Developing an Effective Model for Detecting Trade-Based Market Manipulation
Stock market manipulation is detrimental to traders and corporations, causes unnecessary price fluctuations, and only benefits financial criminals. The research presented here determines an appropriate model to help identify stocks witnessing activities that are indicative of potential manipulation through three separate but related studies.

In Developing an Effective Model for Detecting Trade-Based Market Manipulation, classifiers based on three different techniques namely discriminant analysis, a composite classifier based on Artificial Neural Network and Genetic Algorithm and support Vector Machines is proposed. The proposed models help investigators, with varying degree of accuracy, to arrive at a shortlist of securities which could be subject to further detailed investigation to detect the type and nature of the manipulation, if any.

Following a fluid outline, Developing an Effective Model for Detecting Trade-Based Market Manipulation, introduces the topic, explores the aims and scopes of the research, before delving into the data and modelling to explore their application to the stock market to detect price manipulation.

1139032945
Developing an Effective Model for Detecting Trade-Based Market Manipulation
Stock market manipulation is detrimental to traders and corporations, causes unnecessary price fluctuations, and only benefits financial criminals. The research presented here determines an appropriate model to help identify stocks witnessing activities that are indicative of potential manipulation through three separate but related studies.

In Developing an Effective Model for Detecting Trade-Based Market Manipulation, classifiers based on three different techniques namely discriminant analysis, a composite classifier based on Artificial Neural Network and Genetic Algorithm and support Vector Machines is proposed. The proposed models help investigators, with varying degree of accuracy, to arrive at a shortlist of securities which could be subject to further detailed investigation to detect the type and nature of the manipulation, if any.

Following a fluid outline, Developing an Effective Model for Detecting Trade-Based Market Manipulation, introduces the topic, explores the aims and scopes of the research, before delving into the data and modelling to explore their application to the stock market to detect price manipulation.

64.99 In Stock
Developing an Effective Model for Detecting Trade-Based Market Manipulation

Developing an Effective Model for Detecting Trade-Based Market Manipulation

Developing an Effective Model for Detecting Trade-Based Market Manipulation

Developing an Effective Model for Detecting Trade-Based Market Manipulation

Hardcover

$64.99 
  • SHIP THIS ITEM
    In stock. Ships in 6-10 days.
  • PICK UP IN STORE

    Your local store may have stock of this item.

Related collections and offers


Overview

Stock market manipulation is detrimental to traders and corporations, causes unnecessary price fluctuations, and only benefits financial criminals. The research presented here determines an appropriate model to help identify stocks witnessing activities that are indicative of potential manipulation through three separate but related studies.

In Developing an Effective Model for Detecting Trade-Based Market Manipulation, classifiers based on three different techniques namely discriminant analysis, a composite classifier based on Artificial Neural Network and Genetic Algorithm and support Vector Machines is proposed. The proposed models help investigators, with varying degree of accuracy, to arrive at a shortlist of securities which could be subject to further detailed investigation to detect the type and nature of the manipulation, if any.

Following a fluid outline, Developing an Effective Model for Detecting Trade-Based Market Manipulation, introduces the topic, explores the aims and scopes of the research, before delving into the data and modelling to explore their application to the stock market to detect price manipulation.


Product Details

ISBN-13: 9781801173971
Publisher: Emerald Publishing Limited
Publication date: 05/05/2021
Series: Emerald Points
Pages: 120
Product dimensions: 5.98(w) x 9.02(h) x 0.39(d)

About the Author

Dr. Jose Joy Thoppan is an Associate Professor at Saintgits Institute of Management, India, and has a PhD in capital markets from the National Institute of Technology, Tiruchirappalli. He holds an MBA in Finance and has served Tata Consultancy Services for 6 years where he was a business area specialist for the Trading, Clearing and Surveillance platform – TCS BaNCS Market Infrastructure.

Dr. M. Punniyamoorthy is Professor [HAG Scale] in Operations and Analytics at the National Institute of Technology, Tiruchirappalli, India. His research interests include Supply Chain performance, Supplier Selection, Technology Selection, Data Analytics, Data Science, Performance Measurement and Balanced Scorecard.

Dr. K. Ganesh is Senior Knowledge Expert and Global Lead of “manufacturing and supply chain management center of competence” (MSC CoC) at McKinsey & Company, Chennai, India.

Dr. Sanjay Mohapatra has more than 37 years of combined industry and academic experience. He was VP in three organizations (Polaris Lab, iSOFT Plc, JB Soft Inc.) and was heading Asia Pacific, Europe and USA. He has authored twenty eight books and seventy eight papers in Scopus indexed journals.

Table of Contents

Chapter 1. Introduction
Chapter 2. Literature Review
Chapter 3. Research Gap, Scope And Objective
Chapter 4. Methodology
Chapter 5. Linear Discriminant Analysis For Detecting Stock Price Manipulation
Chapter 6. Quadratic Discriminant Analysis For Detecting Stock Price Manipulation
Chapter 7. Ann-Ga Based Composite Model For Detection Of Stock Price Manipulation
Chapter 8. Svm Model For Detecting Stock Price Manipulation
Chapter 9. Summary And Conclusion
From the B&N Reads Blog

Customer Reviews