EURO Forum

During the last months, INFORMS Data Mining Section holds a Data Mining Contest (http://kaggle.com/informs2010) which required participants to develop a predictive analysis solution that predicts is a stock price will increasing or decreasing in 60 minutes according to the data we have now (60 minutes before).

Eg.: Is Apple stock price will increasing or decreasing in 60 minutes (ex.:at 10:30) according to the data we have now (60 minutes before (ex.: at 9:30)).

Competitors were provided with intraday trading data (609 explanatory variables) showing:
-Stocks price values (at five minute intervals)
-Sectoral data (at five minute intervals)
-Economic data (at five minute intervals)
-Experts' predictions (at one week intervals)
-Indices (at five minute intervals)

Traders, analysts, investors and hedge funds are always looking for techniques to better predict stock price movements. Being able to better predict short-term stock price movements is a boon in high-frequency context, so the methods developed in this contest have a big impact on the finance industry. Knowing whether a stock will increase or decrease allows traders to make better investment decisions, better understand what drives stock prices (supporting better risk management).

This is the overview of the contest:
-28 496 visits on the competition website (http://kaggle.com/informs2010)
-894 participants
-147 submitted predictive analysis solutions
-27 countries were represented (In order of most participants to fewest: United States, Colombia, India, Australia, United Kingdom, France, Thailand, Canada, Germany, Argentina, Japan, Afghanistan, Albania, Austria, Belgium, Chile, China, Croatia, Ecuador, Finland, Greece, Hong Kong, Iran, Poland, Portugal, Slovak Republic and Venezuela)

This is the results of the contest:
Overall ranking:
1) Cole Harris from DejaVu Team
2) Christopher Hefele from Swedish Chef Team
3) Nan Zhou from Nan Zhou Team

“Not using future information ranking”:
1) Anuja Kokrady, Sweta Agrawal, Merin Varghese and Mahesh Kumar Tambi from Ams2009 Team
2) Jong-Seok Lee from Jumper Team
3) Piaomiao from Piaomiao Team

See: http://kaggle.com/informs2010?viewtype=results for full results.

Cole Harris (#1), Christopher Hefele (#2) and Nan Zhou (#3) presented the methods they used at INFORMS Annual Meeting. See theirs presentation at: http://kaggle.com/view-postlist/forum-4-informs-data-mining-2010/topic-190-methodstechniques-used-by-the-top-three-competitors/task_id-2439.

Similar challenge will be laugh next year for the INFORMS Data Mining Contest 2011. I will keep you informed.

Louis Duclos-Gosselin
Chair of INFORMS Data Mining Contest 2010
Chair of the Data Mining Cluster of INFORMS Healthcare 2011
INFORMS Data Mining Section Council Members
Applied Mathematics (Predictive Analysis, Data Mining) Consultant at Sinapse
E-Mail: Louis.Gosselin@hotmail.com
http://www.sinapse.ca/En/Home.aspx
http://dm.section.informs.org/
Phone: 1-866-565-3330
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Sinapse (Quebec), 1170, Boul. Lebourgneuf
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