Developing an Effective Model for Detecting Trade-Based Market Manipulation (Emerald Points) 9781801173971, 9781801173964, 9781801173988, 1801173974

Table of contents :
Cover
DEVELOPING AN EFFECTIVE MODEL FOR DETECTING TRADE-BASED MARKET MANIPULATION
DEVELOPING AN EFFECTIVE MODEL FOR DETECTING-TRADE BASED MARKET MANIPULATION
Copyright
ABSTRACT
CONTENTS
LIST OF TABLES
LIST OF FIGURES
LIST OF ABBREVIATIONS
1. Introduction
1.1 Market Structure
1.1.1 The Market Participants and Intermediaries
1.1.2 The Instruments
1.1.3 The Regulator and Regulations
1.1.4 The Technology
1.1.5 Market Data Dissemination
1.2 An Efficient Stock Market
1.3 The Indian Stock Market
1.3.1 The Bombay Stock Exchange
1.3.2 The National Stock Exchange
1.3.3 Key Developments in the Indian Stock Market
1.4 Stock Price Manipulation
1.4.1 Issues in Identifying Manipulation
1.4.2 Types of Manipulation
1.5 Stock Market Surveillance
1.5.1 Securities Exchange Board of India (SEBI)
1.5.1.1 Integrated Market Surveillance System (IMSS)
1.6 Motivation for Research
1.7 Models Adopted in the Present Work
1.8 The Structure of the Thesis
2. Literature Review
2.1 An Efficient Market
2.2 Market Integrity
2.3 Market Manipulation
2.3.1 Theoretical Foundation to Market Manipulation
2.3.1.1 Action-based Manipulation
2.3.1.2 Information-based Manipulation
2.3.1.3 Trade-based Manipulation
2.3.2 Empirical Studies in Market Manipulation
2.4 Market Surveillance
2.5 Techniques to Detect Manipulation
2.6 Conclusion
3. Research Gap, Scope and Objective
3.1 Identifying the Research Gap
3.1.1 Issue 1
3.1.2 Issue 2
3.1.3 Issue 3
3.2 Scope of Research
3.2.1 Limitations of the Scope
3.3 Research Objectives
4. Methodology
4.1 Trade Data – Indian Equity Market
4.2 Confusion Matrix
4.3 Linear Discriminant Function for Detecting Stock Price Manipulation
4.3.1 The Linear Classification Function
4.4 Testing Assumptions Governing Linear Discriminant Function
4.4.1 Test for Multivariate Normality
4.4.2 Test of Equal Variance-covariance Matrices
4.4.3 Box's M Test
4.4.3.1 χ2 Approximation Test
4.4.3.2 F-approximation Test
4.5 Quadratic Discriminant Analysis for Detecting Stock Price Manipulation
4.6 ANN-GA Based Composite Model for Detecting Stock Price Manipulation
4.6.1 The Artificial Neural Network Based Model
4.6.1.1 Input Layer Nodes
4.6.1.2 Hidden Layer Nodes
4.6.1.3 Output Layer Nodes
4.6.2 Computing the Weights Using Genetic Algorithm
4.7 Support Vector Machines Model for Detecting Stock Price Manipulation
4.8 Comparison of Results
5. Linear Discriminant Analysis for Detecting Stock Price Manipulation
5.1 Development of the Model
5.2 The Linear Classification Function
5.3 Results and Discussion
5.4 Limitation of This Model
6. Quadratic Discriminant Analysis for Detecting Stock Price Manipulation
6.1 Testing Assumptions Governing Linear Discriminant Function
6.1.1 Test to Check if Data Is Normally Distributed
6.1.2 Test to Check for Equal Variance-Covariance
6.1.2.1 χ2 Approximation Test
6.1.2.2 F-approximation Method
6.2 Quadratic Discriminant Function
6.3 Results and Discussion
7. ANN-GA Based Composite Model for Detection of Stock Price Manipulation
7.1 Development of the Model
7.1.1 Determining Weights Using Genetic Algorithm
7.1.1.1 Generating the Chromosome (Initial Population)
7.1.1.2 Weight Extraction
7.1.1.3 Fitness Function
7.1.1.4 Reproduction
7.1.1.5 Convergence
7.1.2 Applying Weights to the Neural Network
7.2 Results and Discussion
8. SVM Model for Detecting Stock Price Manipulation
8.1 Development of the Model
8.1.1 Linearly Separable Classifier
8.1.2 Non-linearly Separable Classifier
8.2 Results and Discussion
9. Summary and Conclusion
9.1 Comparison of Results
9.1.1 Tabulation of Findings
9.2 Summary
9.3 Conclusion
9.4 Scope for Future Work
I - TYPES OF MANIPULATION
REFERENCES
INDEX