Solving Modern Crime in Financial Markets: Analytics and Case Studies

  • 9h 18m
  • Marius-Christian Frunza
  • Elsevier Science and Technology Books, Inc.
  • 2016

This comprehensive source of information about financial fraud delivers a mature approach to fraud detection and prevention. It brings together all important aspect of analytics used in investigating modern crime in financial markets and uses R for its statistical examples. It focuses on crime in financial markets as opposed to the financial industry, and it highlights technical aspects of crime detection and prevention as opposed to their qualitative aspects. For those with strong analytic skills, this book unleashes the usefulness of powerful predictive and prescriptive analytics in predicting and preventing modern crime in financial markets.

  • Interviews and case studies provide context and depth to examples
  • Case studies use R, the powerful statistical freeware tool
  • Useful in classroom and professional contexts

About the Author

Marius-Cristian Frunza is a Director with Schwarzthal Kapital, a financial advisory and research company. He is specialized in expert witness for litigations, disputes and financial crime. He is also an associate professor of finance with Dauphine University. Previously, he worked as a broker in the energy markets for a commodity broker. He has also a consulting experience working with investment banks and asset managers specialising in risk management, derivative pricing and hedging. He holds a PhD in mathematical finance form the reputed Paris Sorbonne University.

In this Book

  • Prologue
  • David Lee Kuo Chuen—Interview
  • Laura Hutton—Interview
  • Innovation and Crime
  • High-Frequency Trading
  • Commodities Markets
  • Social Networks and Financial Crime
  • Cryptocurrencies—A New Monetary Vehicle
  • The Link between the Betting Industry and Financial Crime
  • Truth—A Game of Probabilities
  • Statistical Distributions
  • Forecasting Densities
  • Genetic Algorithms
  • Statistical Hypothesis Tests
  • Non-Parametric Techniques
  • Fuzzy Methods
  • Clustering Techniques
  • Support Vector Machines
  • Determining the Accuracy of a Fraud-Detection Model
  • Benford's Law
  • Structural Changes in Time Series
  • Exploring Unstructured Data
  • Understanding the Balance Sheets of Financial Firms
  • Fraud on the Market Theory
  • Efficient Market Hypothesis Testing
  • Market Prices and Trading Activity
  • Order Book Analysis
  • Event Study
  • LIBOR Manipulation
  • EURIBOR Manipulation
  • The Madoff Case
  • Enron-WorldCom
  • Rating Agencies and Crisis
  • The FX Fixing Fix
  • The Case of Greenhouse Gas Emission Allowances Market
  • Pros and Cons of Stronger Financial Regulation?
  • Efficient Frameworks for Financial Crime Surveillance
  • Joint Structures for Tackling Financial Offenses—Criminal Investigators and Market Regulators
  • Epilogue
  • Bibliography
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