Case Study

Case Study

Case Study 1: Barings Bank, PLC.

In February, 1995, Nick Leeson, a “rogue” trader for Barings Bank, UK, single-

handedly caused the financial collapse of a bank that had been in existence for

hundreds of years. In fact, Barings had financed the Louisiana Purchase between

the US and France in 1803. Leeson was dealing in risky financial derivatives in

the Singapore office of Barings. He was the lone trader there and was betting

heavily on options for both the Singapore (SIPEX) and Nikkei exchange indexes.

These are similar to the Dow Jones Industrial Average (DJIA) and the S&P500

indexes here in the US.
In the early 90s, Barings decided to get into the expanding futures/options

business in Asia. They established a Tokyo office to begin trading on the Tokyo

Exchange. Later, they would look to open a Singapore office for trading on the

SIMEX. Leeson requested to set-up the accounting and settlement functions there

and direct trading floor operations (different from trading). The London office

granted his request and he went to Singapore in April, 1992. Initially, he could

only execute trades on behalf of clients and the Tokyo office for “arbitrage”

(Lesson 10) purposes. After a good deal of success in this area, he was allowed to

pursue an official trading license on the SIMEX. He was then given some

“discretion” in his executions meaning; he could place orders on his own

(speculative, or “proprietary” trading).
Even after given the right to trade, Leeson still supervised accounting and

settlements. And there was no direct oversight of his “book” and he even set-up a

“dummy” account in which to funnel losing trades. So, as far as the London office

of Barings was concerned, he was always making money because they never saw the

losses and rarely questioned his request for funds to cover his “margin calls”

(Lesson 3). He took on huge positions as the market seemed to “go his way.” He

also “wrote” options, taking-on huge risk (Lesson 10).
He was, in fact, perpetuating a “hoax” in his record-keeping to hide losses. He

would set the prices put into the accounting system and “cross-trade” between the

legitimate, internal, accounts and his fictitious “88888” account. He would also

record trades that were never executed on the Exchange.
In January, 1995, a huge earthquake hit Japan, sending its financial markets

reeling. The Nikkei crashed, which adversely affected Leeson’s position (remember,

he had been selling Options). It was only then that he tried to hedge his

postions, but it was too late. By late February, he faxed a letter of resignation,

and when his position was discovered, he had lost ($1.4 billion USD). Barings, the

bank which financed the Louisiana Purchase between the US and France,  became

insolvent and was sold to a competing bank for $1.00!
(If  you are interested in more details regarding this infamous case, you can read

“Rogue Trader” by Nick Leeson himself. There is also a movie of the same name

starring Ewan McGregor which should be available for rent in DVD format.)
The following two cases are brief descriptions of similar, catastrophic losses by

traders with little, or no, oversight.

Case Study 2: Orange County, CA

Robert Citron was the Treasurer for Orange County, California, in the early 90s.

He was solely responsible for investing several of the county’s funds which

totaled about $7.5 billion USD. Despite having no background in trading financial

instruments, he decided to invest in risky interest rate swaps that were tied to

the US Treasury Department’s rates.
Citron was a County Tax Collector with no college degree who was later elected to

the position of Orange County Treasurer. In this capacity, he was able to push for

California legislative approval for county treasurers to increase their use of

financial instruments for investment and fund management.
He was attempting to artbitrage the difference between short-term and long-term

interest rates. His position was sound and he could make money so long as short-

term rates remained low. During his tenure, the average return on county

investments was a healthy 9.4%, but interest rates had been low for that long.The

position he took would lose money if interest rates rose. And, he inflated the

county’s volumetric position by entering into other derivatives that would also be

negatively impacted by higher interest rates.
Beginning in February, 1994 the Federal Reserve Board made the first of six

consecutive interest rate hikes. Between February and May of that year, the County

had to produce $515 million in cash (margin) to cover its position. Further margin

calls would occur throughout year, leaving the County’s cash reserves at only $350

million by November, 1994.
When word got out about the County’s troubles raising cash, investors sought to

retrieve their money, and by December 6, 1994, the County declared bankruptcy and

lost ($1.64) billion.

Case Study 3: Metallgesellschaft (MG)

MG was a huge, German industrial conglomerate that decided to open an energy

trading office in the US in the early 90s.
The original plan was threefold:
•    Sell refined products in the forward, physical market.
•    Invest in refining capacity to produce the products.
•    Hedge the forward sales through financial derivatives.
When the strategy was first implemented in 1992, current physical prices were

lower than the futures prices. So the sales contracts were set at those higher

future prices. And it meant that purchasing the “near” month futures contracts

would be profitable. So MG developed a strategy whereby they would cover the

long-term, fixed-price sales by buying contracts in these few, near months. As

each month “rolled-off,” they would merely buy contracts in the next month. It was

their intent to continue this process until the physical product sales contracts

expired in (10) years. This strategy worked as long as the futures market was

“backwardated,” whereby each successive month is lower than the prior one (Lesson

