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OPERATIONAL LOSSES: LESSONS from SEVEN of the LARGEST ROGUE TRADING EVENTS in HISTORY by Patricio Leonel Morat a Thesis Submitte

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OPERATIONAL LOSSES: LESSONS from SEVEN of the LARGEST ROGUE TRADING EVENTS in HISTORY by Patricio Leonel Morat a Thesis Submitte OPERATIONAL LOSSES: LESSONS FROM SEVEN OF THE LARGEST ROGUE TRADING EVENTS IN HISTORY by Patricio Leonel Morat A thesis submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Master of Science in Economics Charlotte 2017 Approved by: ______________________________ Dr. Rob Roy McGregor ______________________________ Dr. Craig A. Depken, II ______________________________ Mr. Azhar Iqbal ii ©2017 Patricio Leonel Morat ALL RIGHTS RESERVED iii ABSTRACT PATRICIO LEONEL MORAT. Operational losses: Lessons from seven of the largest rogue trading events in history. (Under the direction of DR. ROB ROY MCGREGOR) Operational risk is the risk of losses arising from the failure of people, processes, and systems, and from external events. A general opinion is that, unlike market risk and credit risk, operational risk is idiosyncratic in the sense that when it manifests in one firm, it does not spread to other firms. This view implies the absence of contagion and that operational risk is firm- specific, not systemic, but there is some new evidence from the Federal Reserve Bank (FRB) that suggests frequencies track both firm and macro variables. Until the emergence of the “Basel 2” reforms to banking supervision in the mid to late 90s, operational risk was largely an afterthought because these uncertainties were difficult to quantify, insure against, and manage in traditional ways. The last 15 years have witnessed the rapid emergence of operational risk from this low status to its institutionalization as a key component of enterprise risk management and global banking regulation. Some authors find it tempting to regard Nick Leeson, the “rogue” trader attributed with the destruction of the legendary Barings bank in 1995, as the true inventor of “operational risk.” The magnitude of loss and the impact of operational risk and losses to date are difficult to ignore. We have seen an increase in the number of large operational losses during times of economic stress. The times of market and economic stress magnify the severity of the large operational losses and lead to the eventual unraveling of the losses in the public eye. iv The research reveals a significant number of similarities between the cases of rogue trading. These results support the hypothesis that failures both internal and external to the companies analyzed facilitated the emergence of rogue trading activities, specially driven by fragmented control environments and incentive schemes undermining financial institutions’ risk culture. v ACKNOWLEDGMENTS I would like to convey my sincere thanks to the following people, whose contributions and support were invaluable. Dr. Rob Roy McGregor – To my thesis coordinator, thank you for your consistent guidance and endless patience. It has been a great privilege to be guided by someone of your academic achievement and stature. Mrs. Ana Morat – My sincere thanks for proofreading this thesis. To my child, Jacques Philippe, and my father, mother and grandmother for their inspiration and support. To my current and previous employers for the opportunity to learn and participate in the development of operational risk frameworks. vi TABLE OF CONTENTS LIST OF TABLES 10x LIST OF FIGURES 11xi CHAPTER 1: INTRODUCTION 1 CHAPTER 2: CASES 11 2.1. Société Générale Group 11 2.1.1. Background 11 2.1.2. Contributory/Control Factors 22 2.1.3. Some additional details from public sources 24 2.2. JPMorgan Chase 27 2.2.1. Background 27 2.2.2. Conflicting Objectives 29 2.2.3. A Strategy is Proposed 33 2.2.4. The Strategy is Implemented (“London Whale” Trades) 33 2.2.5. Consequences 37 2.2.6. Contributory/Control Factors – Book Valuation 40 2.2.7. Contributory/Control Factors – Limits, Metrics and Models 43 2.2.8. Contributory/Control Factors – CIO Compensation 47 vii 2.2.9. Risk Framework 48 2.2.10. Dichotomy – Simply Hedging or Proprietary Trading? 49 2.3. Sumitomo Corporation 51 2.3.1. Background 51 2.3.2. Hamanaka as a trader 52 2.3.3. Investigations launched 54 2.3.4. The BIS backing 55 2.3.5. The trial 56 2.3.6. Lessons from the Sumitomo Debacle 63 2.4. UBS 65 2.4.1. Background 65 2.4.2. Bad news 66 2.4.3. Déjà Vu 68 2.4.4. Under pressure 70 2.4.5. Regulatory findings 71 2.4.6. Gaps and behaviors specific to the First Line of Defense 72 2.4.7. Gaps and behaviors specific to the Second Line of Defense 76 2.4.8. Gaps and behaviors specific to the Third Line of Defense 78 2.4.9. Lessons learned from the UBS incident 78 viii 2.5. Showa Shell Sekiyu K.K. 81 2.5.1. Background 81 2.5.2. The debacle 81 2.5.3. General currency hedging practices at petroleum companies 83 2.5.4. The mechanics of hedging dollar exchange rate risk and oil price risk 84 2.5.5. Were they hedging or speculating? 