Finding Advanced Machine Learning Resources for Trading
Article Quant Q&A · Author: Flake
Summary
The document collects suggestions for learning about machine learning and data mining with an interest in trading. Recommendations include general machine learning courses, practitioner blogs, a software resource catalog, Q&A communities, and a time-series prediction competition. It also points to research aggregation and strategy review sites. These are leads for further study rather than a unified trading method or a tested strategy.
The answers reflect different levels of relevance: several resources teach general machine learning, while others occasionally cover quantitative finance or offer competitions with financial data. One response describes applying machine learning to fraud detection and suggests that trade classification could be possible, but does not present evidence that such a classifier would be profitable. The discussion is an informal snapshot of resources and opinions, not a systematic review. It gives no comparative assessment of source quality, trading performance, or whether the listed materials remain available or current.
Key ideas
- General machine learning courses can build methods relevant to trading even when their examples are outside finance.
- Practitioner blogs and research aggregators may provide occasional quantitative trading material.
- Software catalogs, Q&A communities, and prediction contests can help researchers find tools and applied problems.
- The document offers resource leads rather than a tested trading strategy or evidence of investment performance.
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Full text
# Excellent information source on advanced machine learning / data mining based trading? # Excellent information source on advanced machine learning / data mining based trading? I did check the related posts, like this one here. However, given if one already has knowledge in finance, machine learning and statistics, and wants to know something more advanced on machine learning based trading rather than the introductory. What would you recommend? I am looking for anything related: excellent books, research papers, posts, authors, as long as it is related to machine learning and trading in general, but the thing is, really looking for the sources with quality content rather than the ads sites. ## Answer by Tal Fishman (score 18) https://quant.stackexchange.com/a/2144 Stanford University has a free online course in machine learning with video lectures, problem sets, and even a promise of online help with coursework from Stanford faculty. > This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). (iv) Reinforcement learning. The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas. It does not appear as of yet that trading is one of the applications they intend to cover, but you never know... ## Answer by vonjd (score 14) https://quant.stackexchange.com/a/2049 As the others have already mentioned, this is a very broad question. Anyway, as a starting point there are some blogs that come to my mind that have some up to date high quality content on these issues from time to time: - http://quantivity.wordpress.com/ - http://epchan.blogspot.com/ - http://www.automated-trading-system.com/ - http://intelligenttradingtech.blogspot.com/ ## Answer by Branson (score 12) https://quant.stackexchange.com/a/2064 I think R's CRAN Task Views on Machine Learning is an excellent resource for beginners moving to advanced algorithm traders. It is well-structured, broad, up-to-date, and ready-to-use! http://cran.r-project.org/web/views/MachineLearning.html I believe all advanced quantitative traders already know this. But I haven't seen anyone post it here and Flake's related post. ## Answer by 楊祝昇 (score 7) https://quant.stackexchange.com/a/2977 From this site's perspective, I think nothing would be better than a ML.SE. Finally, we got one awhile ago. UPDATE: Unfortunately, Machine Learning is merging into Cross Validated. To learn more detail, click here." I have no idea why SE admin was rush to merge ML into CrossValidated. Not a fan of it (Orz). I personally prefer a separate site. FYI, http://metaoptimize.com/qa/ is also a great Q&A community for ML, but I do hope we can have our own party room on SE. :) ## Answer by columbus (score 6) https://quant.stackexchange.com/a/2062 In 2010 Informs and Kaggle organized time series prediction contest. The methods used by competitors are described here. ## Answer by Heavywood (score 4) https://quant.stackexchange.com/a/2537 There is another artificial intelligence online course co-sponsored by Stanford http://www.ai-class.org/ The class is about to finish, but you can login as a visitor to access the lecture video and handouts. ## Answer by Stefan Martinek (score 4) https://quant.stackexchange.com/a/8703 These 2 sites are relevant: - The Whole Street (research aggregation) - Oxford Capital Strategies (strategy reviews) ## Answer by rtybase (score 2) https://quant.stackexchange.com/a/3237 I think applying ML techniques to Finance is a work in progress and here are my arguments: - Things like fraud detection are already implemented using ML (personal experience). It should be possible to train a classifier that would tell you when to (or not to) trade. - Have a look at this site http://www.kaggle.com/, from time to time you will find financial related competitions (another indication of the work in progress). - Big players are getting engaged into this game with commercial products: http://www.fico.com/en/Products/DMApps/Pages/FICO-Falcon-Fraud-Manager.aspx http://www.oracle.com/us/dm/h2fy11/advncdanalytics-1568353.html?msgid=3-6193843811
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