Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.630480
Title: Risk measurement of banks using accounting and capital markets measures
Author: Al Abed, Shafiq Khleif Khalaf
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2003
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Abstract:
This thesis investigates the different bank risks in Western European banks and banks in Jordan. Risk applies at multiple levels, and the information structure provided by internal, external and market measures of risk is the main concern of this research. In this thesis, Long Tenn Debt Rating (LTDR) by the popular rating agency "Moody's Rating Agency" was considered as a proxy for risk measurement which reflects mainly different risks facing the banking industry and concurrent with the new suggestions of the Basle Committee where external and internal bank ratings are of importance in the new banking regulation system. In this thesis, we try to determine ways of determining credit risk proxies for individual banks. Furthermore, we explore how macroeconomic and stock market data can improve risk measurement. A Multiple Discriminant Analysis (MDA) model was built from the data of 210 European banks for 1999 to anticipate rating for the Western European banks. This model depends on 5 accounting variables and 3 macroeconomic variables. The classification rate of 60.5% gives the model a good acceptance rate compared with extant prediction models. This model was also used to fit rating for Jordanian banks where rating was not available. The relationship between this rating proxy model and a set of market and accounting variables for a group of 129 Western European banks through the period of 1993-2000 was analysed. The results showed that there was no significant relationship between rating proxy for these European banks and standard deviation of return (total risk) but a group of market measures of risk, return, beta, standard deviation of return and market to book value (MTBV) had a limited effect on the explanation of rating proxy of European banks with adjusted R2 not more than 6.3%. On the other hand, a group of accounting risk measures (ratios) was selected and analysed to determine the relationship between these accounting variables and rating proxy. These accounting variables were dividend payout ratio, leverage ratio, return on assets (ROA), loan to deposit ratio, subordinated debt and non-interest expense over the average assets. The results showed a highly significant relationship between these accounting variables and rating proxy with an adjusted R2 of 40.8%. A combination of accounting and market variables were used to find out if these variables together can provide a greater explanation of rating. The results showed that this combination had slightly more explanatory power than accounting measures alone with adjusted R2 of 43.2%. These results confirmed that accounting variables have more explanation power than market measures and these accounting ratios are still the main source of data for rating agencies when assigning rating for banks. For Jordanian banks, a sample of 16 Jordanian banks through the period 1993- 2000 was examined. The rating proxy model developed for European banks was applied to Jordanian banks. Using the model no Jordanian bank was found to have a Aaa rating whilst 82% of Jordanian banks have ratings of Baa and below. 16 These results tend to reflect the real situation where most banks in Jordan were very small with limited assets and capital. There was no significant relationship between rating proxy and standard deviation of return (total risk) for Jordanian banks. The relationship between a set of market variables and rating proxy was significant with adjusted R2 of 21 % which is better than the results for European banks. This suggest that the Jordanian stock market without the benefit of a credit rating for each bank does use the accounting and economic information which has been found to apply to European banks. The importance of accounting variables is substantiated using OLS regression.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.630480  DOI: Not available
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