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Introduction

Artificial Intelligence (AI) technology has rapidly evolved in recent years and has been increasingly utilized in various industries to improve efficiency and decision making processes. In the context of financial portfolio management, AI has the potential to revolutionize the way investment decisions are made by utilizing advanced algorithms and data analysis techniques to identify and capitalize on market trends and opportunities. This thesis aims to explore the application of AI in financial portfolio management and its impact on investment strategies.

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

– History and evolution of AI in financial portfolio management
– Overview of different AI techniques used in portfolio management
– Case studies of successful implementation of AI in portfolio management
– Challenges and limitations of using AI in portfolio management
– Comparison of AI-based portfolio management with traditional methods
– Role of AI in risk management and asset allocation
– Impact of AI on investment performance and returns
– Ethical considerations in using AI for portfolio management
– Regulatory issues surrounding the use of AI in finance
– Future trends and developments in AI for portfolio management

Chapter Three: Research Methodology

– Research design and approach
– Data collection methods and sources
– Sampling techniques
– Data analysis techniques
– Ethical considerations
– Limitations of the research methodology
– Validity and reliability of the research findings
– Research implications and recommendations

Chapter Four: Discussion of Findings

– Analysis of the research data
– Interpretation of the findings
– Comparison with existing literature
– Implications for financial practitioners
– Recommendations for future research

Chapter Five: Conclusion and Summary

– Summary of key findings
– Conclusions drawn from the research
– Contributions to the field of AI in financial portfolio management
– Practical implications for financial practitioners
– Recommendations for future research

Thesis Overview:

Artificial Intelligence (AI) has gained significant traction in the financial industry, particularly in the domain of portfolio management. This thesis aims to explore the application of AI in financial portfolio management and its impact on investment strategies. The study will provide a comprehensive review of the literature on the history and evolution of AI in portfolio management, different AI techniques used in portfolio management, successful case studies, challenges and limitations, comparisons with traditional methods, role in risk management, ethical considerations, regulatory issues, and future trends.

The research methodology will involve a thorough examination of existing literature, case studies, and empirical data to analyze the impact of AI on investment performance and returns. Data collection methods, sampling techniques, data analysis techniques, ethical considerations, and research limitations will be discussed in detail. The findings of the research will be critically analyzed, compared with existing literature, and implications for financial practitioners will be highlighted.

In conclusion, the thesis will provide a summary of key findings, conclusions drawn from the research, contributions to the field of AI in financial portfolio management, practical implications for financial practitioners, and recommendations for future research. By examining the role of AI in financial portfolio management, this thesis aims to contribute to the growing body of knowledge on the use of AI in the finance industry.

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