Corruption and Fraud in Financial Markets

CAROL ALEXANDER, Ph.D., is Professor of Finance at the University of Sussex, Visiting Professor at Peking University PHBS Business School in Oxford and Co-Editor of the Journal of Banking and Finance. She is the former Chair of the Board of the Professional Risk Manager’s International Association and she consults on model design for major exchanges, banks, and fund managers worldwide. She has edited more than a dozen books in finance and risk management and her sole-authored four-volume textbook on Market Risk Analysis (Wiley, 2008) remains the definitive guide to the subject after more than 12 years in print.DOUGLAS CUMMING J.D., Ph.D., CFA, is the DeSantis Distinguished Professor of Finance and Entrepreneurship at the College of Business, Florida Atlantic University, and Visiting Professor of Finance at Birmingham Business School, University of Birmingham, and Royal Melbourne Institute of Technology. He has published 18 books and over 185 articles in leading journals such as the Academy of Management Journal, Journal of Financial Economics, and Review of Financial Studies, which have been cited over 15,000 times. He is the Managing Editor-in-Chief of the British Journal of Management and Journal of Corporate Finance, and the Founding Editor-in-Chief of the Review of Corporate Finance.

• About the Editors xvList of Contributors xviiForeword xixAcknowledgements xxiChapter 1: Introduction 1Carol Alexander and Douglas CummingPart I What are Manipulation and Fraud and Why Do They Matter? 11Chapter 2: An Overview of Market Manipulation 13Tālis J. Putniņš2.1 Introduction 142.2 Definitions of Market Manipulation 162.2.1 Legal Interpretation and Provisions against Market Manipulation 162.2.2 Economics and Legal Studies Perspective 182.3 A Taxonomy of the Types of Market Manipulation 192.3.1 Categories of Market Manipulation 192.3.2 Market Manipulation Techniques 222.4 Research on Market Manipulation 262.4.1 Theoretical Literature 272.4.2 Empirical Literature 302.4.3 Conclusions from the Research on Market Manipulation 352.5 Summary and Conclusions 39References 40Chapter 3: A Taxonomy of Financial Market Misconduct 45Ai Deng and Priyank Gandhi3.1 Introduction 463.2 Challenges in Research on Financial Market Misconduct 503.3 Defining Financial Market Misconduct 513.3.1 Price Manipulation 533.3.2 Circular Trading 543.3.3 Collusion and Information Sharing 553.3.4 Inside Information 563.3.5 Reference Price Influence 563.3.6 Improper Order Handling 573.3.7 Misleading Customers 583.4 Defining Financial Fraud 593.4.1 Credit Card Fraud 593.4.2 Money Laundering 603.4.3 Financial Statement Fraud 603.4.4 Computer Intrusion Fraud 613.5 Conclusion 61References 61Chapter 4: Financial Misconduct and Market-Based Penalties 65Chelsea Liu and Alfred Yawson4.1 Introduction 664.2 Notable Cases of Financial Reporting Fraud 694.3 Financial Reporting Misconduct and Legal Redress 704.4 Evolution of US Financial Regulations 714.4.1 Private Securities Litigation Reform Act (1995) 724.4.2 Sarbanes–Oxley Act (2002) 724.4.3 Dodd–Frank Act (2010) 734.5 Legal versus Market-Based Penalties for Financial Misconduct 744.5.1 Common Forms of Legal Penalties 744.5.2 Role of Market-Based Penalties 754.6 Firm-Level Penalties for Corporate Financial Misconduct 754.6.1 Direct Economic Costs Captured in Loss of Market Value 834.6.2 Loss of Firm Reputation 834.6.3 Spillover of Reputational Effect 844.6.4 Governance Risk and Insurance Premiums 854.6.5 Reduced Liquidity 854.6.6 Access to Financing 854.6.7 Reduced Innovation 864.6.8 Mergers and Acquisitions 864.7 Individual-Level Penalties for Corporate Financial Misconduct 874.7.1 Executive and Director Turnover 874.7.2 Impaired Career Progression 954.7.3 Loss of Reputation 964.7.4 Executive Compensation 974.7.5 Strengthened