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How to Measure Bank Funding Liquidity Risk - Essay Example

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The paper "How to Measure Bank Funding Liquidity Risk?" will begin with the statement that banks over the years have been faced with crises emanating from various factors. A major player that has historically been associated with these crises is the funding liquidity risk…
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How to Measure Bank Funding Liquidity Risk
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? International Banking How to measure bank funding liquidity risk and market liquidity risk Banks over the years have been faced with crises emanating from various factors. A major player that has historically been associated with these crises is the funding liquidity risk. These are situations where a bank may not be in a position to meet its obligations with urgency or immediacy. This kind of risk will in most cases arise when revenues are not synchronised. It is important that the bank liquidity risk be measured in order to avoid crises in the future. Measuring bank liquidity risk incorporates the comparison of accumulated expected cash shortfalls for a given period of time with the stock available for funding the cash sources. In accounting, the stock or the asset available in an organization should always be sufficient to fund the financial sources. To measure this risk, the accountant is required to assign the anticipated cash flows to periods in the future that have financial products with unpredictable cash flow timings (Musakwa, 2013). It is important to note that there is no agreed criterion that can be used to assign the cash flows. In other words, there is no common consensus on how to carry out the procedures. The variations in measuring funding liquidity risk are normally caused by the considerations of solvency, immediacy, as well as the cost of obtaining liquidity. First, solvency can only be applied in firms that are solvent. It can be defined in terms of funding liquidity risk as the capability of a firm that is solvent to make the payments agreed upon in a timely manner. It should be noted that not only solvent banks that are liquid (Musakwa, 2013). At times, even insolvent banks may be liquid and this makes it difficult to use solvent as the main base for measuring banks liquidity risk. Further, a solvent bank can at times be illiquid. Insolvent banks may for instance be liquid in the event of information asymmetry. Such a situation may arise where the bank is fully aware of its solvency status but the public has no clue regarding the same. The distinction between solvency and funding liquidity risk is easy especially in the events of crises capped with information asymmetry. But it should be noted that solvency is normally covered by capital while ion the other hand funding liquidity risk is covered by cash inflows (Ruozi & Ferrari, 2012). Cost of obtaining liquidity is also likely to cause variations in bank liquidity risk. In most cases, funding is obtained with the main objective of covering obligations (Matz & Neu, 2007). However, it has to be obtained at an additional cost. The additional cost happens to be the major concern of accountants. In fact, some definitions of funding liquidity risk are based on this cost. For instance, the term funding liquidity risk could be defined as “the risk that a financial firm, though solvent, either does not have enough financial resources to allow it to meet its obligations as they fall due or can obtain such funding only at excessive cost” (Musakwa, 2013). This definition describes the cost of liquidity in in subjective terms. The defect of the definition is that the costs differ from market to market as well as across various banks. Under this concept, the bank liquidity risk is measured basing in the additional cost for obtaining the funds (Davis, 2004). Finally, the immediacy is an important aspect of funding liquidity risk. It defines the speed with which a bank can be in apposition to meet its obligations. In measuring funding liquidity under this concept, the time frame within which the bank is likely to become unable to meet its obligations is estimated (Hlatshwayo, et al. 2013). As mentioned earlier, known regarding the distribution of run off profile in most financial products for banks. However, there is an increased need for establishing a reliable method of measuring bank liquidity risk so as to avoid bank crises. In essence, the measure of bank liquidity risk will normally be done by carrying out a simulated distribution of the total liquidity excess which is found by using the Independent Component Analysis. The exercise focuses on the surplus of liquid assets in relation to due payments. The funding liquid risk is the expressed as the difference between the banks level of critical value and the aggregate liquidity surplus (Andrievskaya, 2012). The ease by which an asset can be traded with in the market can