Introduction

• It is important to examine the case studies of famous financial disasters. The purpose of these case studies is to understand how various risk factors can materialize and, when ignored, escalate into major disasters. These cases are classified by the risk factors involved. In each case, however, multiple risk factors simultaneously caused and exacerbated the crisis, leading to major losses.

Interest Rate Risk – The Savings And Loan Crisis

• Over the last century, interest rate risk has caused the failure of individual firms as well as entire industries within the financial services sector. One notable example is the collapse of the US S&L industry in the 1980s. The US S&L industry prospered throughout most of the twentieth century due to –
  • Regulations governing interest paid on deposits (i.e., Regulation Q) and
  • An upward-sloping yield curve.
• The upward-sloping yield curve meant that the interest rate borrowers paid on a ten-year residential mortgage exceeded the rates on the short-maturity savings and time deposits that were S&L’s main source of funding. S&Ls simply had to “ride the yield curve” to make money.
• However, in the late 1970s, the Fed implemented restrictive monetary policy to counter rising inflation, which increased the interest rates significantly. This increase in short-term rates pushed up funding costs for S&Ls, wiping out the interest rate spread they depended on for their profit margin. The spike in their short-term funding costs (which were needed to finance long-term fixed-interest rate mortgages) meant that S&Ls generated negative net interest margins on many of their long-term residential mortgage portfolios.
• The failure of the S&Ls to manage their interest rate risk helped to spark a long-running crisis in the United States, which gathered force through the 1980s as S&Ls desperately sought to repair their balance sheets with new business activities and higher-margin (but riskier) lending. However, these efforts resulted in the industry losing even more money through poorly controlled credit and business risks. Between 1986 and 1995, 1,043 out of 3,234 S&Ls in the United States failed or were taken over and this number further decreased to less than 2,200. This crisis led to the world’s most expensive banking system bailout worth USD 160 billion, funded by American taxpayers.

Lessons learnt

• To mitigate interest rate risk, firms must manage their balance sheet structure such that the effect of any interest rate movement on assets remains highly correlated with the effect on liabilities. This must be the case even in volatile interest rate environments. Such a correlation can be partially achieved using classical duration matching tools. More sophisticated methods involve the use of interest rate derivative products such as caps, floors, and swaps.

Funding Liquidity Risk – Lehman Brothers

• Funding liquidity risk can stem from external market conditions (e.g., during a financial crisis) or from structural problems within a bank’s balance sheet. Most often, however, it stems from a combination of both. The collapse of Lehman Brothers at the height of the 2007-2009 financial crisis offers an example of funding liquidity crisis that was prompted by unexpected external conditions.
• During the late 1990s and early 2000s, investment bank Lehman Brothers invested heavily in the securitized US real estate market. The institution pioneered an integrated business model to sell mortgages to residential customers, repackage them into securitized assets, and then sell these assets to investors.
• In 2006, the real estate market in the United States soured and housing prices began to decline but, Lehman continued to build up its real estate securitization business. Instead of acting as a middleman in the securitization process, the bank continued to increase the amount of mortgage-related assets it held as longer-term investments for its own account. Lehman also began to make outsized bets on US commercial real estate.
• Ultimately Lehman’s leverage ratio and funding strategy using the repo market turned this investment position into a disaster. In the run up to the crisis, Lehman pursued leverage to excess. By 2007, the bank had an assets-to-equity ratio of around 31:1.
• The bank’s funding strategy introduced a fatal element of fragility. Lehman began borrowing huge amounts of money on a short-term basis to fund relatively illiquid long-term real estate assets. These factors meant that the firm had to depend heavily on the confidence of its funders and counterparties if it was to continue to borrow the funds necessary to stay in business.
• During the second half of 2007, the US housing bubble had burst and the subprime mortgage market was in deep trouble. As a result, confidence eroded in firms heavily invested in subprime securities. Investors questioned the accuracy with which Lehman had valued its real estate-based assets. Market confidence, so critical to the firm’s funding strategy, was ebbing fast.
• Many of the bank’s major counterparties began demanding more collateral for funding transactions, others began reducing their exposure or simply refused to deal with the firm. In the early hours of September 15, 2008, Lehman Brothers was forced to file for bankruptcy.

