Stock Prediction using Decision Tree: Classification Tree

This is the fourth post in a series on using Decision Tree for Stock Prediction. For more information, feel free to read post 1, post 2 and post 3 of the series.Once the data have been preprocessed, we obtain a matrix in which each row is a different day (since we work with daily data) and each column is one of the possible variable (close, volume, technical… Continue reading... | 10 Comments
  • Share/Bookmark

Data Mining using SAS Enterprise Miner

I have recently found two new books about data mining. The author of these two books is Randall Matignon. He works at Amgen, Inc. in South San Francisco, California. He is a SAS/Microsoft Office VBA programmer with more than twenty years of experience. His expertise domains include pharmaceutical healthcare and biotechnology industries… Continue reading...
  • Share/Bookmark

Decision Tree for Stock Prediction: Data Preprocessing

This post is part of a series on Decision Tree for Stock Prediction. For more details feel free to read part 1 and part 2 of the series.Once the stock have been filtered, a list of stocks for every months of the shifting window system is available. Then, two steps need to be undertaken: calculation of technical indicators and standardization of data. First, data is separated in training… Continue reading... | 1 Comment
  • Share/Bookmark

New Data Mining Blogs: Datalligence and Life Analytics

I'm happy to highlight two new blogs that discuss data mining, among others. The first is Datalligence, a blog written by Romakanta. His blog is about "Analytics/Data Mining, Marketing Research, Survey Programming" and he started it in June 2008. The second blog is Life Analytics, maintained by Themos Kalafatis. The subject of this blog is "Practical Applications of Data Mining, Text Mining and Information Extraction techniques"… Continue reading...
  • Share/Bookmark

Decision Tree for Stock Prediction: Stock Filtering

This post is the second from a series on Decision tree for stock prediction. The first post is available here.Before using decision tree on each stock separately to make its prediction, the stock universe has to be narrowed down. The "business" reason is that, in my case, we are only interested by big capitalization. The "technical" reason is computational power. Indeed, computing predictions for every stock among all possible… Continue reading... | 4 Comments
  • Share/Bookmark

  • Data Mining Search Engine

  • Reading Recommandations

  • T-shirts, Mugs & Mousepads

  • Archives

  • Pages

  • Disclaimer

    The opinions discussed on Data Mining Research are my own and do not reflect the position of my current employer, FinScore. The views and opinions expressed by visitors to this blog are theirs and do not necessarily reflect mine.
  • Meta