Abstract

This research assesses the fundamental causes of the current financial crisis that hit the USA in 2008. A Close look at financial analysis specifies that theoretical modeling based on unrealistic anticipations led to serious problems in mispricing in the enormous unregulated market for credit default swaps that exploded upon catalytic rises in residential mortgage defaults. Latest academic research suggests solutions to the economic crisis that are appraised to be far less costly than bailing out investors who made poor decisions with respect to credit analysis.
Introduction
The financial crisis that occurred in 2008 is of such epic proportions that even astronomical amounts spent to address this issue have by far been not able to resolve it. This economic crisis is the worst to ever hit USA since the great depression and is utmost important to economists since this led to 2.6 million unemployed furthermore 3.4 trillion dollar were lost in real estate wealth and the stock market also lost 7.4 trillion according to the Federal Reserve. Besides the $700 billion bill approved by Congress, the Federal Reserve has bailed out institutions and markets by generating about $1.3 trillion in investments in various risky assets, also including loans to otherwise bankrupt organizations & collateralized debt obligations which were completely backed by subprime mortgages that were defaulting at rapid rates. Furthermore a $900 billion is in the process of being proposed in lending to big businesses (Aversa, 2008), leading the total amount to approximately $3 trillion in bailouts as of date, even without counting the massive sum of corporate debts which are guaranteed by the U.S. government in the last year. An analysis of the causes of this epic failure that has put the complete financial structure at danger is warranted in order to solve the problem and avoid such events in the future.

Root Cause of the Crisis: Mispricing in the enormous credit default swaps market any responsibility defaulting mortgages for the current economic crisis, but this huge tragedy is only an element and symptom of the deeper problem. The valuing of credit default swaps, whose main amount has been valued to be $55 trillion by the Securities and Exchange Commission and may actually go above $60 trillion (or over 4 times the openly traded corporate and mortgage U.S. debt they are assumed to insure), are totally unregulated, and have often been contracted over the phone without any paper work (Simon, 2008), is the most important fundamental subject from which all the other difficulties of the economic crisis emanate.
Credit default swaps are truly rather simple instruments in model, simply mandating that one party giving a periodic fee to another to assure the debts of some entity (such as a specified corporation) in contradiction of default for a exact quantity of time like5 years. They are effectively debt insurance strategies that are considered otherwise to avoid the guideline that normally is compulsory on insurance contracts. This unregulated market raised astronomically from $900 billion at the seizure of the millennium to above $50 trillion in 2008 after Congress passed a law exempting them from government betting laws in 2000 (PIA Connection, 2008).
Any speculation in a debt requires recompense not only for the time importance of money but also a superior for the credit risk of the debt. Compensation for the time worth of cash is generally offers by the debt encouraging, at a lowest, a yield equal to that of the rate existing on evasion free government safeties like U.S. Treasury bonds. The credit threat premium above that level must compensate investors for not only the predictable value of default losses but also for the organized threat relating to the debt, as well as for any implanted options (Murphy, 1988). In a credit default swap or bond insurance contract, there is no primary investment in the balance by the assuring party, and so only a credit threat premium is essential. This premium must contain both the default risk premium and the regular risk premium. Appropriate appraisal approaches for estimating those payments have long been famous (Callaghan and Murphy, 1998).
However, many specialists today apply pure mathematical theories to calculate credit risk and evaluation credit risk premiums to be obligatory (Glantz and Mun, and Vig 2008) have delivered a study of the very big forecasting errors that effect from the submission of such models that fitting “hard” historical data really well but mostly ignore individuals decision of “soft info.” The models of such ‘quants’ who have influenced a big impact over new banking” are, regarding to some specialists,New Scientist, 2008 and the concern has been disastrous for many institutions religiously following to them. Just for instance, one main insurer of debts via credit default swaps located “visionless faith in economic risk models” and their professional group ever who created huge income for the firm for a few years that later turned into devastating losses (Morgenson, 2008).

Officials’ predictions of serious difficulties and “horror stories” years in development of today’s economic and financial crisis were mostly ignored because of successful lobbying by the very financial organizations that are today either ruined or in the process of being rescued with government financing (Associated Press, 2008). For example, the failures of the two federal organizations often labeled Fannie Mae and Freddie Mac were headed in 2005 by a effective $2 million promotion by Freddie Mac to lobby Assembly from limiting their own funds in higher risk mortgages (Yost, 2008). These same organizations, banks, and other institutions provided assurances their loaning performs (including those enabling lends without acceptable certification) were “safe” based on assessments of past data (Associated Press, 2008).
Some stockholders in debt safeties look only at the credit rankings provided by a few rating agencies such as Moody’s and Standard & Poor’s (S&P), which themselves
Evaluate credit largely using only measured models. Those representations, which use info to discover past relations between debt defaults and a few variables, as in the influential Altman (1968) research, can ignore significant reasons and possibilities (Woellert and Kopecki, 2008). Whereas some have recommended that the models need to be developed (NewScientist, 2008b), purely statistical models can’t incorporate all possible features that are related to an assessment. In addition to this important issue statistical models are matter to the complications of false correlations between variables that are overstated as the number of variables is improved, so that efforts to integrate more relevant variables may only increase other modeling errors.

