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Evaluating Bank Stock Trends for Bank Liquidity - Essay Example

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The essay "Evaluating Bank Stock Trends for Bank Liquidity" focuses on the critical analysis of the concept of bank liquidity and how it is measured in the context of international banking. The first part will involve a theoretical analysis of the concept…
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Evaluating Bank Stock Trends for Bank Liquidity
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PREDICTING BANK LIQUIDITY BY EVALUATING BANK STOCK TRENDS Contents Introduction 3 Bank Liquidity Risk 3 Measurement of Bank Liquidity Risk 4 Bank Liquidity Risks and Bank Stock Returns 5 Methodology 6 Findings 6 Conclusion 7 Bibliography 9 Introduction This paper examines the concept of bank liquidity and how it is measured in the context of international banking. The paper addresses this in two parts. The first part will involve a theoretical analysis of the concept. This will culminate in the evaluation of a realistic analysis of variables and historical data relating to banking liquidity in the era of the global financial crisis. Bank Liquidity Risk Liquidity risk in general refers to a situation whereby an asset cannot be traded quickly enough to make gains rather than a loss (Laycock, 2014). This refers to a situation whereby an organisation or business has immediate cash needs, although it has assets, its trading position is not good enough to honour all cash obligations (Machiraju, 2013). This is described as the risk of overcapitalisation and it occurs when an organisation holds a lot of assets, but lacks the ability to convert the assets into cash in the short-run. In the banking sector, the issue of liquidity risk occurs in a distinct and unique manner. One fundamental assumption of banking is that depositors are not going to withdraw all their money at once (Matz, 2011). Banks are however required to hold assets that are mainly liquid in nature and convert them to cash in a very short term (Matz, 2011). Therefore, in banking parlance, liquidity is defined as “the ability of an economic agent to exchange his existing wealth for goods and services or other assets without incurring damaging losses” (Castagna & Fede, 2013, p. 18). Liquidity risks include funding liquidity which refers to the risk of settling obligations with the central bank as it occurs. There is also the market liquidity risk which revolves around the ability of a bank to settle its obligations to stakeholders on the market. This is the “inability to realise assets due to inadequate market depth, or market disruption” (Adalsteinsson, 2014, p. 26). Measurement of Bank Liquidity Risk Bank liquidity risks can be measured both internally and externally. Internally, bank liquidity risks are defined by international conventions and practices that are placed on the authorities and directors of the bank. This is to be done through the utilisation of various formulas put forward by international entities like the Basel Conventions. Basel III proposed that bank liquidity risks can be evaluated by assessing: 1. The liquidity coverage ratio for short-term resilience and 2. The net stable funding ratio for longer time horizons (Szylar, 2013, p. 369) These are insider indices and they are often done through the utilisation of privileged information that allows banks to evaluate trends and processes in their activities and affairs. However, to the ordinary investor, there is likely to be the use of publicly accessible information that they will use to evaluate and analyse bank liquidity levels and processes. There are fundamentally, three different methods and approaches that can be used to guide and show the way and manner in which banks operate and manage their liquidity risks through the use of publicly granted information. They are: 1. Systematic Liquidity Risk Index; 2. Systematic Risk-Adjusted Liquidity Model; 3. Macro-Stress Testing Model (International Monetary Fund Staff, 2013) Systematic Liquidity Risk Index is done through the evaluation and analysis of several arbitrage relationships and the signals that come with them in order to check violations in relationships and identify the ranking and signs that prompt quick action. Systematic Risk-Adjusted Liquidity Model is based on a combination of various balance sheet and market data on option pricing situations and circumstances. Through this, systematic liquidity risks could be deduced. Finally, Macro-Stress Testing Model involves the evaluation of the impact of adverse macroeconomic financial situation in an economy to the situations of financial institutions. This gives a broad scope of signs that can be used to circumstantially deduce the level of liquidity risks in the financial statement. Bank Liquidity Risks and Bank Stock Returns “Empirical evidence indicates that aggregate liquidity conditions reflected by the SLRI affect the volatility in bank stock returns.” (International Monetary Fund Staff, 2013, p. 88). This implies that bank stock returns are somewhat influenced by the levels of liquidity changes that occur in the bank during a particular season or financial period. This shows that there are shifts and changes that could affect them. This relationship shows that the two can be used in some kind of predictive capacity to tell what is going on with each of them. In cases of low systematic liquidity, there is often an increase in the volatility of the bank’s returns of bank returns after other aggregate risk factors