Analyzing the Impact of Machine Learning Algorithms on Stock Market Prediction Accuracy

1. Introduction 1.1 Background of Stock Market Prediction 1.2 Importance of Prediction Accuracy 1.3 Overview of Machine Learning Algorithms 1.4 Research Objectives and Questions 1.5 Structure of the Thesis 2. Literature Review 2.1 Stock Market Prediction Techniques 2.2 Machine Learning in Financial Markets 2.3 Evaluation Metrics for Prediction Accuracy 2.4 Previous Studies and Findings 3. Methodology 3.1 Research Design and Approach 3.2 Data Collection and Sources 3.3 Selection of Machine Learning Algorithms 3.4 Model Training and Validation Procedures 4. Machine Learning Algorithms Overview 4.1 Supervised Learning Algorithms 4.2 Unsupervised Learning Algorithms 4.3 Ensemble Methods in Prediction 4.4 Algorithm Selection Criteria 5. Experimental Setup 5.1 Data Preprocessing Techniques 5.2 Feature Selection and Engineering 5.3 Implementation Tools and Environment 5.4 Baseline Model for Comparison 6. Results and Analysis 6.1 Model Performance Metrics 6.2 Comparison of Algorithm Accuracy 6.3 Impact of Algorithms on Prediction 6.4 Discussion of Results 7. Discussion 7.1 Interpretations of Key Findings 7.2 Implications for Financial Analysts 7.3 Limitations and Challenges 7.4 Recommendations for Future Research 8. Conclusion 8.1 Summary of Research Findings 8.2 Contributions to the Field 8.3 Final Thoughts on Machine Learning 8.4 Potential Future Developments