Funding Liquidity Risk – Continental Illinois

• The case of Continental Illinois Bank is an example of how internal credit portfolio problems can precipitate a funding liquidity crisis. Continental Illinois was once the largest bank in Chicago.
• The first sign of Continental’s problems surfaced with the closing of Oklahoma-based Penn Square Bank. This smaller bank had issued loans to oil and natural gas companies in Oklahoma during the boom of the late 1970s. If a loan was too large for it to service, Penn Square would pass it on to a larger institution such as Continental Illinois. But as oil and natural gas prices decreased after 1981, some firms began to default on their debt. In 1982, Penn Square became insolvent and regulators stepped in to close the bank.
• At this time, Continental held more than USD 1 billion in loans to Penn Square’s oil and gas customers, and therefore suffered heavy losses as defaults rose. Unlike other banks, Continental had a tiny retail banking operation and a relatively small amount of core deposits. Therefore, it relied primarily on federal funds and floating large issues of certificates of deposit (CDs) to fund its lending business.
• When Penn Square failed, Continental found itself increasingly unable to fund its operations from the US Markets and began to raise money at much higher rates in foreign wholesale money markets. But when rumors about Continental’s worsening financial condition spooked the international markets in May 1984, the bank’s foreign investors quickly began to withdraw their deposited funds.
• Continental Illinois was confronted with a full-blown liquidity crisis as depositors withdrew USD 6 billion in only ten days. Regulatory authorities eventually stepped in to prevent a domino effect on other banks, which they feared might put the entire US banking system at risk.

Funding Liquidity Risk – Northern Rock

• The 2007 failure of mortgage bank Northern Rock is a more recent illustration of liquidity risk arising from structural weaknesses in a bank’s business model. In this case, a combination of an excessive use of short-term financing for long-term assets and a sudden loss of market confidence triggered a funding liquidity crisis that rapidly led to disaster.
• Northern Rock was a fast-growing medium-sized mortgage bank based in the United Kingdom. The bank had been growing assets at around 20% per year for several years prior to the 2007 crisis. The bank’s rate of growth was supported by an originate-to-distribute business model that was unusual among UK banks. As a result, Northern Rock relied much more heavily on investors and wholesale markets and less on retail deposits for funding in comparison to many of its UK peers.
• The bank hoped to mitigate possible weaknesses in this funding strategy by diversifying its funding markets geographically. When widespread doubts about mortgage-related assets began to surface among investors in early 2007, the interbank funding market froze. Due to this, all of Northern Rock’s global funding channels seized up.
• To support Northern Rock, the Bank of England internally planned a support operation. This news was leaked, which set a scene for a run on deposits. The bank run calmed down slowly after UK authorities publicly promised that deposits would be repaid in full. Northern Rock had to accept emergency government support and then public ownership.

Lessons Learned

• As a result of the 2007-2009 crisis, the US Federal Reserve mandated liquidity stress testing programs, for the largest banks, aimed at ensuring that banks have liquidity and funding strategies to survive system-wide stress scenarios. This can be accomplished either by Asset/liability management (ALM) or by using derivatives such as interest rate swaps. The two types of trade-offs inherent in ALM decisions are –
  • A trade-off between funding liquidity and interest rate risk – When funding liabilities have shorter duration than loan assets, the bank is exposed to less interest rate risk and more funding liquidity risk and vice-versa.

• • A trade-off between cost and risk mitigation – To mitigate funding liquidity risk in a positively sloped yield curve environment, institutions can increase the maturity of their funding liabilities. However, it is costly than cheaper shorter-duration funding.
• Banks may also mitigate funding liquidity risk by reducing the maturity of their assets but this is not always possible because asset maturity is often driven by borrower demand, the nature of a bank’s business, and its competitive environment.
• As it is not possible to perfectly coordinate liquidity, firms also need emergency liquidity cushions to ensure they can meet their commitments and reduce the risk. This risk reduction can be costly as highly liquid and marketable assets yield lower returns than less liquid assets and credit lines also incur a cost, even if the funds are not drawn.
• Again, banks must consider the significant trade-off between pursuing a risky funding liquidity strategy and the cost of that strategy compared with less risky strategies and liquidity reserves.

