Forecasting and Artificial Intelligence Based Strategies

– Overview of AI techniques

  • General paradigm of machine learning.
  • Stepwise linear regression, classification and regression trees (CART), neural networks, genetic algorithm, Bayesian networks, and support vector machines (SVM).

– Extended exercise on predicting returns of a portfolio of stocks using stepwise linear regression, CART, neural network, and SVM.

  • Constructing the features set: normalizing technical and fundamental variables, and devising candidate entry rules.
  • Constructing the dependent variable.
  • Tuning the parameters of stepwise linear regression and CART for features selection.
  • Interpretation of output.
  • Incorporating selected features and trading rules into a complete backtest.
  • Out-of-sample testing and cross-validation.
  • Tricks to enhance the classifier: Boosting, bagging, and bootstrapping.
  • Comparison with results from neural networks and SVM.

Posted February 06, 2015 in: by ammin

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