Ανάλυση και διαχείριση τραπεζικών κινδύνων: εμπειρική εφαρμογή στο μοντέλο VaR
Bank risk management methods: experimental study with the VaR model
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Keywords
Διαχείριση κινδύνου ; Χρηματοπιστωτικά ιδρύματα ; Πιστωτικός κίνδυνος ; Κίνδυνος αγοράς ; Οικονομετρική ανάλυση ; Τραπεζικοί κίνδυνοι ; Risk management ; Financial institutions ; Credit risk ; Market risk ; Econometrics ; Value at RiskAbstract
This master thesis analyzes the risks with which they come across with the banking institutions in the country. Risk management is then analyzed through the methodologies for each type of risk separately. The risks determine the proper functioning of the financial system, and reference is made to the regulatory rules laid down for the smooth operation of the financial system.
An empirical application was then made to the Value at Risk-VaR methodology, which mainly refers to market risk and in some cases to credit risk. The empirical application was made in Eviews. The data was used is the daily values of the shareholders of the four major banks for two years from 1/9/2015 to 1/9/2017. Initially, the daily stock returns and their descriptive statistical measures are calculated. Then, the yield time series stagnation is checked. The time series of the four banks have been characterized as non-stop, which is not valued for the returns. Thus, autocorrelation of residuals is performed to evaluate the fluctuations with the GARCH model with a fixedterm. The resulting time series of the variance was used in the value at risk estimate.
Then a portfolio of three stocks (Eurobank, OTE, Terna) belonging to different sectors (to be differentiated) with different signs in the growth rate was selected, as the banking sector declined, the telecommunications sector grew and construction stagnated and applied the historical simulation method to calculate the VaR portfolio. Excel was used in these calculations.
At the end, the conclusions that emerged from the empirical application are the expected ones based on the time period we are going through. An investor who invests in bank shares is more likely to suffer loss than earnings. In the case of the portfolio where the historical simulation method was applied, it is noted that there are days when the portfolio presents profits and days that show losses, which is usual since the portfolio includes different stocks.