Monitoring 974.8 Causes, Risks, and Moderators of Financial Misconduct 984.8.1 Fraud Incentives 984.8.2 Risk Factors 1134.8.3 Public Enforcement: Regulatory and Judicial Stringency 1154.8.4 Public Enforcement: Detection and Surveillance 1164.8.5 Private Enforcement 1174.9 Other Non-Financial Misconduct 1184.10 Concluding Remarks 119References 120Chapter 5: Insider Trading and Market Manipulation 135Jonathan A. Batten, Igor Lončarski, and Peter G. Szilagyi5.1 Introduction 1355.2 Regulatory Framework on Insider Trading and Market Manipulation 1405.3 Recent Examples of Market Manipulation and Insider Trading 1455.4 Conclusions 148References 149Chapter 6: Financial Fraud and Reputational Capital 153Jonathan M. Karpoff6.1 Financial Frauds in the 2000s 1546.2 The Effects of Fraud Revelation on Firm Value and Reputational Capital 1566.2.1 Market Value Losses When Financial Misconduct is Revealed 1566.2.2 Spillover Effects 1576.2.3 Reputational Losses for Financial Misconduct 1586.2.4 Direct Measures of Lost Reputational Capital 1596.2.5 Do Misconduct Firms Always Lose Reputational Capital? 1606.2.6 Rebuilding Reputational Capital 1616.3 The Effects of Fraud Revelation on Shareholders and Managers 1626.3.1 Should Shareholders Pay? Do Managers Pay? 1626.3.2 Do Shareholders Pay Twice? 1626.3.3 Are Firm-Level Penalties Efficient? 1636.3.4 Consequences for Managers and Directors 1636.4 Why Do Managers Do It? Motives and Constraints 1656.4.1 Motives for Financial Misconduct 1656.4.2 Constraints on Financial Misconduct 1676.5 Proxies and Databases Used to Identify Samples of Financial Statement Misconduct 1686.6 Conclusion: Reputation, Enforcement, and Culture 170References 171Part II How and Where Does Misconduct Occur? 179Chapter 7: Manipulative and Collusive Practices in FX Markets 181Alexis Stenfors7.1 Introduction 1817.2 Different Types of FX Orders 1837.3 The Unique FX Market Structure 1847.4 Examples of Manipulative and Collusive Practices in FX Markets 1887.4.1 Front Running 1887.4.2 Triggering Stop-Loss Orders 1907.4.3 ‘Banging the Close’ 1927.4.4 Collusion and Sharing of Confidential Information 1937.4.5 Spoofing 1957.4.6 Market Abuse via Electronic Trading Platforms 1967.5 The Reform Process 197References 199Chapter 8: Fraud and Manipulation within Cryptocurrency Markets 205David Twomey and Andrew Mann8.1 Introduction 2068.2 Why Do fraud and Manipulation Occur in Cryptocurrency Markets? 2128.2.1 Lack of Consistent Regulation 2128.2.2 Relative Anonymity 2138.2.3 Low Barriers to Entry 2148.2.4 Exchange Standards and Sophistication 2148.3 Pump and Dumps 2158.3.1 Case Studies 2178.4 Inflated Trading Volume 2178.4.1 Case Study: January 2017 and PBoC Involvement 2198.5 Exchange DDoS Attacks 2208.5.1 Case Study 2238.6 Hacks and Exploitations 2248.6.1 Exchange Hacks 2248.6.2 Smart Contract Exploits 2298.6.3 Protocol Exploitation 2308.7 Flash Crashes 2308.7.1 GDAX-ETH/USD Flash Crash 2348.8 Order Book-Based Manipulations 2358.8.1 Quote Stuffing 2368.8.2 Order Spoofing 2378.9 Stablecoins and Tether 2398.9.1 Tether Historical Timeline 2408.9.2 Tether Controversy and Criticism 2428.9.3 Tether’s Significance in Cryptocurrency Global Markets 2458.10 Summary and Conclusions 245References 249Chapter 9: The Integrity of Closing Prices 251Ryan J. Davies9.1 Why Closing Prices Matter 2519.2 Painting the Tape and Portfolio Pumping 2529.3 ‘Bang-the-Close’ Manipulation: The Response of Financial Intermediaries 2559.4 Stock Price Pinning on Option Expiration Dates 2599.5 Conclusion: Lessons for the Regulation and Design of Financial Markets 263References 269Chapter 10: A Trader’s Perspective on Market Abuse Regulations 275Sam Baker10.1 Introduction 27510.2 Getting the Trading Edge 27810.3 A Typical Trader’s Market Window 28110.4 Wash Trades 28210.5 High Ticking/Low Ticking – Momentum Ignition 28410.6 Spoofing 28610.7 Layering 29010.8 Smoking 29210.9 Case Study: Paul Rotter a.k.a. ‘The Flipper’ 29510.10 The Innocent and the Guilty 29910.11 What are Exchanges Doing to Prevent Market Abuse? 