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Automated stock picking using random forests
Christian Breitung
Associate Professorship of Finance
Research output
:
Contribution to journal
›
Article
›
peer-review
3
Scopus citations
Overview
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Dive into the research topics of 'Automated stock picking using random forests'. Together they form a unique fingerprint.
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Keyphrases
Random Forest
100%
Outperformance
100%
Stock picking
100%
Feature-based
50%
Random Forest Regression
50%
Human Factors
50%
Technical Characteristics
50%
Firm Size
50%
Deciles
50%
Liquid Stocks
50%
Portfolio Optimization
50%
Crisis Period
50%
Sharpe Ratio
50%
Eternal Return
50%
Limits-to-arbitrage
50%
Stock Ranking
50%
Economics, Econometrics and Finance
Portfolio Selection
100%
Firm Size
100%
Arbitrage
100%
Social Sciences
Firm Size
100%
Portfolio Selection
100%
Computer Science
Random Decision Forest
100%