Implementing A Hedging Strategy

• Developing and implementing effective hedging strategies can be both beneficial and challenging. The function or individual(s) responsible for developing hedging strategies needs access to relevant information and tools, including market data, corporate information, and oftentimes advanced statistical tools. It is also critical that the risk management function has a deep understanding of their proper uses and limitations.
• A key decision for a firm is the choice of whether to use static or dynamic hedging strategy.
  • A static strategy involves the purchase of a hedging instrument that very closely matches the position to be hedged and is typically held for as long as the underlying position is kept, or for a set period of time. It has the advantage of being relatively easy to implement and monitor. It focuses on the result of the strategy at the horizon.
  • A dynamic strategy involves adjusting the hedge through a series of ongoing trades to continuously calibrate the hedge position to the underlying exposure. It involves greater managerial effort to implement and monitor, and may involve higher transaction costs. It tries to rebalance the strategy over short intervals of time.

• Time horizon is also an important aspect. In static and dynamic hedging strategies, horizons can be fixed or rolling. Regardless of the choice of horizon, performance evaluations and investment horizons should be aligned.
• Accounting issues need to be considered when devising a hedging strategy. Accounting rules related to derivatives and hedging can be quite complex and are subject to change. A derivative and the underlying position it is intended to hedge must be perfectly matched (e.g., regarding dates and quantities) in order for them to be reported together in operational profit without the need to report an accounting profit or loss.
• Without such a matching, the International Financial Reporting Standards (IFRS) require that the hedge’s mark-to-market profit (or loss) be recorded. If the hedge is at least 80% effective, the resulting profit or loss can be recorded in the firm’s operational or gross profit. Otherwise, the financial position will be recorded in the financial expenses, while the underlying position will be recorded in the operational expenses.

Implementing A Hedging Strategy – Metallgesellschaft

• MGRM was a US subsidiary of Metallgesellschaft AG, an industrial conglomerate based in Frankfurt, Germany. In 1993, MGRM entered into long-term, fixed-price contracts to deliver oil products to end-user customers. MGRM could not change its prices after these contracts were signed, it was exposed to the risk of rising energy prices.
• Lacking a liquid market for appropriate long-term futures contracts to hedge its price risk, MGRM implemented a dynamic hedging strategy, known as a rolling hedge, that used short-dated energy futures contracts. It can be profitable when the spot price of assets is higher than the futures price (this behavior of prices is known as backwardation). The derivative position was adjusted monthly to reflect the changing amount of outstanding contracts to be hedged in order to preserve a one-to-one hedge. This type of strategy can result in losses when the opposite price relationship exists (a situation known as the market being in contango).
• MGRM was exposed to curve risk (i.e., the risk of shifts in the price curve between backwardation and contango) and basis risk resulting from deviations between short-term prices and long-term prices. Spot oil prices fell significantly in 1993, from nearly USD 20 a barrel mid-year to less than USD 15 a barrel by year-end. This led to USD 1.3 billion in margin calls on MGRM’s long futures positions that had to be met in cash. While MGRM had unrealized economic gains on its original short forward contracts, it had a (temporary) substantial negative cash flow.
• The problem was exacerbated when the oil price curve changed shape, moving from backwardation to contango. MGRM’s parent company, which had been told the position was hedged and therefore did not expect a negative cash flow, ordered the hedges liquidated in December 1993. This resulted in large paper losses being turned into large realized losses.

Hedging Considerations

• The MGRM case highlights the discrepancy between economic and accounting hedging, and between hedging the P&L or hedging the cashflows. Although MGRM was nearly fully hedged in economic terms, it was fully exposed in accounting terms and was therefore not prepared to absorb liquidity risk.
• Another important consideration is the tax implications arising from a hedging strategy as they may have very different tax implications and this can have a big impact on the cash flows of a firm. Getting competent professional guidance on tax matters is therefore critical when developing and implementing a hedging strategy.
• For any strategy to be successful, it must be effectively implemented. This is especially important because markets can move and prices can change, making what had initially appeared to be an attractive hedging opportunity unattractive. During implementation, firms must be ready to adapt to changing conditions with the same care and thoroughness that went into the original strategy design.

