The role of quantitative financial model in the 2008 financial crisis

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  1. The role of quantitative financial model in the 2008 financial crisis

The 2008 financial crisis is a worldwide crisis in terms of banking and finance which caused one of the most global severe economic declines since the 1930s. The impact of 2008 financial crisis yielded $3.4 trillion losses across counties according to the 2007 -2010 report of International Monetary Fund (IMF). Influence of internal and external factors driving this financial crisis is a discussion for many authors, economic experts since 2008 until now. According to their explanation, there are many factors contributed to the $3.4trillion losses from 2007-2020, among of them, quantitative finance had placed an important role in making this financial crisis. This part of the essay pursues to identify either quantitative finance caused this crisis, or in making its worse than it might have been.

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By carrying on the theoretical development of mathematical (or quantitative) finance in the word, many authors have provided various point of view of this framework. According to Merton, Simons, and Wilkie (1994), quantitative finance is the method of transforming the issues from a real-life system into a conformable and controllable mathematical expression where logical consideration decides an insight and orientation for cracking a problem and affords people with a technique for a better developing system. These authors explained that mathematical model is applied globally in many fields such as in social science, in natural sciences, in finance and also in engineering. With a business view, Karatzas (1997) stated that the implementation of this method in finance delivers directions in terms of various impacts on types of financial market, each of which might implicate sophisticated numerical techniques. From a historical view, evaluating the role of quantitative methods in finance is a critical and practical argument of its positive and negative impact on banking and financial markets in the world. 1960s is the period which started modern finance, during this time; quantitative finance predicted other outstanding works rose such as development of the risk measuring models by various authors: Treynor, Sharpe, Lintner, Mossim, Markowitz in 1961, 1964, 1965, 1966, 1979 accordingly. Black-Scholes model (1973) was one of such measuring model presenting the mathematical finance during this time and was adopted by many financial institutions recently (Lyuu, 2002). The historical development of quantitative finance proves, hence, that this model places a huge role in yielding the innovative value of improving financial instruments. This is a basis financial instrument for making any decision of investments, cash-flows, securities and risk controls (Lyuu, 2002).

On the other hand, this quantitative model has not always shown positive impacts on financial market; it has also delivered negative impact on the financial sectors leading the huge financial crisis in 2008. According to Wilmott (2000), when financial mathematics becomes complex and touches higher levels and finance theory turns into sophisticated status, the increase of misuse and abuse will be enhanced. In 2008, the short of comprehension of financial instruments was proved by many loss cases of big organizations in the world such as BNB Paribas, JP Morgan Chase, City Group, Deutsche Bank, IKB Industriekredit-Bank, Lehman Brothers, Goldman Sachs, Lehman Brothers, Washington Mutual Bank….and other financial sectors, these organization gained huge lost and even bankrupted because of opposite effect of wrong calculation and the speculation on the direction of interest rates. Such given situation states that even if the quantitative finance supports the analysis of high levels in numerical methods for a business performance, it is really difficult to analyse the market for a longer period (Sullivan, 2011).

Given the current situation of the financial market, the better forecasting and understanding of every market movements is necessary in business decision-making process. However, to acquire a depth understanding of the market change is a challenge for mangers as there are huge amount of information needed to be investigated and justified. When growing variety of techniques, the failure of financial forecast might happen instinctively and lead to severe consequences. The 2008 financial crisis is a significant example for this discussion. Key contributors for this crisis were managers of the financial institutions in the worlds who applied quantitative financial model with inefficient calculation and practitioners who developed quantitative model of finance before the recession. According to Sullivan (2011), all issues arose from ineffective and exorbitant calculation of mathematics shows that quantitative finance still maintains business limitation although it offers a significant value in forecasting and the decision-making process. Sullivan also stated that the incapacity of capturing changes in undefined directions of current market was the key limitation of this quantitative model. As this result, quantitative finance technique might bring risks to organization that are strongly trust and rely on it. Hendry and Ericsson (2001) additionally stated that this sophisticated framework was likely difficult to understand, it may maintained inadequate analysis of the variables in the global energetic financial market, so this can cause hide dangerous issues for any applicant in the world.

