Target-date funds glide path optimization – Complete Phd and Masters Thesis

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Introduction

Target-date funds (TDFs) have become increasingly popular investment vehicles for retirement savings due to their simplicity and convenience. These funds are designed to automatically adjust asset allocation based on an investor’s target retirement date, with the intention of reducing risk as the investor approaches retirement age. The glide path is a key component of TDFs, representing the asset allocation trajectory over time. Optimizing the glide path is crucial for maximizing returns while managing risk effectively.

This thesis will focus on the optimization of target-date funds glide paths, exploring strategies to enhance the performance and efficiency of these funds. By examining the factors that influence glide path design and implementation, this study aims to provide valuable insights for investment professionals and individual investors seeking to improve their retirement savings strategy.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objectives of Study
1.5 Limitations 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 Target-Date Funds
2.2 Evolution of Glide Paths
2.3 Factors Influencing Glide Path Design
2.4 Performance Metrics for Glide Path Optimization
2.5 Comparison of Different Glide Path Strategies
2.6 Criticisms of Traditional Glide Paths
2.7 Innovations in Glide Path Design
2.8 Empirical Studies on Glide Path Optimization
2.9 Behavioral Finance and Glide Path Decision Making
2.10 Regulatory Environment for Target-Date Funds

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Sample Selection
3.4 Data Analysis
3.5 Research Hypotheses
3.6 Variables and Measures
3.7 Model Specification
3.8 Limitations of Research Methodology

Chapter 4: Discussion of Findings
4.1 Descriptive Analysis
4.2 Hypothesis Testing Results
4.3 Implications for Target-Date Fund Industry
4.4 Practical Recommendations for Investors
4.5 Future Research Directions
4.6 Comparison with Existing Literature
4.7 Key Findings in Perspective
4.8 Challenges and Opportunities

Chapter 5: Conclusion and Summary
5.1 Summary of Key Findings
5.2 Contributions to Literature
5.3 Practical Implications
5.4 Limitations of Study
5.5 Recommendations for Future Research
5.6 Concluding Remarks

Thesis Overview on Target-Date Funds Glide Path Optimization

Target-date funds (TDFs) have gained popularity as an investment option for retirement savings, offering a convenient way for investors to achieve diversification and asset allocation based on their target retirement date. The glide path of a TDF plays a crucial role in determining the asset allocation trajectory over time, impacting the risk and return profile of the fund.

This thesis aims to explore the optimization of target-date funds glide paths, focusing on strategies to enhance performance and efficiency. By conducting a comprehensive literature review and empirical analysis, this study will provide valuable insights for investment professionals and individual investors seeking to improve their retirement savings strategy.

Through a structured approach, this thesis will investigate the factors influencing glide path design, analyze performance metrics for optimization, compare different glide path strategies, and assess the regulatory environment for target-date funds. The research methodology will involve data collection, sample selection, hypothesis testing, and model specification to examine the empirical evidence on glide path optimization.

The findings from this study will contribute to the existing literature on target-date funds and provide practical recommendations for investors and industry professionals. By addressing the limitations of previous research and suggesting future research directions, this thesis aims to advance knowledge in the field of glide path optimization and enhance the retirement savings outcomes for investors.

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