Model Risk – The Niederhoffer Put Options

• Sophisticated financial products often rely on valuation models to determine their prices. Models can be theoretical (e.g., CAPM) or they can be statistically based (e.g., the term structure of interest rates). Use of models for pricing these financial products poses model risk. These can stem from using an incorrect model, incorrectly specifying a model, making wrong assumptions, and/or using insufficient data and incorrect estimators.
• The annals of finance history are filled with examples of strategies based on faulty assumptions (e.g., assumptions about the underlying asset price or interest rate process), as well as other types of flawed models, processes, and controls.
• Victor Niederhoffer was a star trader who ran a very successful and well-established hedge fund. One strategy of the fund involved writing large quantities of uncovered (i.e., “naked”) deep out-of-the-money put options on the S&P 500 Index and collecting the option premiums. Because these were deep out-of-the-money, the premiums collected from these options were quite small. An assumption underlying this strategy was that a one-day market decline of more than 5% would be very rare and if market returns were normally distributed such a decline would be virtually impossible.
• The strategy was undone, however, when the stock market fell by over 7% in one day in October 1997 which was followed by a large overnight decline in the Hang Seng Index, which in turn was the result of a crisis developing in Asian markets. On the back of this shock, liquidity in the markets dried up. Unable to meet over USD 50 million in margin calls, the fund’s brokers liquidated Niederhoffer’s positions for pennies on the dollar and wiped out the fund’s equity.

Lessons Learnt

• The lesson from this case is that one can construct a strategy with options that will produce a small profit over an extended period but there is always a small probability for a major loss. In other words, competitive financial markets rarely offer a “free lunch.”

Model Risk – Long Term Capital Management

• LTCM seemed destined for success. The team had big names like John Meriwether, the famous bond trader from Salomon Brothers, along economists Scholes and Merton, as well as David Mullins, a former vice-chairman of the Fed.
• The fund employed an arbitrage strategy that was based on market neutral trading (also known as relative-value trading). This involves the purchase of one asset and the simultaneous sale of another and are designed to exploit relative mis-pricings between the assets. As a result, they generate profits when the price spread between assets moves in the anticipated direction, regardless of directional movements in the overall market.
• Because differences in values were tiny, the fund needed to take large and highly leveraged positions in order to make a significant profit. LTCM was growing heavily and in the start of 1998, it had $125 billion of assets on $4.7 billion of equity capital, having a leverage of 28 to 1. The economic leverage was much higher.
• Convergence trades were executed which were of four types –

• • Convergence among US, Japan, and European sovereign bonds;
  • Convergence among European sovereign bonds;
  • Convergence between on-the-run and off-the-run US government bonds;
  • Long positions in emerging markets sovereigns, hedged back to dollars.
• Many of these strategies, based on extensive and intensive empirical research by top-level academics and practitioners at the firm, appeared safe at first glance. But building models, or strategies, on relationships that exist during benign market conditions makes them vulnerable to failure during extreme, or crisis, situations. downfall was triggered in August 1998 when the government of Russia declared a moratorium on its debt and devalued its currency. This made many market participants fearful of the possibility of other sovereign defaults.

Key Events

• 17 August 1998 (The Trigger) – Russia devalued its currency and unexpectedly defaulted on its debt. It led to a massive “flight to quality”, with investors getting out of any remotely risky market and getting into “risk-free” government bond market. The banks guaranteeing the ruble hedge shut down when the Russian ruble collapsed, and the Russian government prevented further trading in its currency. Ultimately, this results in a liquidity crisis of enormous proportions, creating huge losses for LTCM’s portfolio.
• 1 September 1998 – LTCM’s equity dropped to $2.3 billion. As its trading losses mounted and its cash ran low, LTCM found itself increasingly unable to meet the growing number of margin calls. The fund’s high degree of leverage exacerbated the problem, and it was forced to sell securities at a massive discount.
• 22 September 1998 – LTCM’s equity dropped to $600 million. The portfolio did not shrink significantly, and so its leverage was even higher. Banks begin to doubt the fund’s ability to meet its margin calls but could not move to liquidate as it could lead to a crisis causing huge losses among the fund’s counterparties and could potentially lead to a systemic crisis.
• 23 September 1998 – The Federal Reserve Bank of New York, acting to prevent a potential systemic meltdown, organized a rescue package under which a consortium of leading investment and commercial banks, including LTCM’s major creditors, injected $3.5-billion into the fund and took over its management, in exchange for 90% of LTCM’s equity.
• Fourth quarter 1998 – The damage from LTCM’s near-default was widespread. Many banks had to do a substantial write-off as a result of losses on their investments. UBS took a third-quarter charge of $700 million, Dresdner Bank AG a $145 million, and Credit Suisse $55 million.
• 15th January 1999 – Brazil devalued its currency, which further increased risk premiums. The increase in volatility led to losses in LTCM’s equity volatility strategies.