30110.11.1 CME Group 30110.11.2 ICE 30210.12 What are Trading Companies Doing to Prevent Abuse? 30210.13 Will There Be an End to Market Abuse? 303Part III Who are These Scoundrels? 305Chapter 11: Misconduct in Banking: Governance and the Board of Directors 307Duc Duy Nguyen, Jens Hagendorff, and Arman Eshraghi11.1 Introduction 30711.2 Literature Review 31111.3 Research Design 31211.3.1 Data 31211.3.2 Empirical Design 31311.3.3 Variables 31411.4 Empirical Results 31611.4.1 Main Results 31611.4.2 Results for Different Classes of Enforcement Actions 32011.4.3 Does Better Board Quality Alleviate Shareholder Wealth Losses? 32311.5 Conclusion 323References 325Chapter 12: Misconduct and Fraud by Investment Managers 327Stephen G. Dimmock, Joseph D. Farizo, and William C. Gerken12.1 Introduction 32712.2 Related Research 32912.3 The Investment Advisers Act of 1940 and Mandatory Disclosures 33112.4 Data 33212.4.1 Investment Fraud 33212.4.2 Form ADV Data and Variables 33712.5 Predicting Fraud and Misconduct 34012.5.1 Predicting Fraud by Investment Managers 34012.5.2 Interpreting the Predictive Content of the Models 34512.5.3 K-Fold Cross-Validation Tests 34612.6 Predicting the Initiation vs. the Continuance of Fraud 34712.7 Firm-Wide Fraud vs. Fraud by a Rogue Employee 34912.8 Out-of-Sample Prediction and Model Stability 35112.9 Policy Implications and Conclusions 352References 355Chapter 13: Options Backdating and Shareholders 359Johan Sulaeman and Gennaro Bernile13.1 Introduction 35913.2 Stock Return Patterns around Option Grants 36013.3 The Backdating Practice 36113.4 Media Coverage, Restatement, and Investigation 36213.5 Stock Market Reaction to Public Revelations of Backdating 36313.6 Investor Reaction to (and Anticipation of) Public Revelations 36413.7 Other Types of Misbehaviour Related to Option Grants 36513.7.1 Forward Dating 36513.7.2 Selective Disclosure 36613.7.3 Option Exercise Backdating 36613.7.4 Independent Director Backdating 36613.8 Connections with Questionable Practices by Corporate Executives and Other Agents 36613.9 Conclusion 367References 368Chapter 14: The Strategic Behaviour of Underwriters in Valuing IPOs 371Stefano Paleari, Andrea Signori, and Silvio Vismara14.1 Valuing IPOs 37114.2 The Underwriter’s Incentives in the Valuation of IPOs 37314.3 Literature Review 37414.4 Sample, Data, and Methodology 37614.4.1 Sample and Data 37614.4.2 Alternative Selection Criteria of Comparable Firms 38014.4.3 Valuation Bias and IPO Premium 38014.5 Results 38114.5.1 Algorithmic Selections 38114.5.2 Affiliated and Unaffiliated Analysts 38614.5.3 Underwriters’ Selection of Comparable Firms Pre- vs. Post-IPO 39014.5.4 Pre- vs. Post-IPO Selections and Industry Effects 39414.6 Conclusions 396References 397Chapter 15: Governance of Financial Services Outsourcing: Managing Misconduct and Third-Party Risks 399Joseph A. McCahery and F. Alexander de Roode15.1 Introduction 39915.2 The Four Components in Outsourcing 40215.2.1 Efficient Outsourcing 40215.2.2 The Four-Factor Governance Model 40415.2.3 Misconduct in Outsourcing and the Ability of Financial Institutions to Monitor 40715.3 The Interaction between Contracting and Monitoring 40815.3.1 Characterization of Financial Institutions 40915.3.2 Risks in Outsourcing Services 41215.4 Governance Mechanisms to Detect Misconduct in Financial Outsourcing 41315.4.1 Screening and Detection 41415.5 Conclusion 416References 417Part IV Detection and Surveillance of Financial Misconduct 423Chapter 16: Identifying Security Market Manipulation 425Mike Aitken, Ann Leduc, and Shan Ji16.1 Introduction 42516.2 Background Legislation 42716.2.1 