The Usefulness of Liquidity Credit and Market Risk Finance Essay

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This essay explores empirically the usefulness of liquidity risk, credit risk and market risk as risk measures indicators to explain whether German banks riskier than European competitors or not. The sample of reference entities consist of all German banks and eleven European banks and the observation cover the period from1994 to 2008. Using a unique dataset available in Bangor university blackboard website that relates to various characteristics of the individual banks operating in a twelve European Union countries, after dividing the period into three terms the first one started from 1994 to 1998 (before the establishing the European Union), the second started from 1999 to 2005 (after joining to European Union and before the last financial crisis) and the third term started from 2006 till 2008(during that crisis). By analysing the t-test hypothesis of three risk mean sources; liquidity risk, credit risk and market risk, we gain important insights into the German banks risk compared with European banks. We compare the risk using three measures for liquidity, credit and the market risk. We find evidence that the liquidity risk for German banks during all terms was higher than European competitors and the credit risk was lower in German banks except in the first term, while in the market risk they are in lower exposure through all terms. However, German banks rely on loan loss provision as the source of liquidity to face the demand of withdrawal of their customers.

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Germany is one of a large diversified modern economy based on gross domestic product (GDP) and is the largest country in the European Union (EU). But currently the German economy start to decline significantly in the fourth quarter of 2008 and recovery is not expected until late 2011. Germany is a member of the European Union and one of the original eleven countries to adopt the euro as its currency in 1999. In addition to the easing of monetary policy being done with the cutting of interest rates by the European Central Bank, the German government is using expansionary fiscal policy to aid the economy. The government has passed two stimulus packages, one in the fourth quarter of 2008 and one in the first quarter of 2009. Available on AMB Country Risk Report 13Augest (2009). Germany has the second largest banking sector by size in Europe. Germany banking sector focus on long-term lending and accounts for just under one-third of all banks in the euro area has largest number of branches and is the largest employers of any European banking sectors Düllmann – Sosinska (2007). A securities market may play a role to provide liquidity to investors whose risk and costs are therefore reduced. Furthermore, by vying for investors’ capital, stock markets increase competition for banks, therefore, stock markets and banks may also complement each other. On the other hand, unlike European economy, German economy depend on banks more than stock market because the bank provide long-term loans and prefer to keep higher ratio of loan loss provision instead using securitization. In this essay, we consider that a credit risk, liquidity risk and securities market may play important role to assistance the banks risk which market represented by the market risk faces possible liquidity shortages. We examine which of these two institutions best prevents a bank’s liquidity shortages while allowing the optimal allocation of the bank’s resources. Indeed, although the bank is able to avoid liquidity shortages by keeping a high proportion of cash (loan loss provision) in its balance sheet and in the same time this reserve use to avoid credit risk. In addition the bank gain a profit from lending money to investors which are affected by credit risk, therefore credit risk drive to liquidity risk and market risk, then each one of these risk lead to others risk. Then by applying mean average of these type of risks to explain Germany banks riskier than non-Germany banks Franck, Krausz, available online 19 January (2005).


The following literatures focus on three important elements which represent the performance and risk taken by German banks as a unique banks structure. A study has done by Hayden at al (2007) investigated the performance of 983 German banks from 1996 to 2002. The study tried to find out the relation between the portfolio diversification on the bank and the bank performance across different countries, rejoins, and industries. Value- at risk based risk variable has calculated. The regression model has set to answer three questions which are: first, Does diversification decreases or increases the bank profitability? Second, are there any changes in the relationship accrue after correcting for risk. Does the changes in diversification and return dependent on the risk level? The study found weak evidence between diversification and the bank profitability. They find almost banks in the sample with a higher diversification have a lower return. Kakes at al (2002) analyses the effect of monetary shocks on German lending banks channel. They investigate six different banking groups by following across-sector approach. The study found that, smaller banks hold enough liquid of asset protects those small banks from monetary shocks. Also they investigate the response of banks lending after a monetary shocks, and they found that: the bank lending is vary across banking sectors. The big banks tend to be able to protect their loans portfolio against this monetary shock because it takes high proportion of loan loss provision. Whereas, small banks lending have a sharp decline. Another study conducted by Beck at al (2009), the study investigated the bank ownership and stability: Evidence from German banks. Banks ownership in Germany have three different types which are government-owned savings banks, cooperative banks and privately- owned banks. The sample was taken from the period 1995 to 2007. Using Z- score and NPL-score and distress probability, they conclude that with privately-owned banks in Germany are more risky than cooperative and savings, but also higher returns. They found some evidence for the too-big-to-fail phenomenon, privately-owned banks decreasing their capital buffer as they grow larger. Overall, the findings gave important insights for supervisors and regulators in charge of banks of different ownership types, especially of applying different stability indexes, as they might give different results, depending on if they focus on, different moments of the distribution or particular risks, example lending risks.


