We determine whether there is an endogenous Hidden Markov Regime (HMR) in the operational loss data of banks from 2001 to 2010. A high level regime is marked by very high loss values during the recent financial crisis. There is therefore temporal heterogeneity in the data. If this heterogeneity is not considered in risk management models, capital estimations will be biased. Levels of reserve capital will be overestimated in periods of normal losses, corresponding to the low level of the regime, and underestimated in periods of a high regime. Variation in capital can go up to 30% during this period of analysis when regimes are not considered
Movements of financial variables exhibit extreme fluctuations during periods of economic crisis and ...
This paper focuses on modeling the real operational data of an anonymous Central European Bank. We h...
This research applies a discrete-time Markov-modulated model to default probability estimation and a...
Operational losses are true dangers for banks since their maximal values to signal default are diffi...
In this study we try to explain the inclusion of banks in the WDCI list proposed by Bloomberg. This ...
Using equity returns for financial institutions we estimate both catastrophic and operational risk m...
According to Basel II criteria, the use of external data is absolutely indispensable to the implemen...
Banks that use the advanced measurement approach to model operational risk may struggle to develop a...
peer reviewedWe investigate a novel database of 10,217 extreme operational losses from the Italian b...
This paper examines factors that affect the performance of investment banks in the G7 and Switzerlan...
Use of variability of profits and other accounting-based ratios in order to estimate a firm's risk o...
International audienceThis paper constructs a regime switching model for the univariate Value-at-Ris...
In this paper, we analyse a database of around 41,000 operational losses from the European bank UniC...
Using a unique and comprehensive dataset, this paper develops and uses three distinct methods to qua...
This paper focuses on operational risk measurement techniques and on economic capital estimation met...
Movements of financial variables exhibit extreme fluctuations during periods of economic crisis and ...
This paper focuses on modeling the real operational data of an anonymous Central European Bank. We h...
This research applies a discrete-time Markov-modulated model to default probability estimation and a...
Operational losses are true dangers for banks since their maximal values to signal default are diffi...
In this study we try to explain the inclusion of banks in the WDCI list proposed by Bloomberg. This ...
Using equity returns for financial institutions we estimate both catastrophic and operational risk m...
According to Basel II criteria, the use of external data is absolutely indispensable to the implemen...
Banks that use the advanced measurement approach to model operational risk may struggle to develop a...
peer reviewedWe investigate a novel database of 10,217 extreme operational losses from the Italian b...
This paper examines factors that affect the performance of investment banks in the G7 and Switzerlan...
Use of variability of profits and other accounting-based ratios in order to estimate a firm's risk o...
International audienceThis paper constructs a regime switching model for the univariate Value-at-Ris...
In this paper, we analyse a database of around 41,000 operational losses from the European bank UniC...
Using a unique and comprehensive dataset, this paper develops and uses three distinct methods to qua...
This paper focuses on operational risk measurement techniques and on economic capital estimation met...
Movements of financial variables exhibit extreme fluctuations during periods of economic crisis and ...
This paper focuses on modeling the real operational data of an anonymous Central European Bank. We h...
This research applies a discrete-time Markov-modulated model to default probability estimation and a...