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Introduction

Quantum computing is a cutting-edge technology that has the potential to revolutionize various industries, including finance and investing. In recent years, researchers have been exploring the application of quantum computing in portfolio optimization, which is a crucial aspect of financial management. This thesis aims to investigate the potential of quantum computing in enhancing portfolio optimization strategies.

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
– Overview of portfolio optimization
– Traditional portfolio optimization techniques
– Introduction to quantum computing
– Quantum algorithms for portfolio optimization
– Previous studies on quantum computing for portfolio optimization
– Challenges and limitations in applying quantum computing to portfolio optimization
– Comparison of quantum computing and classical computing for portfolio optimization
– Potential benefits of quantum computing in portfolio optimization
– Future directions for research in quantum computing for portfolio optimization
– Summary of key findings in the literature review

Chapter 3: Research Methodology
– Research approach and design
– Data collection methods
– Research participants
– Data analysis techniques
– Ethical considerations
– Validity and reliability of the study
– Tools and software used
– Limitations of the research methodology

Chapter 4: Discussion of Findings
– Analysis of data collected
– Comparison of traditional and quantum-based portfolio optimization strategies
– Impact of quantum computing on portfolio performance
– Practical implications for investors and fund managers
– Recommendations for future research in this area

Chapter 5: Conclusion and Summary
– Summary of key findings
– Contribution to the existing body of knowledge
– Implications for practice
– Limitations of the study
– Suggestions for future research
– Concluding remarks

Thesis Overview on Quantum Computing for Portfolio Optimization

Quantum computing is a promising technology that has the potential to revolutionize portfolio optimization in the finance industry. This thesis aims to explore the application of quantum computing in enhancing portfolio optimization strategies. The introduction provides background information on quantum computing and portfolio optimization, states the problem statement, objectives, limitations, scope, significance of the study, and defines key terms.

The literature review presents an overview of portfolio optimization, traditional techniques, and quantum algorithms for optimization. It also discusses previous studies, challenges, limitations, benefits, and future directions in quantum computing for portfolio optimization. The research methodology outlines the approach, data collection methods, participants, analysis techniques, ethical considerations, and tools used.

The discussion of findings analyzes collected data, compares traditional and quantum-based strategies, evaluates the impact on portfolio performance, and provides recommendations for future research. The conclusion summarizes key findings, contributions, implications for practice, limitations, suggestions for future research, and concluding remarks.

Overall, this thesis aims to advance the understanding of the potential of quantum computing in portfolio optimization and provide insights for investors and fund managers in leveraging this technology for improved financial outcomes.

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