Operational Risk: Scenario analysis

Zájem o problematiku řízení a meření operačního rizika se v posledních letech prudce zvyšuje - zejména kvůli požadavkům kapitálové přimeřenosti definovaných v Basel II, které musí k 1. lednu 2008 splňovat všechny mezinárodně aktivní finanční instituce a také kvůli závažným ztrátám v oblasti operačního rizika, které se staly v nedávné minulosti. Tato diplomová práce se zaměřuje na techniky meření operačního rizika a metody odhadů kapitálové přiměřenosti. Soubor ztrát operačního rizika, který byl poskutnut středoevropskou bankou, je analyzován pomocí různých přístupů. Je posuzováno několik statistických konceptů používaných pro modelování rozdělení operačních ztrát. Jednou z metod řízení operačního rizika je metoda analýzy scénářů. V této metodě jsou definovány hypotetické ztrátové události a tyto události jsou přidány do souboru empirických událostí a následně je posuzován vliv výsledného souboru událostí na výpočet kapitálové přiměřenosti a na finanční instituci jako celek. Tato diplomová práce se zejména věnuje následujícím dvěma problémům - jaká je nejpřijatelnější statistická metoda na měření a modelování rozdělení ztrát operačního rizika a jaký je vliv hypotetických událostí na finanční instituci. G&h distribuce byla vyhodnocena jako nejvhodnější pro modelování ztrát operačního rizika a výsledky...Operational risk management and measurement has been paid an increasing attention in recent years - namely due to the Basel II requirements that were to be complied with by all international active financial institutions by January 2008 and also due to recent severe operational risk loss events. This diploma thesis focuses on operational risk measurement techniques and on regulatory capital estimation methods. A data sample of operational losses provided by a Central European bank is analyzed using several approaches. Multiple statistical concepts for the Loss Distribution Approach are considered. One of the methods used for operational risk management is a scenario analysis. Under this method custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution as a whole is evaluated. Two main problems are assessed in this diploma thesis - what is the most appropriate statistical method to measure and model operational loss data distribution and what is the impact of hypothetical plausible events on the financial institution. The g&h distribution was evaluated to be the most suitable one for operational risk modeling because its results are consistent even while using scenario analysis method. The...Institute of Economic StudiesInstitut ekonomických studiíFaculty of Social SciencesFakulta sociálních vě

Modelling Long-Term Electricity Contracts at EEX

The main aim of this paper is to develop and calibrate an econometric model for modelling prices of long term electricity futures contracts. The calibration of our model is performed on data from EEX AG allowing us to capture the specific features of German electricity market. The data sample contains several structural breaks which have to be taken into account for modelling. We model the data with an ARIMAX model which reveals high correlation between the price of electricity futures contracts (namely Phelix Base Fututes with next year´s delivery) and prices of long-term futures contracts of fuels (namely coal, natural gas and crude oil). Besides this, also a share price index of representative electricity companies traded on Xetra, spread between 10Y and 1Y German bonds and exchange rate between EUR and USD appeared to have significant explanatory power over these futures contracts on EEX.electricity futures, EEX, ARIMAX, emission allowances

Operattional risk : scenario analysis

Zájem o problematiku řízení a meření operačního rizika se v posledních letech prudce zvyšuje - zejména kvůli požadavkům kapitálové přimeřenosti definovaných v Basel II, které musí k 1. lednu 2008 splňovat všechny mezinárodně aktivní finanční instituce a také kvůli závažným ztrátám v oblasti operačního rizika, které se staly v nedávné minulosti. Tato diplomová práce se zaměřuje na techniky meření operačního rizika a metody odhadů kapitálové přiměřenosti. Soubor ztrát operačního rizika, který byl poskutnut středoevropskou bankou, je analyzován pomocí různých přístupů. Je posuzováno několik statistických konceptů používaných pro modelování rozdělení operačních ztrát. Jednou z metod řízení operačního rizika je metoda analýzy scénářů. V této metodě jsou definovány hypotetické ztrátové události a tyto události jsou přidány do souboru empirických událostí a následně je posuzován vliv výsledného souboru událostí na výpočet kapitálové přiměřenosti a na finanční instituci jako celek. Tato diplomová práce se zejména věnuje následujícím dvěma problémům - jaká je nejpřijatelnější statistická metoda na měření a modelování rozdělení ztrát operačního rizika a jaký je vliv hypotetických událostí na finanční instituci. G&h distribuce byla vyhodnocena jako nejvhodnější pro modelování ztrát operačního rizika a výsledky...Operational risk management and measurement has been paid an increasing attention in recent years - namely due to the Basel II requirements that were to be complied with by all international active financial institutions by January 2008 and also due to recent severe operational risk loss events. This diploma thesis focuses on operational risk measurement techniques and on regulatory capital estimation methods. A data sample of operational losses provided by a Central European bank is analyzed using several approaches. Multiple statistical concepts for the Loss Distribution Approach are considered. One of the methods used for operational risk management is a scenario analysis. Under this method custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution as a whole is evaluated. Two main problems are assessed in this diploma thesis - what is the most appropriate statistical method to measure and model operational loss data distribution and what is the impact of hypothetical plausible events on the financial institution. The g&h distribution was evaluated to be the most suitable one for operational risk modeling because its results are consistent even while using scenario analysis method. The...Institute of Economic StudiesInstitut ekonomických studiíFaculty of Social SciencesFakulta sociálních vě

