Journal of Sensor Networks and Data Communications(JSNDC)

WorldQuant University, New Orleans, Louisiana, USA

Publications

• Research Article   
  A Test of Market Efficiency: A Supervised Machine Learning Approach to Binary Options Trading
  Author(s): Joe Wayne Byers*, Ioannis Evgeniou and Anand Ravindra Manjrekar
  
  There has been significant progress in automating binary options trading and in developing more sophisticated trading strategies. Most of these tools rely on historical data of shorter time frames; often without verifying the presence of any predictable patterns. These trading systems lack robust predictive analytics, which results in exposing the retail traders to a significant risk. This study attempts to address this loophole through a comprehensive analysis using large datasets to detect the presence of any predictable patterns. The study involves the usage of a sophisticated machine learning technique such as XGBoost. The workflow commences from generation of datasets to feature extraction, then it is followed by patterns recognition for determining trading positions. The features and outcomes are stored and used for the hyperparameter tuning process which is followed by the mode.. Read More»
  

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