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Credit Default Swaps - Research Proposal Example

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This paper "Credit Default Swaps" discusses the origins of the global financial crisis of 2008, and its roots in the credit derivatives markets. Institutional trading in securitized debt in its many forms has largely been blamed for the collapse of global financial institutions…
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Credit Default Swaps
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Credit Default Swaps and Their Role in the 2008 Global Financial Crisis Overview of Research Proposal This research proposal is for the purpose of determining the probable origins of the global financial crisis of 2008, and its roots in the credit derivatives markets. Institutional trading in securitized debt in its many forms has largely been blamed for the collapse of global financial institutions which had been generally regarded as bastions of financial stability and expertise. It is to one instrument in particular – the credit derivative swap – that the credit crisis of 2007-2008 has been attributed to. While the crisis is still unfolding, it is critical that data and events be analyzed to discern the context within which an effective recovery may be more speedily administered. Research Objectives It is the objective of this research to determine the causes of the financial market collapse of 2008 and recommend directions towards a lasting solution, or prevention of the same from happening again. To come to this generalization, the paper shall attempt the following: 1. Determine the significant events in the development of the crisis; 2. Examine the instruments (primarily the CDS), markets and institutions involved in the crisis; 3. Gather a consensus on the qualified opinions and perceptions of middle and top level managers of financial and economic institutions on the crisis; and 4. Formulate recommendations on the solution of the present crisis and prevention of future occurrences of the same. Theoretical Framework: Risks in credit management and securitization Early in the 1990s, innovative inroads into credit risk management found their way into the development of the credit derivative. The credit derivative is a financial instrument designed to separate market risk from credit risk. Its purpose been described as “the transfer of credit exposure of an underlying asset or assets between two parties” (Anson et al, 2004, p. 23). It is thus a tool to manage or distribute the risk associated with the lending of funds, in order to protect the lender from credit risk. There are various types of credit risk. They are: Credit Default Risk. Default risk is the risk the borrower (the issuer of the bond or the debtor in a loan) will not pay the outstanding debt, or not pay it in full. Downgrade Risk. Downgrade risk refers to the risk that a reputable and recognized credit ratings agency reduces it credit rating for an issuer. The most relied-on ratings are those released by Moody’s Investors Services, Standard & Poor’s, or Fitch Ratings. These ratings are based on the agency’s evaluation of the debt issuer’s current earning power vis-à-vis its capacity to pay its debt obligations as they become due. Credit Spread Risk. Credit spread risk is the risk that the spread (or premium) over a reference rate will increase for an outstanding debt obligation. In contrast to downgrade risk, which is published by a particular ratings agency, credit spread risk is the financial markets’ reaction to perceived credit deterioration (Anson et al 2004, p. 23). There are also other types of risks, beside market risk and credit risk, that could affect the performance of securities trading. These would include: Operational risk refers to the possibility of a breakdown in the operations of the derivatives program or risk management system. This is envisioned in the occurrence of events such as power failures, crashed computer systems and virus problems, or human error in the recording and monitoring of records. The most important concern of operational risk is the need to insure proper controls, particularly in the actions of individuals (such as those authorized to trade) to faithfully follow policies as to what contracts and how much to trade. It is a fact that many derivatives losses are traceable to operational risks such unauthorized trades by rogue traders. (Chance 2001, pp. 714-715) Model risk is the risk that the firm may be using a pricing or risk assessment model that is inappropriate to the underlying asset, or that the proper model is being used but the wrong inputs are applied to the model, thus yielding an erroneous result. Because of the intricacies and sophistication of derivatives in general, and prevailing lack of transparency of information, this risk is not easily addressed even if detected. It is not at all unheard of that major financial institutions have committed “embarrassing errors, even in simple valuation problems such as forward contracts” that have resorted to substantial losses (Chance 2001, pp. 714-715). Liquidity risk is the risk associated with the engagement of a firm into a derivatives transaction, only to find that the market (demand and supply) for that instrument is of such low or irregular volume that it would require a significant discount (or