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Introduction

In recent years, advancements in artificial intelligence (AI) technology have significantly impacted various industries, including financial services. One area where AI has shown great promise is financial portfolio management, where algorithms and machine learning models can analyze vast amounts of data to make informed investment decisions. This thesis aims to explore the role of AI in financial portfolio management and its implications for investors and financial institutions.

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 Two: Literature Review
2.1 Overview of AI in Financial Services
2.2 AI-driven Portfolio Management Strategies
2.3 Challenges and Opportunities of AI in Portfolio Management
2.4 Previous Studies on AI-driven Portfolio Management
2.5 Regulatory Considerations for AI in Finance
2.6 Ethical Implications of AI in Finance
2.7 Comparison of AI-driven and Human Portfolio Management
2.8 Impact of AI on Financial Markets
2.9 Future Trends in AI-driven Portfolio Management
2.10 Summary of Literature Review

Chapter Three: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Sample Selection
3.5 Variables and Hypotheses
3.6 Research Instrument
3.7 Data Validation Methods
3.8 Ethical Considerations
3.9 Limitations of the Study

Chapter Four: Discussion of Findings
4.1 Overview of Data Analysis
4.2 Descriptive Statistics
4.3 Regression Analysis
4.4 Interpretation of Results
4.5 Comparison with Literature Review
4.6 Implications for Financial Portfolio Management
4.7 Recommendations for Investors and Financial Institutions
4.8 Future Research Directions

Chapter Five: Conclusion and Summary
5.1 Conclusion
5.2 Summary of Findings
5.3 Contributions to Literature
5.4 Practical Implications
5.5 Limitations of the Study
5.6 Recommendations for Future Research
5.7 Final Thoughts

Thesis Overview on AI-driven Financial Portfolio Management

The use of artificial intelligence (AI) in financial portfolio management has gained significant attention in recent years due to its potential to enhance decision-making processes and improve investment outcomes. This thesis aims to explore the role of AI in financial portfolio management and its implications for investors and financial institutions.

The literature review will provide an overview of AI in financial services, AI-driven portfolio management strategies, challenges and opportunities of AI in portfolio management, previous studies on AI-driven portfolio management, regulatory considerations, ethical implications, comparison with human portfolio management, impact on financial markets, and future trends.

The research methodology will outline the research design, data collection methods, analysis techniques, sample selection, variables and hypotheses, research instrument, data validation methods, ethical considerations, and limitations of the study.

The discussion of findings will include descriptive statistics, regression analysis, interpretation of results, comparison with the literature review, implications for financial portfolio management, recommendations for investors and financial institutions, and future research directions.

In conclusion, this thesis will provide insights into how AI can be effectively utilized in financial portfolio management, the potential benefits and challenges associated with its adoption, and recommendations for future research and practice in this area.

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