Risk Measurement Models and Stress Testing

• LTCM made heavy use of a Value-at-Risk (VaR) model as part of its risk control. VaR is a measure of the worst-case loss for an investment, or set of investments, given normal market conditions, over a specific time horizon, and at a given confidence level. LTCM felt that it had structured its’ portfolio so that the fund’s risk should not have exceeded that of the S&P 500.

• LTCM Model did not consider that a major portion of its balance sheet was exposed to a general change in the “price” of liquidity. As liquidity became more valuable, its short positions increased in price relative to its long positions which was a massive, unhedged exposure to a single risk factor.
• Some assumptions made when calculating regulatory VaR calculations do not necessarily apply to hedge funds –
• The time horizon for economic capital should be the time it takes to raise new capital, liquidate positions in an orderly manner, or the period over which a crisis scenario will unfold. Based on the experience of LTCM, 10 days is clearly far too short a time horizon to determine a hedge fund’s VaR.
• Liquidity risk is not factored into traditional static VaR models. Such models assume that normal market conditions prevail and that markets exhibit perfect liquidity.
• Correlation and volatility risks i.e., the risk that the realized correlations and volatilities significantly deviate from expectations) can be captured only through stress testing. This was probably the weakest point of LTCM’s VaR system.
• The breakdown in the historic correlation and volatility patterns assumed in LTCM’s models led to most of its losses. During the run-up to its collapse, LTCM experienced daily volatility of more than US 100 million, more than twice the level it envisioned. Furthermore, despite estimating its ten-day VaR to be USD 320 million, LTCM suffered losses of over USD 1 billion. Simply put, LTCM’s risk model had fatal flaws that ultimately contributed to the firm’s demise.
• Ironically, LTCM’s strategies were valid in the medium term, and as the crisis ended, the banks that took over LTCM realized substantial profits.

Model Risk – The London Whale

• JP Morgan Chase & Company is the largest financial holding company in the United States, with $2.4 trillion in assets. It is also the largest derivatives dealer in the world and the largest single participant in world credit derivatives markets.
• In 2006, the bank’s Chief Investment Office (CIO) approved a proposal to trade in synthetic derivatives, a new trading activity also called Synthetic Credit Portfolio (SCP). In early 2012, the CIO placed a massive bet on a complex set of synthetic credit derivatives that lost at least $6.2 billion.
• These losses were the result of the so-called “London Whale” trades executed by traders in its London office-trades so large in size that they roiled world credit markets. The trading losses quickly doubled and then tripled despite a relatively benign credit environment.
• In December 2011, the CIO was asked to reduce its Risk Weighted Assets (RWA). In January 2012, rather than dispose of the high risk assets in the SCP, the CIO launched a trading strategy that called for purchasing additional long credit derivatives to offset its short derivatives positions and lower the CIO’s RWA in that manner.
• This trading strategy not only ended up increasing the portfolio’s size, risk, and RWA, but also, by taking the portfolio into a net long position, eliminated the hedging protections the SCP was originally supposed to provide.

Operational Risk

• The CIO had typically established the daily value of a credit derivative by marking it at or near the midpoint price in the daily range of prices offered in the marketplace. But later in the first quarter of 2012, the CIO began to assign more favorable prices within the daily price range to its credit derivatives. Due to this, two different business lines within JP Morgan Chase, the CIO and the Investment Bank, assigned different values to identical credit derivatives holdings.
• The more favorable prices enabled the CIO to report smaller losses in the daily profit/loss (P&L) reports that the SCP filed internally within the bank. By March 16, 2012, the SCP had reported year-to-date losses of $161 million, but if midpoint prices had been used, those losses would have swelled by at least another $432 million to a total of $593 million.
• In May, the bank’s Deputy Chief Risk Officer directed the CIO to mark its books in the same manner as the Investment Bank, and brought down an end to the mismarking.

