The Measurement of Bank Liquidity Risk - Essay Example

How to measure bank liquidity risk using publicly available information? The measurement of bank liquidity risk using publicly available information can take various forms, based on the nature of the information that is available, and the available skills for applying the methods. This is because, although all methods may apply publicly available information to assess the bank liquidity risk, they vary in the nature of their complexity (IMF, 83). The first method that can be applied to measure the liquidity risk of banks by applying the available public information is the Systematic Liquidity Risk Index (SLRI), which is a market oriented measure of the liquidity risks of the banks (IMF, 83). The Systematic Liquidity Risk Index applies the information related to the daily market observation of the violations that might occur in the arbitrage relationship of the cash flows and the fundamentals of the bank that are traded at different prices (IMF, 83). It is the relationship between the arbitrage relationship of the cash flows and the trading of the fundamentals of the bank in the market that is exploited to indicate the lack of market and funding liquidity (Corcoran, 30). This market-based method of measuring the liquidity risks of the banks by using the available public data applies the principle that; under the normal market conditions, the portfolios, financial tools or securities that produce the same cash flow should fundamentally have no difference in their prices, unless a slight difference that might be attributed to the differences in the transactional costs for the different trading fundamentals (IMF, 84). Therefore, the it is expected that the securities, financial tools and the portfolios belonging to a bank that produces the same cash flow like other fundamentals of different organizations ought to trade at the same price, only differing in the issues of taxes or other trading micro features, which can only make a slight difference in the prices of the traded fundamentals. Therefore, to the extent that there is a large difference between the prices of the securities and the portfolios of the bank and those of other organizations, then it is an indication of a bank liquidity risk (Bansal, 113). Thus, to the extent that there is a mismatch in the pricing of similar assets in the market, with the bank’s assets being lowly priced than the other assets, then the investors are applying the arbitrate strategies to short sell the overpriced assets and then use the revenues generated to buy more of the underpriced assets (Fernandez and Pastor, 84). This then allows them to make a risk free gain by violating the law, but quickly reverting to the normal market conditions before the violation can be realized by the law. Thus, it is this pricing mismatch of similar assets that is applied to indicate the extent of the liquidity risk that a bank holds (Amihud, Mendelson, and Pedersen, 140). A Systematic Liquid-Adjusted Model (SRL) is yet another method of measuring the liquidity risks of banks using the available public information (IMF, 89). This method applies the marketing data, and then combines it with the option pricing and the balance sheet data in order to measure the liquidity risk that a banking institution might have (IMF, 89). The combination of the three set of data is then applied towards estimating the contribution of a banking institution to the systematic liquidity risk. Nevertheless, the application of the Systematic Liquid-Adjusted Model and its accuracy in determining the liquidity risk of a banking institution is largely dependent on the asset structure, as well as the structure of the funding of the institution (Severo, 7). This method of measuring risk applies an innovative method of assessing the liquidity position of a financial institution, through applying the contingent claims analysis as the prime determinant of the liquidity risk that a financial institution holds (IMF, 89). Therefore, through the computation of the financial data as provide by the balance sheet, the Systematic Liquid-Adjusted Model is able to establish the contingent claims that a financial institution holds, which then translates to the determination of both the solvency and the credit risk held by the banking institution. The balance sheet data regarding the assets held by a banking institution is compared to the debts and other contingent claims that the bank holds, in order to determine whether the assets of the bank are capable of funding all the claims and debts held by the banking institution. The results obtained are then adjusted for the forward looking probabilities, such that the adjusted-risk computation then helps to determine the probability that the banking institution is likely to experience a liquidity shortfall in the future (Vázquez and Pablo Federico, 9). Further, the adjusted-risk computation probability also helps in calculating the associated loss that might amount from the occurrence of the liquidity shortfall caused by the higher claims and debts when compared to the asset structure of the bank. The Stress-testing Framework for Systematic Risks is yet the other method that applies the available public information related to a banking institution, in order to measure the liquidity risk associated with the bank (IMF, 93). This method of measuring bank liquidity risks assumes that the rising liquidity risks is caused by the uncertainty over the banking institution’s asset value in addition to the increasing solvency of the bank assets. Thus, this method looks at the banks cash flows in relation to its asset valuation, to determine the likely disparity, which is then applied to determine the probability of the default risk by the bank on its debt and other claims obligations (Jobst, 18). On the event that the assets of the bank are undervalued, the funding costs, the profitability and the consequent solvency of the bank are lowered (Wu, 16). It is the perceived lower profitability and solvency of the banks that causes the investors to hoard liquidity towards the bank, which then lowers the banks liquidity position and thus serves to increase the liquidity risk of the bank (IMF, 93). Thus, the Stress-testing Framework for Systematic Risks considers the bank’s asset valuation against its financial obligations, to determine the extent to which the bank holds some systematic liquidity shortfalls (Homburger, 254). Works Cited Amihud, Yakov, Haim Mendelson, and Lasse H. Pedersen. Market Liquidity: Asset Pricing, Risk, and Crises. , 2013. Print. Bansal, Manish. Derivatives and Financial Innovations. New Delhi: Tata McGraw-Hill Pub. Co, 2007. Print. Corcoran, Clive M. Systemic Liquidity Risk and Bipolar Markets: Wealth Management in Todays Macro Risk On/risk Off Financial Environment. Hoboken: Wiley, 2013. Internet resource. Fernandez, De G. R. J, and Monsalvez J. Pastor. Modern Bank Behaviour. Basingstoke: Palgrave Macmillan, 2012. Print. Homburger, René B. Banking Regulation: Jurisdictional Comparisons. London: European Lawyer, 2012. Print. International Monetary Fund (IMF). Global Financial Stability Report: Durable Financial Stability: Getting There from Here, April 2011. Washington: International Monetary Fund, 2011. 83-96. Print. Jobst, Andreas. Measuring Systemic Risk-Adjusted Liquidity (srl): A Model Approach. Washington, D.C: International Monetary Fund, 2013. Print. Severo, Tiago. Measuring Systemic Liquidity Risk and the Cost of Liquidity Insurance. Washington, D.C.: International Monetary Fund, 2012. Print. Vázquez, Francisco F, and Pablo Federico. Bank Funding Structures and Risk: Evidence from the Global Financial Crisis. Washington, D.C.: International Monetary Fund, 2012. Print. Wu, Desheng D. Quantitative Financial Risk Management. Berlin: Springer, 2011. Print. Read More