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From duration analysis to GARCH models – An approach to systematization of quantitative methods in risk measurement

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Krzysztof J.

Economics and Business Review

2016

vol. 2(16)

issue 3

The development of scientific research has led to the very dynamic growth of methods in the area of financial risk management. This refers particularly to risk measures in which quantitative methods are applied. The paper provides a discussion on a systematization of different risk measures proposed in scientific literature and used in practice. There are four criteria proposed in the paper. The first is the concept of risk applied by distinguishing negative and neutral concept. The second criterion is the character of the risk variable, either discrete or continuous . The third criterion makes the distinction between high frequency, low severity events, corresponding to standard (normal) type of risk, and low frequency, high severity events, corresponding to extreme risk. Finally the fourth criterion distinguishes between the risk variable expressed in monetary values and risk variable expressed in time units. Using these criteria the most common groups of risk measures are discussed. The final part of the paper gives a synthetic discussion on model risk which is a risk resulting from the erratic model used in a real world. In the paper three main sources of model risk are presented and the methods to evaluate model risk are given.

Estimating Model Risk of VaR under Different Approaches: Study on European Banks

86%

Pasieczna A. H., Szydłowska M. J.

Współczesne Problemy Zarządzania

2021

vol. 9

issue 2(19)

65-76

The objective of this research is to estimate the model risk, represented as precision, and the accuracy of the Value at Risk (VaR) measure, under three different approaches: historical simulation (HS), Monte Carlo (MC), and generalized ARCH (GARCH). In this work, to analyze the VaR model, the accuracy and precision were used. Estimation of the accuracy and precision was done under the three approaches for four European banks at 95 and 99% confidence levels. The percentage crossings and Kupiec POF were used to judge the model accuracy, whereas the ratio of the maximum and minimum VaR estimates, and the spread between the maximum and minimum VaR estimates were used to estimate the model risk. This was achieved by changing input parameters, specifically, the estimation time window (125, 250, 500 days). Implications/Recommendations: The accuracy alone is not sufficient to evaluate a model and precision is also required. The temporal evolution of the precision metrics showed that the VaR approaches were inconsistent under different market conditions. This article focuses on the accuracy and precision concepts applied to estimate model risk of the Value at Risk (VaR). VaR is the foundation for sophisticated risk metrics, including systemic risk measures like Marginal Expected Shortfall and Delta Conditional Value at Risk. Thus, understanding the risk associated with the use of VaR is crucial for finance practitioners.

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1 Economics and Business Review

1 Współczesne Problemy Zarządzania

1 Krzysztof J.

1 Pasieczna A. H.

1 Szydłowska M. J.

1 2021

1 2016

Search results

From duration analysis to GARCH models – An approach to systematization of quantitative methods in risk measurement

Estimating Model Risk of VaR under Different Approaches: Study on European Banks