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In summary, no-one can ignore the important role of quantitative finance in global business development and also the contribution of this model in making this financial crisis, especially in the 2008 financial crisis. By carrying on the historical development of quantitative financial model over many decades under the view of various famous authors in the world, people identify that this model is often tackled with the full collection of mathematical technology and is used in financial activities including cash flow predicting, market evaluation, risk management, product innovation, working capital expenditure forecasting, financial analysis and others. Applying this essential model supports organization yields the high-level mathematical modelling methods is a powerful way of predicting and decision-making in financial markets. On the other hands, there are various sources of information causing the failure of quantitative processes and leading to the global 2008 financial crisis. Although this quantitative model has each own limitations, the need for a deep understanding and looking at its significant role in driving global market growth is considerable. Any financial models or frameworks are established by human being, so there might hide risks which probably bring inaccurate or wrong outcomes, practitioners are key users who should closely rely on with their intuition and practical judgement. Proper implementation will yield mutual performance for not only organization but also the global business.

  1. Black-Scholes model and its role in global business performance

This second part of the essay mentions of Black-Scholes and its impact on global financial market. Black-Scholes is a quantitative model of financial calculation which is widely used in the world. Being established in 1973, this financial model was initially invented to support managers for calculating the best financial solution for their long term business development. This kind of quantitative financial method refers to the recommended price of option of four key quantities. Three of them can be measured straightly includes the price of assets based on it the option is secured, the risk-free interest rate and time. The fourth element of quantities is the volatility of the asset, volatility of asset is applied for statistically analyzing the market movement of price in a specific time. Black-Scholes presents not only the value of the option (the price at which it should be sold or bought) but also a reality of the current financial status of a company’ assets. This is an essential method representing the change rate of the price in the context of the rates at which other quantities changes significantly. The success of Black-Scholes supports all financial and banking sectors to enhance a host of related equations focused at various financial instruments. In the world reality, all mathematical models are mainly based on simplifications and assumptions. Whenever people provide valid assumptions, business and financial risks are mitigated. As global competition increases remarkably in recent decades, hence fluctuations of stock market steadily enhances to challenge any rival business units. For example in 1987, the global stock market had to face to a loss of more than 20% comparing to their real value, given this current situation, no assumption of business or economic experts can be justified. Financial sectors normally ignore the limitation of financial models; they applied the equation as a mathematical instrument to protect their companies out of market fluctuation and changes. So, Black-Scholes model doesn’t illustrate the reality of the world, it just provides a general calculation of the world assets’ value. The Black-Scholes equation mainly bases on mathematical physics, in which quantities are infinitely divisible, time flows uninterruptedly and variables move smoothly. This model is not appropriate and suitable to the real financial world where there always mismatches between traditional mathematical economics and reality.

References

Merton, R. C, Simons, R. VandWilkie, A. D (1994), “Influence of mathematical models in finance on practice: past, present and future”,Philosophical Transactions: Physical Sciences and Engineering347.1684: 451-463.

Karatzas, I. (1997), “Lectures on the mathematics of finance”, American Mathematical Society, USA

Sullivan, R. (2011), “Financial models useful but limited”,The Financial Times,03 April, available at <http://www.ft.com>, accessed on 20 Mar 2014

Felix Salmon (2009), Recipe for Disaster: The Formula That Killed Wall Street, available at<http://www.wired.com/techbiz/it/magazine/17-03/wp_quant?currentPage=all>, accessed on 20 Mar 2014

Lan Sterwart (2012), “The mathematical equation that caused the banks to crash”, available at <http://www.theguardian.com/science/2012/feb/12/black-scholes-equation-credit-crunch>, accessed on 21 Mar 2014

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