Corporate Governance – Poor Risk Culture

• In contrast to JPMorgan Chase’s reputation for best-in-class risk management, the whale trades exposed a bank culture in which risk limit breaches were routinely disregarded, risk metrics were frequently criticized or downplayed, and risk evaluation models were targeted by bank personnel seeking to produce artificially lower capital requirements.

• The CIO used five key metrics and limits to gauge and control the risks associated with its trading activities, including Value-at-Risk (VaR) but the SCP trades breached the limits on all five risk metrics.
• Many breaches were routinely reported to JPMorgan Chase and CIO management, risk personnel, and traders. The breaches did not, however, spark an in-depth review of the SCP or require immediate remedial actions to lower risk and were largely ignored.

Fudging VaR Models

• To eliminate the breach of its own and the bank-wide VaR limit, an alternative CIO model was hurriedly adopted which immediately lowered the SCP ‘s VaR by 50%. This not only enabled CIO to end its breach, but also to engage in substantially more risky derivatives trading.
• Months later, the bank determined that the model was improperly implemented, requiring error-prone manual data entry and incorporating formula and calculation errors. On May 10, the bank backtracked, revoking the new VaR model due to its inaccuracy in portraying risk, and reinstating the prior model.

Rogue Trading And Misleading Reporting – Barings

• The incident – There was a loss of approximately $1.25 billion due to the unauthorized trading activities of a junior trader named Nick Leeson during 1993 to 1995.
• The result – The size of the losses along with potential additional losses on outstanding trades were huge as compared to Baring Bank’s capital, which forced Barings into Bankruptcy in February 1995.
• How unauthorized positions arose –
  • Leeson took large speculative positions in Japanese stocks and interest rate futures and options and reported that he was taking positions on behalf of customers, whom he faked.
  • He booked the losses on these fake customer accounts and manufactured profits for his own accounts, so that he got a bonus of $720,000 in 1994.
• How unauthorized positions were not detected –
  • Leeson worked hard to create false customer accounts and the management ignored all controls and did not act in spite of obvious indications. They did not inquire how a low-risk trading strategy generated such huge profits.
  • To save money, the management allowed Leeson to function as the head of trading and the back office at an isolated branch.
  • The organization structure added to confusion as to who was reporting to whom, and finally different risk control areas looked at different reports that did not align.
  • Financial control system was inadequate in terms of understanding the requirement of funding by Baring London to Barings Singapore.
  • External auditors failed in examining the nature of large funding done by London head office to Singapore operations.
  • The regulator knew the extent of profits reported by Barings Singapore and the large exposure of Barings London to Singapore operations, but still allowed concession to Barings Bank.
• How unauthorized positions were finally detected –
  • The size of the losses gradually got so huge that Leeson fled away leaving behind a ‘sorry’ note. At his trial at Singapore District Court, Leeson, admitted charges of forgery and cheating.
• Lessons Learnt –
  • A main lesson to learn from the Barings collapse is that reporting and monitoring of positions and risks must be separated from trading. It should be incumbent upon risk managers to analyze if the reported business profits seem logical with respect to the positions held.
• • The management should be competent and try to investigate any matter where the slightest of doubt is raised.
• • There should be an independent trading back office.
• • Detailed inquiries should be made regarding unexpected sources of profit (or losses).
• • Detailed inquiries should also be made regarding the unexpected movement of cash.

Financial Engineering

• Derivatives like forwards, swaps, and options are the main building blocks of financial engineering. They can be used separately to hedge specific risks or be combined to form complex structures that meet client needs. These allow investors and institutions to break apart (i.e., segment) risks. Conversely, derivatives can be used to manage risks on a joint basis.
• The financial engineers responsible for devising complex instruments do so to satisfy the risk return appetites of their clients. But financial engineering is not by itself risk management, and in the world of derivatives the line between hedging and speculation can be blurry.
• Firms may be tempted to enter into complex transactions that enhance immediate portfolio returns. However, enhancing returns almost always means taking on more risk in some form or other. This risk may come in the form of an unlikely but potentially very severe future loss.