premium) to effect a desirable exit (or entry). Accounting risk refers to the uncertainty of the appropriate accounting treatment of a derivatives transaction. “Accounting for derivatives has been a significant source of controversy and risk for many years. Users of derivatives have lived with an ongoing concern that the manner in which they account for derivatives will be declared inappropriate after the fact and that they will be required to restate certain transactions with the potential to lower past earnings figures,” according to Chance (2001, pp. 714-715). Derivatives, particularly those developed recently, have effects and considerations not yet fully understood as to be accorded a definitely proper accounting treatment. Legal risk is the risk that the legal system will lack the elements to enforce a contract. Many jurisdictions to which derivatives contracts or their counterparties are subject may lack the legislation to support the peculiar character of the contracts, or allow for loopholes that would render the enforcement of said contracts ineffective. Tax risk is the risk that tax laws or their interpretation will significantly change without warning. For example, tax risk has completely eradicated the use of certain transactions, such as the American Stock Exchange’s PRIMES and SCORES, both precursors to equity-linked debt (Chance 2001, pp. 714-715). Regulatory risk is, as the name implies, the chance that the regulatory framework or thrust will change unexpectedly. A common controversy in this regard is linked to the regulatory style of administrators – that is, some officials favour a liberal, free-market approach while others who may eventually take over would implement a more restrictive manner of regulation. There is thus the possibility that some existing or pending transactions overnight can become illegal or heavily regulated. Settlement risk is a risk common to international transactions. In transactions conducted within the span of a business day, there are at any one time markets opening at one part of the world and closing at another. It is possible that the time it takes for the resumption of a business day in the other country would introduce the risk of developments taking place seemingly “overnight” to affect certain transactions, such as the sudden suspension of payments. This risk is also known as the Herstatt risk, named after the German bank which failed in 1974 under similar circumstances. Systemic risk is the risk associated with the interconnectedness of economies, firms, or markets, and is sometimes called the contagion effect. It springs from the belief that when one company defaults (or one economy falters, etc.), it could trigger the default of one of its creditors, which could trigger further defaults. The “domino effect” if such an occurrence could create fear and panic among creditors and investors, leading to a possible meltdown of a system so dependent on trust and confidence. The economy came to such a head during the crash of October 1987 and that of September 1988. However, these two occurrences pale in comparison with the financial debacle that led to the bankruptcy of Lehman Brothers and the sale of Merrill Lynch in September of 2008, a crisis which is still unfolding. After 1988, and particularly with the introduction of credit derivatives in the 1990s, there was a exponential increase in volume of derivative transactions worldwide, and that risk management as it was known to be sufficient in the past may be inadequate to contain a meltdown today. Background of Credit Default Swaps As earlier described a credit derivative is an instrument designed to separate market risk from credit risk and to allow the separate trading of the latter. The most popular and widely used of these, and the instrument most blamed for the present credit crunch, is the credit default swap. Credit Default Swaps (CDS). This is not only the most common stand-alone product employed by asset managers and traders, but it is also used extensively in structured credit products such as CDOs and credit-linked securities (Anson et al 2004, p. 23). Phillips (2008) disclosed that the CDS was engineered by JPMorgan as a means of eliminating credit risk from its books, in order for capital reserves required by the Federal regulations to be freed up. The importance of the CDS is such that “their significance stems from the fact that they serve as building blocks for many complex multi-name products (Bomfim, 2005, p. 344). How the CDS works. A credit default swap is a bilateral agreement between two parties (the protection buyer and the protection seller) based on a significant event (the default on payment of a debt) involving a third party (the reference entity). In its “vanilla” form, the buyer of a CDS agrees to pay a regular amount to the seller for the duration of the maturity of the contract. In return, the seller agrees to make a payment to the buyer in the event that a third party (the reference entity) should default on his obligation. The relationship on many aspects is, thus, similar to an insurance contract, except for the fact that conventional insurance is restricted by tight government regulation and monitored by an oversight agency, while CDS is not. In case of a default by the reference entity, settlement may be made physically or in cash. In a physical settlement, the protection buyer