85 2.5.6. Concealing currency losses 86 2.5.7. The story unfolds 87 2.5.8. Lessons learned 88 2.6. Daiwa 91 2.6.1. Background 91 2.6.2. The role of management 93 2.6.3. Role regulators played in the fiasco 97 2.6.4. Company Culture and drivers to Iguchi 98 2.6.5. Lessons from the Daiwa debacle 101 2.7. Barings plc 103 2.7.1. Background 103 2.7.2. Baring Securities (Singapore) Ltd. (BSS) 105 2.7.3. Unauthorized Trading 109 ix 2.7.4. Management Involvement 111 2.7.5. Funding Margin Calls 112 2.7.6. Options Sales 114 2.7.7. The Collapse of Barings 117 2.7.8. Aftershocks 121 2.7.9. Lessons from the Barings Debacle 122 CHAPTER 3: CONCLUSION 126 3.1. Lessons Learned 126 3.2. Solutions to rogue trading activities 136 3.3. Additional measures 139 BIBLIOGRAPHY 141 x LIST OF TABLES TABLE 1: Operational event examples – rogue traders in perspective 2 TABLE 2: Top seven operational losses selected for further analysis 8 xi LIST OF FIGURES FIGURE 1: Incentive schemes – front office vs controlling staff 6 FIGURE 2: CBOE Volatility Index (VIX) 14 FIGURE 3: CAC40 & DAX Indexes 16 FIGURE 4: Société Générale Group stock 17 FIGURE 5: S&P 500 Index 19 FIGURE 6: Market reaction to Kobe earthquake 116 FIGURE 7: Leeson and SIMEX Nikkei Futures 116 FIGURE 8: True net position of Barings in British Pounds 120 1 CHAPTER 1: INTRODUCTION Background The purpose of this research is to examine some of the largest rogue trading events in history from an operational risk management perspective. A deep review of rogue trading cases has prompted the need to understand what role risk culture played in facilitating these losses. Because of the financial crisis of 2007-2008, there has been an industry-wide effort to more effectively manage risk culture, driven by continuing high-profile conduct failings and growing pressure from regulators, consumers, and shareholders to tighten controls on risk behavior. Tim Geithner, Secretary of the United States Treasury, said he realized Merrill Lynch’s risk culture was not in great shape when John Thain, then chief executive, did not know the name of his chief risk officer – who at the time was sitting next to him. The anecdote demonstrates a truth that is in danger of being lost in the regulatory clamor for banks to hold even more capital: that the driver for bank failure is not insufficient capital but rather a bad “risk culture.”1 1 Samuels, Simon. “A culture is more important than a capital one.” Financial Times, November 24, 2014. 2 Rogue trader events have been the largest operational events for the banking industry (high severity, low frequency). See Table 1 for a comparison of severity and frequency combinations for different industries. Table 1: Operational event examples – rogue traders in perspective2 Definition A good working definition of rogue trading can be given as follows: “Trading activity that undertakes speculative and unprotected one-way trading positions (naked trading – without or with inadequate hedging positions), with the aim of creating large profits once the market moves in favor of the position. Typically, fraudulent activity is undertaken to hide the one-way nature of the trade by manipulating internal controls and systems. The frequency of this fraudulent activity increases when the markets move in an unfavorable way to the position, in an attempt to mask actual P&L losses, until a time when the market moves too far in an unfavorable way, thus exposing the position.”3 Rogue trading does include intentional mis-marking of positions; trading of positions and products without authorization, breaching agreed trading desk mandates and failure to report breaches to supervisors; buy-to-cover (when a legitimate trade goes into 2 Corrigan, Joshua, Luraschi, Paola. “Operational risk modelling framework.” Milliman Research Report, February 2013, pp. 13. http://www.milliman.com/uploadedFiles/insight/life-published/operational-risk- modelling-framework.pdf 3 ORX (Operational Risk Exchange) Association Scenario Program, ORX Driver Workbook: Rogue Trading, December 11 2014, pp.3 3 loss territory and the trader tries to cover losses using unauthorized trading activity); manipulation of trading systems to hide trades; and use of suspense accounts to book losses or fake trades. It does not include other types of unauthorized activity (tax evasion and bribery, opening and closing or altering accounts, transferring funds; transferring cash from branch to branch, performing any transaction in a manner that does not comply with internal policies and procedures; approval or processing of transactions or accounts where you have a personal connection; securities fraud (stock fraud and investment fraud, stock manipulation, embezzlement by stockbrokers, offers of risky investment opportunities, misstatements on financial records, insider trading, front running); or corporate/market misconduct (“pump-and-dump” and other forms of market manipulation, scalping via “stock picks of the month”, accounting fraud, naked short selling, spreading of false information in the form of “short and distort”, or Ponzi schemes).
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