Financial Engineering – Bankers Trust

• In the early 1990s, Bankers Trust (BT) proposed that clients Procter & Gamble (P&G) and Gibson Greetings enter complex leveraged swaps to achieve lower funding costs. In the swap with P&G, for example, BT would pay a fixed rate to P&G for five years, while P&G would pay a floating rate, which was the commercial paper rate minus 75-basis points if rates remained stable.
• But, through a complex formula, the floating rate would increase considerably if rates rose during the period; for example, an increase of 100-basis points in rates produced a 1035-basis point spread over the commercial paper.
• In 1994, the Fed increased the federal funds rate by 250-basis points, causing colossal losses for both P&G and Gibson Greetings. Both companies sued BT for misrepresenting the risk embedded in these complex swap transactions. BT never quite recovered from the ensuing reputational damage and was eventually acquired by Deutsche Bank.

Financial Engineering – Orange County

• Repos allow investors to finance a significant portion of their investments with borrowed money (i.e., leverage). But using leverage means that the profit or loss on any position is multiplied; even a small change in market prices can have a significant impact on the investor.
• Leverage, through the use of repos, was part of the undoing of California’s Orange County. In the early 1990s, Orange County treasurer Robert Citron borrowed USD 12.9 billion through the repo market and accumulated around USD 20 billion of securities even though the fund he managed had only USD 7.7 billion in invested assets.
• The borrowed funds were used to purchase complex inverse floating-rate notes whose coupon payments decline when interest rates rise. In the years before 1994, Citron was able to increase the return of the fund by 2% compared to similar pools of assets.
• In 1994, the Federal Reserve raised interest rates by 250-basis points which led to a decline the market value of his positions, generating a loss of USD 1.5 billion by December 1994. At the same time, some of the fund’s lenders stopped rolling over their repo agreements. Ultimately, Orange County was forced to file for bankruptcy.
• This debacle was caused by a combination of excessive leverage and a risky (and eventually wrong) interest-rate bet embedded in the securities bought by the fund. Citron later admitted he did not understand either the position he took nor the risk exposure of the fund.

Lessons learnt

• Firms need to understand the risks that are inherent in their business models. Senior management then needs to deploy robust policies and risk measures tying risk management, and particularly the use of derivatives, to risk appetite and overall business strategy as it has been communicated to stakeholders.
• Management, and boards, should always ask where the risks are hiding and under what circumstances could they produce a loss.

Financial Engineering – Sachsen

• Prior to the 2007-2009 financial crisis, some of the biggest buyers of US subprime securities were European banks including a publicly owned bank in Germany, the Leipzig-based Sachsen Landesbank.
• The bank traditionally specialized in lending to regional small- and medium-sized companies. However, during the boom it opened overseas branches and developed investment banking businesses. The MBS required expertise in pricing of these securities and the bank lacked this expertise.
• Sachsen opened a unit in Dublin tasked with setting up vehicles to hold large volumes of highly rated US mortgage-backed securities. While these vehicles were technically off the parent bank’s balance sheet, they benefited from the guarantee of Sachsen itself.
• This operation was highly profitable but also too large when compared to the size of Sachsen’s balance sheet. During the subprime crisis, the whole capital of the bank was wiped out and the bank was sold to another German state bank, Landesbank Baden-Württemberg.

Reputation Risk – Volkswagen Emission Cheating Scandal

• A firm’s reputation is based on the belief that it can and will fulfill its promises to counterparties and creditors, and that the enterprise is a fair dealer and follows ethical practices. In recent years, reputation risk has become more prominent with the rapid growth of public and social networks. As a result, the reputational damage for unethical conduct can be very severe.
• In 2015, the US Environmental Protection Agency (EPA) announced that Volkswagen had programmed certain emissions controls on its diesel engines to be activated only during regulatory testing but not during real-world driving. Volkswagen executives in Germany and the US acknowledged the deception on a conference call with the EPA and California officials.
• The damage to Volkswagen, the world’s biggest carmaker, was significant.
  • The share price of the company fell by over by one-third.
  • The firm faced billions of dollars in potential fines and penalties.
  • Numerous lawsuits were filed.
  • Its reputation, particularly in the important US market, took a severe hit.
  • German government officials expressed concerns that the value of the imprimatur “Made in Germany” would be diminished because of Volkswagen’s actions.

