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Introduction

Artificial intelligence (AI) has revolutionized many industries in recent years, including finance and investment management. In the field of portfolio management, AI technologies are increasingly being used to analyze data, make predictions, and optimize investment strategies. This thesis explores the applications of AI in portfolio management, focusing on how these technologies can improve decision-making processes and outcomes for investors.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Overview of Portfolio Management
2.2 Traditional Portfolio Management Strategies
2.3 Applications of Artificial Intelligence in Finance
2.4 AI Technologies in Portfolio Management
2.5 Benefits of Using AI in Portfolio Management
2.6 Challenges and Limitations of AI in Portfolio Management
2.7 Current Trends and Developments
2.8 Case Studies of AI in Portfolio Management
2.9 Regulatory Considerations
2.10 Future Directions and Opportunities

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Sampling Strategy
3.5 Ethical Considerations
3.6 Research Limitations
3.7 Validation Methods
3.8 Research Settings and Participants

Chapter 4: Discussion of Findings
4.1 Analysis of Data
4.2 Interpretation of Results
4.3 Comparison with Existing Literature
4.4 Implications for Practice
4.5 Recommendations for Future Research

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusions
5.3 Contributions to the Field
5.4 Limitations of the Study
5.5 Recommendations for Practitioners
5.6 Suggestions for Future Research

Thesis Overview on Artificial intelligence in portfolio management:

Artificial intelligence (AI) has gained significant traction in recent years, revolutionizing various industries including finance. In portfolio management, AI technologies have enabled investors to analyze vast amounts of data, make informed decisions, and optimize their investment strategies. This thesis aims to explore the applications of AI in portfolio management, highlighting the benefits, challenges, and future directions of using AI technologies in the field.

The literature review will provide an overview of traditional portfolio management strategies, the evolution of AI technologies in finance, and the current trends and developments in AI-driven portfolio management. Case studies and regulatory considerations will also be examined to provide a comprehensive understanding of the topic.

The research methodology section will outline the design, data collection methods, analysis techniques, and ethical considerations of the study. The discussion of findings will analyze the data collected, interpret the results, and compare them with existing literature to draw meaningful insights and implications for practice.

In conclusion, this thesis will summarize the findings, highlight the contributions to the field, discuss the limitations of the study, and provide recommendations for practitioners and suggestions for future research in the area of AI in portfolio management.

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