One of the major flaws in this approach, however, was the volume of contracts

being traded since they were “loading-up” on closer month contracts. Add to that

the fact that they would not get paid for the product sales for years out, and you

begin to have a cash flow problem where margin calls are concerned. Their position

in the Fall of 1993 was estimated to be between 160 to 180 million barrels

stretched-out over the following (10) years.
In 1993, prices fell as the market received a “bearish” signal from OPEC on

production quotas. This lowered futures prices and reversed the market from

“backwardated” to “contango,” whereby each successive month’s price is higher than

the prior one (Lesson 3). Faced with this position, MG management was changed and

the new team was directed to close all positions. This resulted in losses on the

futures purchases totalling almost ($1.5) billion USD. The had to seek bailout

funds from one of their banks, and in return, had to sell-off several

divisions.Today, the German industrial giant no longer exists having been bought-

out by a competitor.
Key Lessons Learned by Examining the Case Studies
There were some common themes that ran through each of these cases.
•    Single, or small groups, of “rogue” Traders (little supervision over the

decision-making process).
•    The use of risky financial derivatives.
•    Lack of real accounting/auditing oversight and/or Trader(s) controlled

•    No trading policies, controls, etc., in-place.
•    “Hidden” trade losses.
•    Lack of executive knowledge and understanding of the inherent risks in

•    Trading positions increased to lessen impact of losses led to increased

exposure (so-called, “doubling-down”).
These events, along with others, prompted the financial industry to institute ways

to monitor, track and stay on top of, financial derivative trading. These same

methods would later have to be adopted by publicly traded energy companies in the

Key Learning Points for the Mini-Lecture: Risk Control
•    Severe losses by “rogue” Traders led to the establishment of controls for

financial derivative trading in the banking and finance businesses.
•    These “risk measures” were later made mandatory for the energy industry.
•    Companies face more than just financial risk, such as legal, operational,

•    Necessary risk controls, measures, reports and organizational structure.
o    “mark-to-market”
o    “Value at Risk”
o    “P&L”
o    Volumetric
o    Risk Control Group/Chief Risk Officer/Risk Oversight Committee

Lesson 12

Risk Controls in Energy Commodity Trading

Today’s Market Environment
–    Controls for financial trading have never been as important as now
o    History of huge losses
?    Early case studies
?    Enron, et al.
?    Still occurring today
o    Extreme volatility in energy commodity prices
?    Global economy
?    Geo-political climate
o    Credit Crunch
?    Risk of losses due to counterparty collapse
?    Margin requirements – cash flow issues
o    Weather
?    La Nina
?    El Nino
?    Global Warming
?    Unpredictable hurricane seasons

Financial Risk types
–    Market
–    Operational
o    Performance
–    Liquidity
o    Lack of counterparties
o    Exchange interruptions
–    Speed of Transactions
o    Electronic Trading – 24 hours-a-day
?    ICE, ICE Future – Europe, NYMEX, GLOBEX, NYMEX Clearport
–    Legal
o    Contractual
?    ISDA
?    NAESB
?    “Force majeure”
–    Credit – post-2008 economic collapse
o    Counterparty liquidity
o    Counterparty solvency

Risk control Topics
–    Why controls? – Case studies in the financial markets
–    Risk measures
–    Energy commodity trading
–    Types of controls
–    Recommendations

Common Issues
–    Single of multiple “rouge” traders
–    Risky derivatives
–    Little or no, accountability
–    Total control of “paper trail”
–    Lack of understanding & recognition by executive of financial derivative

trading and risks involved

Risk Measures
–    “mark-to-market” (m-t-m)
o    Value of portfolio at close of day based on “settlement” prices.
–    “Value at risk” (VaR)
o    Theoretical maximum loss on total “book” for a given period of time, at a

given Confidence Level, defined holding period, at expected market conditions.
?    Expressed as a single value
•    $10 million dollar loss at 98% confidence level
?    Historical prices
?    Monte Carlo Simulation – random number generator
–    Profit & Loss (P&L) – daily profit/loss on mark-to-market changes
–    Volumetric Position – total of all derivative contracts including options

delta effect

Energy Commodity Trading
–    April 1990 – Introduction of NYMEX natural gas futures contract
o    Provided price transparency & market liquidity
o    Hedge price risk
o    Speculative (“spec”) trading
o    Proliferation of financial derivatives
?    Options – puts/calls, “Exotics”
?    Swaps (Henry Hub “look-a-like”, swing, basis)
–    SEC & CFTC: publicly-traded energy companies must implement risk controls

for FY2001
o    Must report m-t-m value as earnings
?    Enron “license to steal”
•    Create various “companies” where m-t-m earnings can be generated. More

earnings, higher share price, etc.
?    Traders now have large stake in m-t-m
•    Set “forward curves” = m-t-m manipulation
•    Set cash market indexes = market manipulation
•    “roll” positions forward/backward to gain m-t-m value
–    Post-Enron
o    Top (5) marketing companies gone in (1) year
o    Wall street leery of energy “trading” companies (now, energy “services”)
?    Analyze “book” size and m-t-m (not VaR)
o    Adopt FAS133 Hedge Accounting – shrink “spec” book
o    Sarbanes-Oxley (SOX)

–    Executive Training
–    Risk policy & procedures
o    Purpose of hedging activity
o    Risk measures & limits
o    Oversight
?    Risk control desk – positions & responsibilities
?    Risk oversight committee – Executive panel
o    Trading Policy w/ violation penalties
o    Procedures
–    FAS133 Hedge Accounting
–    Educated Internal/External Auditors
–    Sarbanes-Oxley (SOX)

Lesson Activity: Baring’s Bank Case Study
Using the information presented in this Lesson, evaluate the Baring’s Bank case to

determined where the flaws were in the risk controls.
•    What controls were lacking in the Singapore office?
•    What were Nick Gleeson’s biggest mistakes?
•    What should London have done to prevent this?
•    What controls/guidelines do you think should’ve been in place?
•    Using the “Recommendations” I have presented, which of these would you

recommend in this instance?


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