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Introduction

The financial markets have witnessed significant changes in the way securities are traded over the past few decades. One such development is the emergence of dark pool trading, which has become increasingly popular among institutional investors. Dark pools are private trading platforms where large block orders are executed anonymously, away from the public exchanges. This form of trading has raised concerns about its impact on market liquidity, as it can potentially fragment the market and reduce price transparency.

This thesis aims to investigate the impact of dark pool trading on market liquidity. By analyzing the relationship between dark pool trading and market liquidity, this study seeks to provide valuable insights for regulators, market participants, and academics. The findings of this research can help to enhance our understanding of how dark pool trading affects market dynamics and can inform policy decisions aimed at maintaining a fair and efficient market structure.

Table of Contents

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 Dark Pool Trading
2.2 Market Liquidity
2.3 The Impact of Dark Pool Trading on Market Liquidity
2.4 Empirical Studies on Dark Pool Trading
2.5 Regulation of Dark Pools
2.6 Market Microstructure
2.7 Trading Strategies in Dark Pools
2.8 Information Asymmetry
2.9 Price Discovery
2.10 Market Fragmentation

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Sampling Method
3.4 Data Analysis Techniques
3.5 Hypotheses Development
3.6 Variables Measurement
3.7 Model Specification
3.8 Statistical Analysis

Chapter 4: Discussion of Findings
4.1 Descriptive Statistics
4.2 Regression Results
4.3 Robustness Checks
4.4 Interpretation of Results
4.5 Comparison with Previous Studies
4.6 Implications for Market Participants
4.7 Policy Recommendations
4.8 Future Research Directions

Chapter 5: Conclusion and Summary
5.1 Recap of Findings
5.2 Contributions to Existing Literature
5.3 Limitations of the Study
5.4 Implications for Practice
5.5 Recommendations for Future Research
5.6 Conclusion

Thesis Overview

Dark pool trading has become a controversial topic in the financial markets, as it offers benefits to institutional investors but also raises concerns about market fairness and efficiency. This thesis aims to explore the impact of dark pool trading on market liquidity, focusing on how this form of trading affects price discovery, order execution, and overall market dynamics.

The literature review will provide a comprehensive overview of dark pool trading, market liquidity, and related concepts such as market microstructure and information asymmetry. It will also summarize existing empirical studies on the impact of dark pool trading on market liquidity and highlight gaps in the literature that this research seeks to address.

The research methodology section will outline the study’s design, data collection process, sampling method, and analytical techniques. It will also present the hypotheses developed for testing the relationship between dark pool trading and market liquidity, as well as the variables measured and model specifications used in the analysis.

The discussion of findings will present the results of the empirical analysis, including descriptive statistics, regression results, and robustness checks. It will interpret the findings in light of the existing literature and offer insights for market participants, regulators, and academics. Policy recommendations and future research directions will also be provided.

In conclusion, this thesis will summarize the key findings, contributions to existing literature, limitations of the study, and implications for practice. It will offer recommendations for future research in this area and conclude with a reflection on the importance of understanding the impact of dark pool trading on market liquidity.

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