has the right to deliver a range of defaulted assets to the protection seller and receive in return the full face value of the assets. The bilateral contract should specify the type of deliverable assets. It is typical for the contract to specify that the buyer may deliver any form of senior unsecured debt issued by the reference entity. It is thus conceivable that any bank loan or bond that falls within this criterion is a deliverable asset. In practice, the protection buyer will deliver the “cheapest-to-deliver” bond from the “deliverable basket”. For instance, these may include: the bond with the lowest coupon, a convertible bond, an illiquid bond, or a very long-dated bond (Anson et al, 2004, p. 23-27). In a cash settled swap, the counterparties may agree to specify a particular set of market participants to be polled in order to determine the recovery value of the defaulted assets. The protection seller thereafter becomes liable to the buyer for the difference between the face and recovery values. Cash settlement is more commonly resorted to in Europe, while physical settlement is more common in the United States (Bomfim 2005, p. 344). There are certain advantages of cash over physical settlement. Firstly, there is less administration cost associated with it. It is also more suitable where the CDS is used as part of a structured credit product, as such contracts may be accommodate the delivery of physical assets. But probably most important of the advantages is that it does not expose the protection buyer to risks in case of a shortage of deliverable assets in the market (e.g., due to illiquidity). And of course, there is greater certainty of settlement with cash than the cheapest-to-deliver bond (Anson 2004, pp. 23-27). CDS contracts define what the parties agree would be a default event. Typical default events include bankruptcy, failure to pay, debt moratorium, debt repudiation, restructuring of debts and acceleration of default. Brief Background of Financial Institutions under study There are several institutions which shall be made focus of this study, the most salient of which are Lehman Brothers, American International Group, Bear Stearns, Merrill Lynch, Fannie Mae and Freddie Mac. Lehman Brothers has been one of the worlds leading investment bankers, specializing in mergers and acquisition advice, debt and equity underwriting, and global finance. The firm primarily operated in Europe and the United States, and is based in New York. In September 15, Lehman filed for bankruptcy protection under Article 11 (Datamonitor, 2008). American International Group (AIG) is a major American insurance corporation based in New York City. The 2008 Forbes Global 2000 listed AIG as the 18th-largest public company in the world. It recently suffered from a liquidity crisis after its credit ratings were downgraded below "AA" levels, and the Federal Reserve Bank on September 16, 2008, created an $85 billion credit facility to enable the company to meet collateral and other cash obligations, at the cost to AIG of the issuance of a stock warrant to the Federal Reserve Bank for 79.9% of the equity of AIG (Andrews et al, 2008). Bear Stearns and Merrill Lynch are two of the nation’s leading underwriters of mortgage bonds. Fundamental stalwarts until the subprime market began to give way in 2007, both institutions suffered heavily in devaluations, reported losses of hundreds of millions of dollars and have written off more than a billion dollars each in mortgages and mortgage-backed securities. Bear Stearns was eventually acquired by JPMorgan. Fannie Mae and Freddie Mac are respectively the largest and second-largest underwriters of mortgage bonds in the US market. Operating under a federal charter, their participation in the market affects the lives of tens of millions of home buyers (New York Times, Dec. 20, 2008). They were taken over by the Federal Government on September 8, 2008. Brief Literature Review Most of the studies done on credit derivatives have to do with the construction of models for the most accurate possible determination of security pricing and risk measurement. In their study Default probabilities in a corporate bank portfolio: A logistic model approach, Westgaard and Van der Wijst (1999, p. 338) determined that while estimated default frequencies (EDFs) play a crucial role in credit risk modeling often relied on by banks, trying to estimate EDF from a grade system that was originally not intended for this might be dangerous and often causes mispricing of clients. The proponents develop a model using microeconomic information, combining financial ratios as well as firms fixed data to come up with a set of coefficients to assessing the default risk of the client. The main conclusion arrived at is that EDF decreases as a function of the ratios of cash flow to debt, liquidity, solidity and financial coverage, as well as with size and age. Aderholdt and Rasmussen (1996, p. 62) in their article “Using derivatives to hedge against the unexpected” published in Healthcare Financial Management, have determined that potential pitfalls exist particularly for derivatives. Derivative instruments are found to be subject to the same risks of changing market conditions that affect the underlying assets on which derivatives are based. Thus, risks pertaining to these derivative instruments should be apparent and easy to