Corporate Governance – Enron

• Enron was formed in 1985 following the heavily leveraged merger of InterNorth and Houston Natural Gas. Due to deregulation, however, the firm lost the exclusive rights to its pipelines. So, Enron devised a new and innovative business strategy to become a so-called “gas bank” but constantly pushed for deregulation of the energy market, which would give the firm greater flexibility to pursue its business model. Enron played a key role in the 2000-2001 California electricity crisis.
• The business strategy used by Enron involved buying gas from various suppliers and selling it to a network of consumers at guaranteed amounts and prices. In return, Enron charged fees for these transactions and successfully created a market for energy derivatives. By taking power plants offline during times of peak demand, Enron could raise power prices by up to 2,000%. Because the California government had capped retail electricity prices, Enron’s actions squeezed revenue margins across the industry and eventually led to the bankruptcy of Pacific Gas and Electric Company in 2001.
• Enron itself declared bankruptcy in December 2001 and was the largest corporate bankruptcy in US History at the time.
• Many in Enron’s senior management acted in their own self-interest and against the interests of shareholders (this is known as agency risk). Enron chairman and CEO Ken Lay was charged with “falsifying Enron’s publicly reported financial results and making false and misleading public representations about Enron’s business performance and financial condition.”
• Enron’s board also failed to fulfill its fiduciary duties to the shareholders. The board was aware of and allowed the CFO to become the sole manager of a private equity fund that did business with Enron. The private equity fund lacked economic substance. Enron also used “creative” (i.e., fraudulent) accounting practices to hide flaws in its actual financial performance. It transferred its stock to a special purpose vehicle (SPV) in exchange for either cash or notes. The SPV classified the Enron stock as an asset on its balance sheet. In turn, Enron guaranteed the SPV’s value to reduce its credit risk. Importantly, Enron failed to adequately disclose the lack of an arm’s length relationship between the company and the SPV.
• Another fraudulent accounting practice that Enron followed was used to build a physical asset, and then immediately declare a projected mark-to-market profit on its books. It would do this even though it had not yet made any money from the physical asset. If the revenue from the asset was less than the projected amount, then Enron would simply transfer the asset to an SPV. The financial loss would therefore go unreported and Enron could write off unprofitable activities without impacting the bottom line.
• Arthur Andersen, formerly one of the Big Five accounting firms, was responsible for auditing the books of Enron. Andersen either failed to catch or explicitly approved many of the fraudulent accounting practices that led to Enron’s collapse. Once the scandal came to light, Andersen was forced to surrender its accounting licenses.
• The aftermath of this debacle resulted in the following –

• • In the United States, the Sarbanes-Oxley Act (SOX) of 2002 was a key legislative reform that resulted from the Enron debacle, along with associated changes in stock exchange and accounting rules.
  • SOX created the Public Company Accounting Oversight Board (PCAOB), which has assumed an important role in promoting good corporate governance and financial disclosure.

Cyber Risk – The Swift Case

• Cyber risk has become a critically important consideration in recent years. Banks’ systems can be hacked, their ATMs can be used to steal money and client information, customer identities can be stolen and misused, and so on. Financial institutions are spending billions of dollars every year on their systems to make them safer. These systems must be protected from the outside world as well as from internal misuse. Threats to the banking system from cyberattacks are also a major concern to international regulatory bodies, such as the Bank for International Settlements (BIS) and the International Monetary Fund (IMF), as well to local regulators.
• SWIFT is the world’s leading system for transferring funds electronically among banks and processes billions of dollars in transactions every day. In fact, SWIFT is considered so reliable that transactions which normally take days are instead completed in seconds.
• In April 2016, it was revealed that hackers had used the SWIFT network to steal USD 81 million from the account of the Central Bank of Bangladesh at the New York Fed with the help of a malware that sent unauthorized SWIFT messages instructing funds to be moved to an account controlled by the hackers. Then, the malware deleted the database record of the transfer and disabled transaction confirmation messages that would have revealed the theft.