Perhaps as a result, standing mathematical credit risk models have “a tendency to undervalue the likelihood of unexpected great occasions” that are mainly significant in the credit markets where the tail of a delivery is key in predicting the defaults that normally have a low probability of occurrence (Murphy, 2000). The mathematical models normally fail to study inter-related methodical threats (Jameson,2008), and they tend to make unrealistic expectations such as bazaars always being in balance (NewScientist, 2008a). Despite their “poor risk modeling” in reality (Jameson, 2008), the statistical exactness of the models in expecting backward into the past using important data produced in the planned modelers such as communication in their illustrations which was going around in the actual world.
It is uncertain whether credit analysis can ever be conducted without human judgment. Human judgment can incorporate a huge number of variables that are quickly processed using simple but effective procedures that are subconsciously developed (Gigenrenzer, 2007). It can therefore help to mostly avoid the errors of purely mathematical models that are built on unrealistic assumptions, that take into consideration only a subsection of all the related variables, and that may be influenced by past spurious relationships which may not hold in future situations.
Conclusion
In the start of 2009, the economic damage from the financial crisis was still at a large scale. This took some time before anyone could understand the exact real value of the “toxic assets” that destroyed our banking system. Furthermore, personal credit card debt bubble had yet to take a hit. When it will, many economists predict that the downward spiral could possibly re-ignite; sending unemployment numbers to almost double to what it was and making the stock market go below 6,000.
Also there was this uncertainty whether the government’s strategy to rescue the financial system would work. Simon Johnson and Andrew Lo were promoting various measures that they thought would solve this current crisis and likely make the next disaster a little less severe. Whether, if and how would the government apply their recommendations was ambiguous.
Besides this financial crisis that almost demolished financial system of USA and most places in the world would likely happen again in the near future, Lo noted that the entire financial industry was in a state of flux. For young generation of people opting finance, the industry held a lot of promise:
The way I look is this is an incredible opportunity for those who want to opt for finance. Periods of crisis breed new opportunity for younger generation to capitalize on. According to me there will be many prospects in the coming 5-10 years creating new financial technologies to help us evade this level of crisis. The industry will be never what is used to be. Compensation will not be the same. There has to be a paradigm shift in how we reflect about different financial markets, considering from a financial technology (IT) point of view as well as from the human side.

References
E. Altman. “Financial Ratios, Discriminant Analysis and the Prediction of Corporate
Bankruptcy.” Journal of Finance 23 (1968), 589-609.
Associated Press. “Bush Administration Ignored Clear Warnings.” http://www.msnbc.msn.com/id/28001417#storyContinued J. Aversa. (2008, October 7). “Fed Eyes Plan to Fund Short-Term Business Loans.” Associated Press
Boni, L., 2006. Strategic Delivery Failures in U.S. Equity Markets. Journal of Financial
Markets 9, 1-26.
M. Buchanan. (2008, July 19) “Crazy Money. New Scientist, 32-35.
J. Burns. (2008.October 23), “Former Ratings-Firm Officials Blame Conflicts for Rosy Views. Wall StreetJournal, A4.
J. Callaghan and A. Murphy. (1998), An Empirical Test of a Stochastic Cash Flow Theory of Evaluating Credit. Advances in Financial Planning and Forecasting 31-51.
D. Collins and C. McMahon. (2008.November),Great Bailout of 2008, What’s Next Futures 28-36.
F. Duffee. (1999), Estimating the Price of Default Risk. Review of Financial Studies 12
197-226.
E. Elton, M. Gruber, D. Agrawal, and C. Mann. (2008.November), Explaining the Rate Spread on Corporate Bonds. Journal of Finance 56 (2001), 247-277. G. Favel. “Sold Short. Futures 32.
G. Gigerenzer. (2007) Gut Feelings, the Intelligence of the Unconscious. Viking. New York.
M. Glantz and J. Mun. (2008).The Banker’s Handbook on Credit Risk. Elsevier: Burlington.
B. Jameson. (September 27, 2008).The Blunders that Led to Catastrophe. NewScientist 8-9.
C. Jones and O. Lamont. (2002).Short-sales Constraints and Stock Returns. Journal of Financial Economics 66, 207-239.
P. Koh. (2005.April 1).Stung by the German Connection. Euromoney 1.
R. Merton. (1974).On the Pricing of Corporate Debt. A Further Note. Journal of Finance 29, 449-470.
G. Morgenson. (2008.September 28,).Behind Insurer’s Crisis. Blind Eye to a Web of Risk. New York Times.
C. Morris. (2008.October 14). Fed's $1.6 Trillon Bet. The $700-Billion Wall Street Bailout Was Only theHalf of It. Washington Independent.
A. Moses and S. Harrington. (2008.October 23).Company Bond Risk Surges on Argentina Default Concerns, Bloomberg.
A. Murphy. (1988).A Discounted Cash-Flow Model of Fixed-Income Securities Subject to Multiple Calls. Southern Economic Journal 55, 21-36.
A. Murphy. (2000). Scientific Investment Analysis. Quorum Books,Westport.
A. Murphy, J. Callaghan, and M. Parkash. (2005.September 27).Shorting Down Value.” Presented at the 2005Southern Finance Association (SFA) conference.
A. Murphy.( 2008.September 27).An Analysis of SAM Pricing in the UK.” Presented at the 2007 European
U. Rajun, A. Serun, and V. Vig.( 2008.October 15).The Failure of Models that Predict Default. Distance, Incentives, and Default.” Chicago GSB Research Paper No. 08-19.
R. Shiller. (2005.Summer), Homes are a Risky Long-Term Investment. TIAA-CREF
19-22.
E. Simon. (2008.October 26).Meltdown 101: What are Credit Default Swaps? Kansas City Star .
Weiss, G. (1997.December 15).The Mob is Busier than the Feds Think.Business Week
130.
L. Woellert and D. Kopecki. (2008.October 22).Moody’s, S&P Employees Doubted Ratings, E-Mails Say.” Bloomberg online http://www.bloomberg.com
/apps/news?pid=20601087&sid=a2EMlP5s7iM0&refer=home
Yost. (2008.October 20). AP IMPACT: Mortgage Firm Arranged Stealth Impact.” Associated Press.
A. Zibel. (2008.August 18).Liar Loans Threaten to Prolong the Crisis. Huffington Post