Day Trading the Emerging Markets Using Multi-Time Frame Technical Indicators and Artificial Neural Networks

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 486)

Abstract

This chapter addresses the topic of automated day trading systems based on artificial neural networks and multi-timeframe technical indicators, a very common market analysis technique. After we introduce the context of this study and give a short overview of day trading, we set out our approach and methodological framework. Then, we present the results obtained through these procedures on several of the most liquid stocks in the Romanian stock market. The final section of the chapter concludes the study and brings some insight about possible future work in the area.

Keywords

Day trading systems Neural networks Multi-time frame technical analysis Market forecast Automatic trading 

Notes

Acknowledgments

This work is a part of CNCSIS TE_316 Grant « Intelligent Methods for Decision Fundamentation on Stock Market Transactions Based on Public Information », manager V.P. Bresfelean, Assistant Professor PhD.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Babes-Bolyai UniversityCluj-NapocaRomania

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