The economic development of Brazil in nineties

This paper analyzes transformation process of Brazilian economy during last decade of the 20th century from an industrional based country into modern open market economy. Special focus is given to the exchange rate anchor stabilization program - Plano real - which mixed spectacular price stabilization with some macroeconomic destalization. Powered by TCPDF (www.tcpdf.org

Operational Risk: Scenario analysis

Operational risk management and measurement has been paid an increasing attention in recent years - namely due to the Basel II requirements that were to be complied with by all international active financial institutions by January 2008 and also due to recent severe operational risk loss events. This diploma thesis focuses on operational risk measurement techniques and on regulatory capital estimation methods. A data sample of operational losses provided by a Central European bank is analyzed using several approaches. Multiple statistical concepts for the Loss Distribution Approach are considered. One of the methods used for operational risk management is a scenario analysis. Under this method custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution as a whole is evaluated. Two main problems are assessed in this diploma thesis - what is the most appropriate statistical method to measure and model operational loss data distribution and what is the impact of hypothetical plausible events on the financial institution. The g&h distribution was evaluated to be the most suitable one for operational risk modeling because its results are consistent even while using scenario analysis method. The..

Operattional risk : scenario analysis

Operational risk management and measurement has been paid an increasing attention in recent years - namely due to the Basel II requirements that were to be complied with by all international active financial institutions by January 2008 and also due to recent severe operational risk loss events. This diploma thesis focuses on operational risk measurement techniques and on regulatory capital estimation methods. A data sample of operational losses provided by a Central European bank is analyzed using several approaches. Multiple statistical concepts for the Loss Distribution Approach are considered. One of the methods used for operational risk management is a scenario analysis. Under this method custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution as a whole is evaluated. Two main problems are assessed in this diploma thesis - what is the most appropriate statistical method to measure and model operational loss data distribution and what is the impact of hypothetical plausible events on the financial institution. The g&h distribution was evaluated to be the most suitable one for operational risk modeling because its results are consistent even while using scenario analysis method. The..

Operattional risk : scenario analysis

Operational risk management and measurement has been paid an increasing attention in recent years - namely due to the Basel II requirements that were to be complied with by all international active financial institutions by January 2008 and also due to recent severe operational risk loss events. This diploma thesis focuses on operational risk measurement techniques and on regulatory capital estimation methods. A data sample of operational losses provided by a Central European bank is analyzed using several approaches. Multiple statistical concepts for the Loss Distribution Approach are considered. One of the methods used for operational risk management is a scenario analysis. Under this method custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution as a whole is evaluated. Two main problems are assessed in this diploma thesis - what is the most appropriate statistical method to measure and model operational loss data distribution and what is the impact of hypothetical plausible events on the financial institution. The g&h distribution was evaluated to be the most suitable one for operational risk modeling because its results are consistent even while using scenario analysis method. The..

The economic development of Brazil in nineties

This paper analyzes transformation process of Brazilian economy during last decade of the 20th century from an industrional based country into modern open market economy. Special focus is given to the exchange rate anchor stabilization program - Plano real - which mixed spectacular price stabilization with some macroeconomic destalization. Powered by TCPDF (www.tcpdf.org

A Service of zbw Operational risk -scenario analysis Operational Risk -Scenario Analysis

Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Abstract: Operational risk management and measurement has been paid an increasing attention in last years. The main two reasons are the Basel II requirements that were to be complied with by all international active financial institutions by the end of 2006 and recent severe operational risk loss events. This paper focuses on operational risk measurement techniques and on economic capital estimation methods. A data sample of operational losses provided by an anonymous Central European bank is analyzed using several approaches. Multiple statistical concepts such as the Loss Distribution Approach or the Extreme Value Theory are considered. One of the methods used for operational risk management is a scenario analysis. Under this method, custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution as a whole is evaluated. Two main problems are assessed in this paper -what is the most appropriate statistical method to measure and model operational loss data distribution and what is the impact of hypothetical plausible events on the financial institution. The g&h distribution was evaluated to be the most suitable one for operational risk modeling because its results are consistent even while using a scenario analysis method. The method based on the combination of historical loss events modeling and scenario analysis provides reasonable capital estimates for the financial institution and allows to measure impact of very extreme events and also to mitigate operational risk exposure

Value at Risk forecasting with the ARMA-GARCH family of models in times of increased volatility

The paper evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the ARMA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting accuracy is evaluated on the out-of-sample data, which are more volatile. The main aim of the paper is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index separately. The primary result of the paper is that the volatility is best modelled using a GARCH process and that an ARMA process pattern cannot be found in analyzed time series.VaR, risk analysis, conditional volatility, conditional coverage, garch, egarch, tarch, moving average process, autoregressive process