
  10. Twitter Sentiment Corpus for use in training neural networks or Bayesian style heuristical algorithms.
  11. SharpNLP – an open source NLP project port from Java to C#.
  12. DTN News Feed for streaming financial data and news.
  13. Trading Physics Feeds – historical financial data for testing strategies
  14. Recommendations for non-retail data feed and non-retail automated trading platform? via Reddit.
  15. ZeroMQ distributed Message Queue library.
  16. Event Programming with Esper and NEsper.
  17. How I made $500k with machine learning and HFT (high frequency trading) by Jesse Spaulding
  18. JavaScript Machine Learning and Neural Networks with Encog by Jeff Heaton
  19. An Introduction to Encog Neural Networks for C# by Jeff Heaton
  20. Encog CSharp Examples on the Heaton Research wiki
  21. Encog Dotnet examples on Github
  22. Neural Network Indicator for NinjaTrader with C-Sharp by Heaton Research
  23. NinjaTrader on Develop Automated Trading Strategies
  24. The Biased Coin – a HFT blog
  25. Continous LINQ for a LINQ query syntax to create continuous self-updating result sets.
  26. Slinq – Streaming LINQ – a set of extension methods that implement the LINQ pattern geared for constantly changing data.
  27. Tales from a trading desk – a trading blog with a focus on HFT and automated strategies.
  28. Encog-cs source code on Google Code and on Github.
  29. Encog on wikipedia