be referred to by the term market liquidity. Market liquidity risk is the term that refers to the extent to which it could be difficult to trade assets fast enough so as to avoid a loss. In the case of an organization, it is the ease with which it could get sufficient to pay its dues or to make any other necessary payments. Quantifying market risk just like measuring funding liquidity risk is not an easy task. It has been an issue of major concern to most financial institutions. According to Sebastian and Christoph (2009), the reliable method with which liquidity risk should be treated is still undergoing development. Marketing liquidity is a very essential factor in the management of risk for any business organization. Every organization wants to make the best out of any sale. The basic objective of an organization is to maximize profits. Therefore, no organization would want to sell an asset at a loss. It is important that it measures the market liquidity risk so as to establish reliably when it is appropriate to make a sale so as to avoid losses. It is for this reason that liquidity has been termed as a continuous problem for most financial institutions. A number of models have been developed to measure the market liquidity risk. One of the models is the Systemic Risk-adjusted Liquidity (SRL). This is the major approach/model. It combines the available market information with option pricing (Cornelia, Sebastian and Christoph, 2009; Jobst, 2013). It also focuses on the data available in the balance sheet so as to establish a probabilistic estimation of the frequency of the various business entities that are experiencing liquidity scenarios. The other model that can be used to measure market liquidity risk is the transaction regression model. Under this model, the liquidity risk is measured basing in the regression of past market conditions. The future market condition will be determined by the risk factors in the past and the impact that liquidity has on trading (Berkowitz, 2000). The interactions of bank funding liquidity and market liquidity based on the dataset Bank funding liquidity and the market liquidity are two issues that have to go hand in hand. They have a very close relation in that the influence of one affects the other in some way. For instance, it is argued that market liquidity risk is common in debt markets. These are markets such as the binds and security markets. Banks are increasingly known to use market securities as well as the end users who gets funding from the banks. If the bank has an obligation to pay a certain debt, the situation in the market may affect its ability to pay the obligation with urgency. It may have acquired funding from another institution in order to finance market securities purchase. Depending on the market situation, the bank will want to sell the securities at a time when it will be able to make maximum possible profit. This will also facilitate its ability to pay its obligation with urgency since it will have generated sufficient revenues. If the price for securities is on the decline, the bank should sell them as fast as possible in order to avoid losses. However, there are circumstances when the bank is not able to sell the securities fast enough in order to avoid the losses. In such a situation, the funding liquidity risk increases since it will be difficult for the bank to pay its obligations with urgency due to lack of sufficient funds (Jobst, 2013). From the given data set for instance, it can be observed that the funding liquidity risk represented by the initials cds and the market liquidity risk represented by amihud are related but they vary from country to country. The graph provided for the dataset indicates that the relation between the two variables is not linear. However, it is easy to predict the market conditions in the future using the figures. But it should be noted that due to the fact that the relation between the two is not linear, and that it is not perfectly constant, the prediction deduced from the graph can only be a mere estimation based on the trends on the graph. Below is the graph and the discussion follows below. From the figures given and from the graph, the market conditions are also influenced by the time. For instance, in the year 2002, both the funding liquidity risk and the market liquidity risk were on the decrease at the beginning of the year 2002, the funding liquidity risk was 63.25 and at the end of the same year it had decreased to 53.75. The average funding liquidity risk for the year 2002 was 117.8021 and the average market liquidity ration was 69.31375. Towards the end of the year 2003 and all the way to the year 2006, the market liquidity risk started to increase, while on the other hand, the funding liquidity risk was decreasing during the same time. In 2003, the funding liquidity risk averaged at 82. 