Data Mining Techniques in Stock Market Prediction Sen Jiao EECS 435, Data Mining Apr. 14, 2015 Case...
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Transcript of Data Mining Techniques in Stock Market Prediction Sen Jiao EECS 435, Data Mining Apr. 14, 2015 Case...
Data Mining Techniques in Stock Market Prediction
Sen JiaoEECS 435, Data MiningApr. 14, 2015Case Western Reserve University
OutlineTechnical & Fundamental
AnalysisBayesian ProbabilityDynamic Time SeriesArtificial Neural Network Training
Bayesian ProbabilityUpdate the probability estimates for a
hypothesis once additional evidence is learned
Stand for performance accuracy of individual stock over a certain period of time
Provide standard of optimal decision-making for selecting significant technical indicators
Artificial Neural Network (ANN)
Training algorithm iteratively adjusts the connection weights
Generalize relevant output when network is adequately trained
Training automatically stops when generalization stops improving
Artificial Neural Network (ANN)
ANN is expected to yield better prediction results than dynamic time series in most cases
# of hidden neurons: 1070% training data, 15% validation, 15% testing
Preliminary ResultsStock: Apple (AAPL)Data from Apr. 11, 2013 to Apr.
11, 2015505 trading days450 days training, 55 days
predictionMatlab Neural Network Toolbox