quantify. Furthermore, the price of a good many of these derivatives is more volatile than that of the underlying security or commodity, and in a sense riskier. They cite as an example, that for a portfolio of conventional 20-year US Treasury bonds, a 0.25 percent increase in interest rates would cause a 2.83 percent decline in the market value of the portfolio. The study determined, more importantly, that the most dangerous level of risk experienced by derivative instrument users is a result of the combination of extraordinary price volatility of derivatives and the use of leverage to make large bets on the direction of stock, bond, or commodity prices. “Such a combination can yield large returns, but the price of failure can be severe. For example, Barings, a $1 billion financial institution with a history predating the American Revolution, collapsed in 1995 as a result of this type of market activity. In another recent example, Orange County, California, had only a portion of its investment pool in derivatives. Orange County borrowed short and invested long. However, its position would have been worse with a greater investment in derivative securities” (Aderholdt and Rasmussen, 1996, p. 62). Bonfim (2008, p. 282) in her article “Credit Risk Drivers: Evaluating the contribution of firm level information and macroeconomic dynamics” as published in the Journal of Banking and Finance, sought to draw observations in the relation of idiosyncratic firm characteristics and systematic factors as drivers or determinants of credit risk. She concluded that in periods of economic growth there is a tendency towards excessive risk-taking by both firm-borrowers and institution-creditors. It is conclusive that where default probabilities are influenced by several firm-specific characteristics, when time-effect controls or macroeconomic variables are also taken into account, the results are reinforced. “Hence, though the firms financial situation has a central role in explaining default probabilities, macroeconomic conditions are also very important when assessing default probabilities over time” (Bonfim 2008, 282). In “Credit Default Swaps: Evolving Financial Meltdown and Derivative Disaster Du Jour” by Dr. Ellen Brown (2008, p. 34) in Global Research, centered on the risks and dangers involved in credit default swaps. Brown observes that while CDSs function as insurance contracts, institutions that deal in them they suffer from a lack of regulation which insurance companies are subjected to by the government, with reserve requirements, statutory limits, and examiners routinely monitoring the books to ensure that the company is sufficiently funded to cover potential claims. The dearth of such regulation was supposed to have been addressed by the “sacrosanct” free market in which the CDSs operate. Dubbing the CDS market the “Wall Street Ponzi Scheme,” Brown wrote that the “scheme is built on ‘fractional reserve’ lending, which allows banks to create ‘credit’ (or ‘debt’) with accounting entries. Banks are now allowed to lend from 10 to 30 times their “reserves,” essentially counterfeiting the money they lend.” She pointed out that the effect amounted to insurance fraud, with banking and institution officials benefiting from sizeable compensation schemes and ultimately leaving the public coffers to assume the burden of default in the bailout packages that followed. It is apparent from the foregoing survey that there is more to credit default swaps than they were theoretically intended for. The relative brevity in the time duration of their implementation (only slightly over a decade) and the severity of the crash to which they had subjected the global financial markets, are reasons that warrant a more detailed examination of this type of security. Proposed Methodology (per objective) The qualitative approach will be used to attain the objectives of this research, through the descriptive-historical method of inquiry. A survey, designed to gather primary data, will be conducted among middle and top-level managers of financial institutions to draw their expert views and assessments of the causes of the financial crisis and measures taken to stem its further deterioration. The proposed questionnaire is included in this proposal as Appendix A. The survey includes questions eliciting the profile of the respondents, followed by statements on the risks of the credit derivatives market, to which the respondent is asked to react. There are four possible responses to statements, to which values are assigned in the form of a four-point Likert scale, as follows: SA - Strongly Agree - 4 points A - Agree - 3 points D - Disagree - 2 points SD - Strongly Disagree - 1 point The responses will be totalled and averaged for each item, and interpreted in the following manner: 1.00 to 1.50 - Strongly Disagree 1.51 to 2.50 - Disagree 2.51 to 3.50 - Agree 3.51 to 4.00 - Strongly Agree The four-point Liker scale is chosen to eliminate any centrist tendencies in the answers and to compel the respondent to give a qualified opinion one way or the other. Secondary data, in the form of a timetable of events leading to the collapse of the global financial system will be drawn to provide the context for analysis. Other secondary data to be gathered from reputable financial market advisory firms, concerning fundamental and technical information affecting the trading