98983 while the market liquidity risk was at 42.31019. In 2004, the funding liquidity risk dropped to 33.64902 while the market liquidity risk increased to 67.12. In the year 2005, the average funding liquidity risk further decreased to 24.93295 while the market liquidity risk increased to 153.6601. In the year 2006, funding liquidity risk continued to decrease to 17.01287 while the market liquidity risk further increased to 174.7462. The funding liquidity risk started to increase in the year 2006. It actually increased at a relatively higher rate up to the year 2009 when it slightly dropped before increasing again at a steadily high rate in 2010. In the years 2006, 2007, 2008, 2009 and 2010, it averaged at 17.01287, 34.80611, 186.1697, 248.3099 and 243.733 respectively. The market liquidity risk on the other hand is decreasing starting the year 2006. The rate of decreasing is however, relatively low in 2006, it increases in 2007 up to 2008 when it starts to increase again. The increase continues to the year 2010 and then it decreases again. The average in the years 2006, 2007, 2008, 2009 and 2010 was at 174.7462, 169.836, 124.8108, 161.0404 and 188.6012 respectively. In 2011, the funding liquidity risk continues to increase averaging 518.2993 while the market liquidity risk continues to decrease averaging at 150.4352. It can be observed from the movement of this graph that despite the fact that it may be predictable, it is not easy to tell what will happen over a long period of time. In other words, it can only be predictable in the short run. This is actually relevant given the fact that the market environment is highly uncertain. Managers have to operate in an environment that is highly uncertain and hence face a lot of difficulty in making decisions. Another interaction that is observable from the graph is that when the funding liquidity risk is high, the market liquidity risk on the other hand is low and when the market liquidity risk is high, the funding liquidity risk is low. The two are rarely heading the same direction. For instance, starting the year 2004, the market liquidity risk is increasing while at the same time the funding liquidity risk was decreasing. In the year 2007, the market liquidity risk starts decreasing while the funding liquidity risk starts increasing. The two intersect at a point during the year 2008. At this point, the funding liquidity risk equals the market liquidity risk. It is at this point when the bank is able to pay its obligations with immediacy while at the same time it can be able to sell an asset with immediacy to avoid huge losses and maximize its revenue. The market liquidity risk and the funding liquidity risk may also vary from country to country. For instance, in the European countries, the market liquidity risk is relatively low as compared to the United States. However, in Singapore, the market liquidity risk is relatively higher than the United States. In the years 2010 and 2011, Germany is an exceptional in Europe with a high market liquidity risk. The funding liquidity risk however does not vary so much in almost all the countries. Therefore, from this dataset, it can be deduced that the interaction between the market liquidity risk and the funding liquidity risk varies with time and location and that it is not easy to predict precisely. This could be due to the variations in the models used to measure them. As it has been mentioned earlier, there is no universally accepted model for measuring the two variables and this could also be another cause of the variations. Reference List Andrievskaya, I. 2012, Measuring systemic funding liquidity risk in the Russian banking system, BOFIT Discusiion Paper, Accessed online from on December 9, 2013 Berkowitz, J.2000, Incorporating Liquidity Risk Into Value-at-Risk Models, Working paper, University of California, Irvine Cornelia E., Sebastian, S. and Christoph, K. 2009, Measuring Market Liquidity Risk - Which Model Works Best? CEFS Working Paper Series 2009 No. 1, Accessed online from on December 9, 2013 Davis P. E. 2004, Market Liquidity Risk, The Competitiveness of Financial Institutions and Centres in Europe Financial and Monetary Policy Studies Volume 28, 1994, pp 381-402 Hlatshwayo, L. N. P., Petersen, M. A. Mukuddem-Petersen, J. and Meniago C. 2013, Basel III Liquidity Risk Measures and Bank Failure, Discrete Dynamics in Nature and Society, Volume 2013, Article ID 172648, 19 pages Jobst, A. 2013, Measuring systemic risk-adjusted liquidity (SRL): A model approach,. Washington, D.C: International Monetary Fund. Matz, L. M., & Neu, P. 2007, Liquidity risk measurement and management: A practitioner's guide to global best practices. Singapore: J. Wiley. Musakwa, F. T. 2013, Measuring Bank Funding Liquidity Risk. Accessed online from < http://www.actuaries.org/lyon2013/papers/AFIR_Musakwa.pdf> on December 9, 2013 Ruozi, R., & Ferrari, P. 2012, Liquidity risk management in banks: Economic and regulatory issues. Berlin: Springer. Sebastian S. and Christoph, K. 2009, Market Liquidity Risk - An Overview, CEFS Working Paper Series 2009 No. 4, Accessed online from on December 9, 2013 Read More
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