Australia 42716.2.2 UK 42816.2.3 Hong Kong 42816.2.4 Canada 42916.2.5 Singapore 43016.2.6 Malaysia 43016.2.7 New Zealand 43116.3 Attributes of Manipulation 43116.3.1 How Traders Minimize the Resources Needed for Manipulative Trading 43216.3.2 Difficulties in Determining Whether Trading Behaviour is Manipulative 43316.3.3 Surveillance Systems 43416.4 Detection Algorithms 43616.5 Conclusion 439Chapter 17: The Analytics of Financial Market Misconduct 441Ai Deng and Priyank Gandhi17.1 Introduction 44217.2 Financial Economic Analysis 44617.2.1 Benchmarking to Historical or Past Data 44717.2.2 Benchmarking to Alternate Proxies 45117.2.3 Benchmarking to a Model 45417.3 Quantitative Techniques 45617.3.1 The Principles of Fraud Detection 45717.3.2 Popular Supervised Learning Techniques for Fraud Detection 45817.3.3 Popular Unsupervised Learning Techniques for Fraud Detection 46017.3.4 Dynamic Misconduct Detection 46217.4 Conclusion 464References 466Chapter 18: Benford’s Law and Its Application to Detecting Financial Fraud and Manipulation 473Christina Bannier, Corinna Ewelt-Knauer, Johannes Lips, and Peter Winker18.1 Introduction 47418.2 Benford’s Law and Generalizations 47618.2.1 The Basic Principle of Benford’s Law 47618.2.2 Illustration of Benford’s Law 47718.2.3 Testing for Conformity with Benford’s Law 47818.2.4 Considering Further Digits with Benford’s Law 48018.2.5 When Do Data Conform to Benford’s Law? 48218.2.6 Limitations of Using Benford’s Law for Identification of Manipulations 48318.2.7 Generalizations of Benford’s Law for Identification of Manipulations 48418.3 Usage of Benford’s Law for Detecting Fraud and Deviant Behaviour 48518.3.1 Forensic Accounting in the Context of Auditing, Internal Control Systems, and Taxation 48618.3.2 Finance 48718.3.3 Surveys and Research 49018.4 A Case Study: Benford’s Law and the LIBOR 49118.5 Policy Implications 49818.6 Summary, Limitations, and Outlook 498References 49918.A Appendix 504Part V Regulation and Enforcement 505Chapter 19: The Enforcement of Financial Market Crimes in Canada and the United Kingdom 507Anita Indira Anand19.1 Introduction 50719.2 Existing Scholarship 50819.3 Comparative Analysis 51219.3.1 Canada 51219.3.2 The United Kingdom 51319.4 Reform 51519.4.1 Resource Allocation 51519.4.2 Principles-Based Regulation 51619.4.3 Targeted Regulatory Reforms 51819.5 Conclusion 520References 520Chapter 20: A Pyramid or a Labyrinth? Enforcement of Registrant Misconduct Requirements in Canada 527Mary Condon20.1 Introduction 52720.2 Definitional and Institutional Quagmires 52920.3 The Compliance/Enforcement Continuum 53120.4 Enforcement Options Available to Sanction Registrant Misconduct 53320.5 Empirical Information Available about Registrant Misconduct in Canada 53520.5.1 Criminal Enforcement 53520.5.2 CSA Non-Criminal Enforcement 53620.5.3 Director’s Decision Data in Ontario 53720.5.4 SRO Enforcement 53820.6 Analysis 538Chapter 21: Judicial Local Protectionism and Home Court Bias in Corporate Litigation 541Michael Firth, Oliver M. Rui, and Wenfeng Wu21.1 Introduction 54221.2 Institutional Background 54421.2.1 Decentralization and Local Protectionism 54421.2.2 Judicial Independence 54521.2.3 The Heterogeneity of the Legal Environment across Regions 54821.3 Empirical Evidence 54821.3.1 Sample 54921.3.2 Basic Statistics 55021.3.3 The Wealth Effect for Defendants and Plaintiffs around the Filing Announcements at Different Courts 55621.3.4 The Impact of Court Location on the Wealth Effect 56021.3.5 Regression Analysis of the Wealth Effects from a Filing Announcement 56021.3.6 Heckman Two-Step Analysis of Sample Selection Bias 56721.3.7 The Impact of Court Location on the Likelihood to Appeal 57321.3.8 Sensitivity Tests 57621.4 Conclusion 579References 580Index 583

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