are controlled with bank-specific measures. This is because when investor uncertainty increases, tighter funding conditions creates an impact on banks’ earning capacities. There are other studies that show that bank equity is sensitive to the estimation of insurance premium that banks pay (Barwell, 2013) Other studies show that bank liquidity risks are strongly connected to increased levels of confidence that is put into the banks and their affairs. This is because the level of risks that are apparent in the macroeconomy gives the impetus for the increase or decrease in the levels of interests and desires to deposit money in a given economy (Carey & Stulz, 2013). This simply shows that there is a strong evidence that bank liquidity risks reduce when bank stock returns increase and vice versa. This is because the more money that is put into a bank will mean that the bank will have to react in relation to that. Where there is more investment into their stocks, it shows an increase in the amount of money they can withhold. In cases where they are receiving less, they are likely to be pulled out. Therefore, it can be logical to infer that there is a direct positive relationship between bank stock returns and bank liquidity risks. Therefore, this paper hypothesises that: 1. Bank Liquidity Risks increases when Bank Stock Returns Increases; 2. Back Stock Returns are the primary indicators of the level of Bank Liquidity Risks 3. People can rely on Bank Stock Returns to predict the level of Bank Liquidity Risk in a bank at any point in time. Methodology In order to test these hypotheses, it is important and vital for the study to analyse and review empirical data to assess whether this relationship really exists or not. To this end, the stock returns of a sample of banks in the developed world are examined in relation to the Amihud Index. This is to show a relationship between the two variables and provide a core interpretation of the relationship between the two variables. The sample includes a list of approximately 50 banks that are studied over a period between 2003 and 2011. This is aimed at providing an important set of variables that can be used to make predictions and conduct various forms of analyses. The fundamental relationship is examined by evaluating the relationship between stock returns and illiquidity. The paper therefore examines the stock returns of over 2000 entries of months of these banks and matches it against the Amihud Illiquidity Returns Index. This is to show the relationship that exists between the two variables. Findings The findings are presented in the form of a regression analysis that is presented in figure 1 below. Figure 1: Correlation between Stock Return and Amihud Index The Amihud Illiquidity Index examines the price impact measure that captures daily price response associated with one dollar of trading volume, hence, Illiquidity is: Average (Stock return on a day’s trading/Volume of a day’s trading) (Goyenko, et al., 2009) The figure above shows that there is a positive correlation between stock return and the Amihud Index. This is because there is a slight evidence that when the Amihud index increases for each period, stock prices also increases slightly. This indicates that the higher the return on stocks, the higher the liquidity risk. Conclusion The findings indicate that when bank liquidity risks rise and they increase, the bank’s stock returns also increases. This confirms our hypothesis and shows that there is a positive correlation between bank liquidity risks and bank stock return increases. However, there is no possibility of showing that bank stock returns are the primary indicators of the level of bank liquidity. This is because there are some factors that could cause the prices to change, like the return on equity, return on assets and the level of risks in the economy in general. Therefore, it is not possible to rely fully on bank stock returns as a means of telling the level of liquidity in a given bank’s transactions. In spite of this, it could also be stated that the correlation identified with the banks is not so strong because the regression shows that the trendline is not steep enough to be viewed as an appropriately strong relationship. Therefore, the third hypothesis is not very strong and it will not be right for an average investor to rely fully on the stock prices as a means of measuring bank illiquidity. Bibliography Adalsteinsson, G., 2014. The Liquidity Risk Management Guide: From Policy to Pitfalls. 3rd ed. Hoboken, NJ: John Wiley & Sons. Barwell, R., 2013. Macroprudential Policy: Taming the World Gyrations of Credit Flows. 3rd ed. London: Palgrave Macmillan. Carey, M. & Stulz, R. M., 2013. The Risks of Financial Institutions. 4th ed. Chicago, IL: University of Chicago Press. Castagna, A. & Fede, F., 2013. Measuring and Managing Liquidity Risk. 2nd ed. Hoboken, NJ: John Wiley & Sons. Goyenko, R., Holden, C. W. & Trzcinka, 2009. Do Liquidity Measures Measure Liquidity?. Journal of financial economics, 82(1), pp. 153-181. International Monetary Fund Staff, 2013. Global Financial Stability Report: Durable Financial Stability:. New York: IMF. Laycock, M., 2014. Risk Management At The Top: A Guide to Risk and its Governance in Financial Crisis. Hoboken, NJ: John Wiley & Sons. Machiraju, H. M., 2013. Modern Commercial Banking. Delhi: New Age Publishing. Matz, L., 2011. Liquidity Risk Measurement and Management. Indianapolis, IN: XB Press. Szylar, C., 2013. Handbook of Market Risk. 3rd ed. Hoboken, NJ: John Wiley & Sons. 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