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Introduction:

Option pricing models play a crucial role in financial markets by determining the fair price of financial instruments known as options. These models are used by investors and financial institutions to make informed decisions regarding the buying and selling of options. Market volatility, on the other hand, is a measure of the degree of variation in the trading price of a financial instrument over time. Understanding market volatility is essential for risk management and portfolio optimization.

This thesis aims to explore the relationship between option pricing models and market volatility. Specifically, the study will analyze how different option pricing models perform under varying market volatility conditions. By conducting empirical research and statistical analysis, this study seeks to provide insights into the effectiveness and accuracy of option pricing models in predicting market volatility.

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 Historical development of option pricing models
2.2 Theoretical framework of option pricing models
2.3 Empirical studies on option pricing models
2.4 Market volatility measurement techniques
2.5 Relationship between option pricing models and market volatility
2.6 Critique of existing literature
2.7 Recent trends in option pricing and market volatility
2.8 Gaps in the literature
2.9 Theoretical framework for the study
2.10 Conceptual framework for the study

Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection methods
3.3 Sample selection
3.4 Variables and measurements
3.5 Data analysis techniques
3.6 Hypotheses formulation
3.7 Model specification
3.8 Research limitations

Chapter 4: Discussion of Findings
4.1 Descriptive statistics
4.2 Data analysis results
4.3 Hypotheses testing
4.4 Comparison of option pricing models
4.5 Implications for market participants
4.6 Practical implications for financial institutions
4.7 Recommendations for future research
4.8 Conclusion and summary

Chapter 5: Conclusion and Summary
5.1 Summary of findings
5.2 Contributions to literature
5.3 Practical implications
5.4 Limitations of the study
5.5 Future research directions
5.6 Conclusion

Thesis Overview on Option Pricing Models and Market Volatility:

The study of option pricing models and market volatility is essential for understanding the dynamics of financial markets and making informed investment decisions. This thesis aims to explore the relationship between option pricing models and market volatility by analyzing the performance of different models under varying market conditions.

The literature review will provide a comprehensive overview of existing research on option pricing models and market volatility, highlighting the historical development of these models, theoretical frameworks, empirical studies, and measurement techniques. The study will identify gaps in the literature and propose a theoretical and conceptual framework for the research.

The research methodology will outline the design of the study, data collection methods, sample selection, variables and measurements, data analysis techniques, hypotheses formulation, model specification, and limitations of the study. By conducting empirical research and statistical analysis, the study will test hypotheses and compare the performance of option pricing models in predicting market volatility.

The discussion of findings will present descriptive statistics, data analysis results, hypotheses testing, comparisons of option pricing models, implications for market participants, practical implications for financial institutions, recommendations for future research, and a conclusion and summary of the study.

In conclusion, this thesis will contribute to the existing body of knowledge on option pricing models and market volatility by providing insights into the effectiveness and accuracy of these models in predicting market volatility. The findings of this study will have practical implications for investors and financial institutions, as well as guide future research in this area.

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