The sample of reference entities consist of individual banks and the observation cover the period from1994 to 2008 for a twelve European countries which are Germany, Italy, France, Greece, Netherlands, Luxembourg, Finland, Belgium, Austria, Portugal, Ireland, and Spain. The data is available from Bangor university blackboard website. In our study we used three variables from the available data to measure the risk for German banks (about 2640 banks) and European banks (about 2515 banks).


The purpose here is to measure three types of risks; liquidity risk, credit risk and market risk. In order to measure the liquidity risk we use the liquid variable which represents a ratio of liquid assets to total assets, this ratio is useful to determine the size of liquid assets to total asset which can be converted into cash quickly, and it reflects the liquidity position of the bank. On the other hand we used the llpl variable which represents the loan loss provision to total loans ratio that captures the credit risk of the banks, it is helpful because it reflects the bank’s ability to recover its default loans (Hlawatsch & Ostrowski 2009).while in measuring market risk we used the ratio: { 1-(equity + deposits)/total assets} as the third variable, it represents the market proportion in financing assets in the bank (i.e. if the bank want to increase finance we use three type of sources equity, deposit and market by borrowing from other banks) , it is an indirect measure but still it gives us a clear idea about the effect of market risk in the bank . When dealing with the data we chose to divide the period from 1994 to 2008 into three intervals, this segmentation meant to take into account tow major actions that may result in having effects on the European banks; the first action is the establishment of the European Union in 1999 and the second is the last financial crisis that start from united states and hit all over the world. Therefore we had an interval from 1994 to 1998, followed by an interval from 1999 to 2005 and from 2006 to 2008. We investigated all data under our chosen variables. After that we calculate the average values of our variables for every bank during the specified period and compare the mean of the averages between German banks and European banks (Non German) for every period. We preferred to calculate the average value for bank per se in sake of getting more smooth distribution for the tow populations. Then we exclude outliers using the simple classical approach to screen them by using the Standard Deviation method, it is defined as: 2 SD Method: x A± 2 SD; the observations outside these intervals are considered as an outliers (Songwon Seo 2006). And then we run unpaired T-test (one tail) to check the equivalence of the means for the two populations (German banks and non German banks) for every variable in the three determined period, we assumed that both populations will approximately follow the normal distribution for the reason of large size of our sample, and we got unequal variances between populations for all variables in the periods so we operate T-test with unpaired and unequal conditions in order to get a valid test (Stata 10 A produces Satterthwaite’s or Welch’s approximation for the degree of freedom). As well as the two populations are independent.

Results and Discussions:

Based on Stata result, first we describe the data (see table 1) and then we run T-test for independent samples with unequal variances (we test the variances equivalence using F-test). For all tests we run we have the null hypothesis that says both populations are equal in the mean of the specified measure of the risk. First we test the credit risk using llpl ratio during the three intervals, in the first period we reject the null hypothesis and accept the alternative hypothesis that means the mean average of loan loss provision to total assets for German banks is significantly less than the mean of European banks(see table2), and also in the following two periods we reject the null hypothesis and accept the alternative hypothesis that says the mean of loan loss provision for German banks is significantly greater than European banks(see tables 4&5). Second we test the liquidity risk using liquid ratio during the same periods, for the three tests we reject the null hypothesis and accept the alternative hypothesis that declares the mean of liquid assets to total assets in German banks is significantly less than the mean of European banks(see tables 5&6&7). Finally we test the market risk using the proportion of the market (interbank market) in the total assets and for three tests we reject the null hypothesis and accept the alternative that provide the mean of market proportion in German banks assets is significantly less than the mean of European banks (see tables 8&9&10). The mean values of three risk measures across the three periods are stated in the following table (values are in percentages):

German banks:


Before the European integration After the European integration an before last financial crisis During the last financial crisis

Risk measure

Loan loss provision to total loans .8403876 .7747105 1.005803 Liquid assets to total assets 14.90594 15.40948 17.46113 Market proportion in the total assets . .0756065 .0697405 .0690318

For European banks:


Before the European integration After the European integration an before last financial crisis During the last financial crisis

Risk measure

Loan loss provision to total loans 1.457796 1.005803 .5611184 Liquid assets to total assets 37.15308 30.54644 30.0822 Market proportion in the total assets .1314926 .1672181 .1185017


According to the above explanation German banks have higher liquidity risk than European competitors while they are less exposure to the credit risk especially during the last financial crisis, except in the period before the European integration was more risky than European competitors. In addition, German banks are less exposure to the market risk, that means European competitors are depend on market finance, hence the German banks they face less risky from the market risk (this case refers to the high regulation by the state particularly after European integration when the competition increased). My opinion, German banks are not riskier than European competitors because its focus on long-term loans that is possible to face difficult to liquidate asset, but this problem solved by taking large proportion of loan loss provision to compensate any credit risk and liquidity risk, because credit default lead to liquidation asset. However, the current literature as we discuses above suggest that Germany me face some economic problems.

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The Usefulness Of Liquidity Credit And Market Risk Finance Essay. (2017, Jun 26). Retrieved June 26, 2022 , from

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