Rogue Traders
Huayuan Dong, Paolo Guasoni & Eberhard Mayerhofer
Finance & Stochastics
Business School
School of Mathematical Sciences

The expression “rogue trader” entered popular culture in 1995 when Nicholas W. Leeson, a trader of an overseas office of Barings Bank in Singapore, made unauthorised bullish bets on the Japanese stock market, concealing his losses in an error account. At first, losses were recovered with a profit, but in the aftermath of the Kobe earthquake, they reached $1.4 billion, forcing the 233 years old bank into bankruptcy. The earliest case of such acvitity is possibly the law firm of Grant & Ward in 1884, which embarrassed former president Ulysses S. Grant, one of the firm’s partners.

Since the demise of Barings Bank, rogue trading episodes have increased in frequency and magnitude. In 2008, Jerome Kerviel, a junior trader at Société Générale who had been exceeding position limits through fictitious trades to avoid detection, eventually lost $7.6 billion, the largest rogue trading loss in history. In his defense, he claimed that colleagues also engaged in unauthorised trading. Most recently, in September 2021, Keith A. Wakefield, the former head of the fixed income trading desk at the broker–dealer IFS Securities, was charged by the U.S. Securities and Exchange Commission with unauthorised speculative trading and creating fictitious trading profits, leading to the closure of IFS Securities and substantial losses to both IFS Securities and one dozen counter-parties to the trades.

Investing on behalf of a firm, a trader can feign personal skill by committing fraud that with high probability remains undetected and generates small gains, but with low probability bankrupts the firm, offsetting ostensible gains. This DCU research project demonstrates that honesty among traders requires skin in the game: if two traders with isoelastic preferences operate in continuous time and one of them is honest, the other is honest as long as the respective fraction of capital is above an endogenous fraud threshold that depends on the trader’s preferences and skill. If both traders can cheat, they reach a Nash equilibrium in which the fraud threshold of each of them is lower than if the other one were honest. More skill, higher risk aversion, longer horizons and higher volatility all lead to honesty on a wider range of capital allocations between the traders.