Case Study: Trading Scandal at Kidder Peabody

To cut a long story short; young man armed with an engineering degree from MIT and an MBA from Harvard Business School joins Kidder Peabody after working with Morgan Stanley and First Boston at age 33. He starts generating fabulous profits for his government bond desk (1991). By 1993, he was managing thirty billion dollars. The management higher up starts looking into these profits. Sadly and unfortunately for them the massive profits are fake and they are left staring at a big loss. They call in the lawyers and try to nail him. The scholarship student has been using his high-end mathematical skills to use a flaw in the system to book profits that never were. Full of righteous anger they try to pin all the blame on Joseph Jett, the man in question. He is banned from trading in any form in the USA. It was Kidder Peabody vs. Jett. It turned out the Peabody management was not entirely blameless and were in the know. A fine was slapped on Jett by the SEC for $8million. A career full of promise and opportunity goes down on the altar of high profit. Big company owner of Kidder Peabody GE sells stake to Paine Webber for big bucks, who in turn decides to do away with the Peabody name.

The trading scandal at Kidder Peabody in 1994 has all the elements of most scandals in Wall Street – greed, projections, pointing fingers, value erosion, lack of processes and big losses. If only to reiterate why these elements are not desirable in a good investment bank and its team it is important to go through the details of the Kidder Peabody case.

Jett joined the GE run Kidder Peabody government bond trading desk. His job was to make profits by stripping bonds. STRIPS is the acronym for “Separate Trading of Registered Interest and Principal Securities”. These are zero-coupon securities (zeros) of the U.S. Treasury created by physically separating the principal and interest cash flows. The process of stripping is known as coupon stripping.

All STRIPS are traded over-the-counter (OTC), with the primary government securities dealers being the largest and most important market participants. A small group of interdealer brokers disseminates quotes and broker trades on a blind basis between market participants. Arbitrageurs continually monitor the prices of STRIPS and underlying coupon-bearing bonds, looking for profitable opportunities to strip or reconstitute. Price transparency is relatively high for STRIPS since several information vendors disseminate prices to the investment public.

Jett in fact did little stripping and instead identified an accounting glitch which he used to his benefit. Jett used the system to make settlements by using incorrect valuations for forward dated transactions. He continuously forward rolled the trades, never settling them. Naturally when the actual settlement happened any false profit was negated and a loss recorded. To prevent this he generated more phony trades. To continue booking profits he continued generating more and more false trades and therefore false profits. Eventually these profits touched $350million.

Jett attracted little attention and later on big bonus checks as the profits grew. There was little investigation by top management as to how he was managing to make these profits even during a recessionary phase. It was all good as long as profits were being booked.

In 1994 he was supposed to have made trades worth 1.76 trillion, of which only $79 billion were real. His losses were eventually shown to be at $85,415,000.

Though Kidder Peabody was quick to put all blame on Jett, it pointed to a larger lack of internal controls and supervision. The technical flaw was used rather than reported by Jett for his own gains. It pointed to the rather self-congratulatory rather than professional approach from a top-end investment bank. If in fact if the details of the trades and  how profit was being made was analyzed, even if it was to provide tips to other traders in the team these flaws would have been uncovered earlier. Instead Jett seems to have used the star trader system to his benefit, even if only for a short while.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $39 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.