and valuation of financial instruments, will be collated and analyzed in connection with the primary data acquired, and collectively and qualitatively analyzed to arrive at the objectives. The analysis will be conducted with a view to the risks to which the events are addressed, along the theoretical framework specified in this proposal. The findings and conclusions arrived at will be verified with acknowledged authorities in the field of finance and investments. Limitations of Methodology The study seeks to document a developing phenomenon and to provide useful and incisive commentary on the way to its eventual resolution. It thus has a particular advantage in that it is able to provide a perspective of a participant in a series of unfolding events, a perspective often lost in hindsight, which will be useful as a springboard for future research. The immediate unavailability of quantitative data, however, is inevitable as entities with an active interest in the issue will expectedly control the release of such data. This will be an impediment to the formulation of more precise conclusions through econometric tools that would have aided construction of quantitative models. Also, as the complete extent of the financial crisis will not be known until well after the writing of this paper, it is expected that the findings will be of an interim nature which, nevertheless, will find significant use in drawing perspectives on future research years after the crisis would have ended. References Aderholdt, J. and Rasmussen, R.H. (1996) “Using derivatives to hedge against the unexpected”, Healthcare Financial Management; Feb 1996 Andrews, E.L., De la Merced, M.J., and Walsh, M.W. (2008) "Fed’s $85 Billion Loan Rescues Insurer", New York Times. Retrieved on 17 September 2008, as seen in Wikipedia. Anson M.J.P., Fabozzi F.J., Choudhry M., Ren R.C. (2004), Credit Derivatives: Instruments, Applications and Pricing, John Wiley & Sons, New Jersey Bonfim, D. (2008), “Credit Risk Drivers: Evaluating the contribution of firm level information and macroeconomic dynamics”, Journal of Banking and Finance,29 May 2008 Bomfim A.N. (2005), Understanding Credit Derivatives and Related Instruments, Elsevier Inc., San Diego, California Brown, E. (2008) “Credit Default Swaps: Evolving Financial Meltdown and Derivative Disaster Du Jour”, Global Research, April 11, 2008 Brummer, A. (2008), “Where the Credit Crash Came From”, Management Today, May 2008, Haymarket Publishing Ltd., London Chance D.M. (2001) An Introduction to Derivatives and Risk Management, Harcourt College Publishers, Orlando, FL. Das S. (2005), Credit Derivatives: CDOs & Structured Credit Products, John Wiley & Sons, Singapore Datamonitor Plc, as seen in www.datamonitor.com. Retrieved on 19 December 2008. Haugen R.A. (1997) Modern Investment Theory, Prentice-Hall, Inc., New Jersey. Mishkin F.S. and Eakins S.G. (2003) Financial Markets and Institutions, Addison-Wesley, New York Philips, M. “The Monster that ate Wall Street: How credit default swaps—an insurance against bad loans—turned from a smart bet into a killer”, Newsweek Sept. 27, 2008. Reilly F.K. and Brown K.C. (2006) Investment Analysis and Portfolio Management, Thomson South-Western, Mason, OH Schὂnbucher P.J. (2003), Credit Derivatives Pricing Models: Models, Pricing and Implementation, John Wiley & Sons, New Jersey. Smith, D. “How to manipulate the markets.” Management Today Feb. 1995, Haymarket Publishing Ltd., London Steinherr A. (1998), Derivatives, The Wild Beast of Finance, John Wiley & Sons, West Sussex, England Westgaard, S. and Van der Wijst, N. (1999) “Default Probabilities in a Corporate Bank Portfolio”: A Logistical Model Approach”, European Journal of Operational Research, 29 November 1999 APPENDIX A – Survey Questionnaire Dear Respondent, Thank you for agreeing to answer this questionnaire. I am a student ­­­­­­­­­­­­pursuing a masters degree in (college/university). This survey will solicit your opinion on the current global financial crisis, as a part of my dissertation in Quantitative Finance. Rest assured that your responses will be kept confidential. Very truly yours, M.. Respondent Profile: Name (Optional):__________________________________ Age: ______ Gender: _______ Office, Country:_________________________________ Years with the Firm __________ Educational attainment: College degree __________________________________ Graduate course (current): _________________________ Graduate degree/s: _______________________________ Current position and brief job description: ________________________________________ __________________________________________________________________________ Please indicate which of the following activities you are professionally involved in: ____ Credit investigation ____ Fundamental analysis ____ Credit and loan policy formulation ____ Technical analysis ____ Credit securitization ____ Investment advisory ____ Credit derivatives trading ____ Investment management ____ Credit securities underwriting ____ Others ______________________ ____ Financial portfolio management ___________________________ In the following section, please tick off (√ or X mark) the appropriate box corresponding to how much you agree with the statement. The possible responses are: SA – Strongly agree A – Agree D – Disagree SD – Strongly disagree Read More
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