The Risk Map: A new tool for validating risk models

Colletaz, Gilbert; Hurlin, Christophe; Pérignon, Christophe

doi:10.1016/j.jbankfin.2013.06.006

Cited by 67 publications

(42 citation statements)

References 34 publications

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“…We use the test of unconditional coverage (UC) by Kupiec (1995) to asses if the number of VaR exceedances differs significantly from ˛· 100% within the sample. Furthermore, we apply the multivariate unconditional coverage likelihood ration (LR MUC ) test of Colletaz et al (2013), which jointly tests the number of VaR exceedances and super exceedances. Super exceedances are defined as the VaR exceedance at a very low probability ˛*, in our case 0.02%.…”

Section: Var-forecastingmentioning

confidence: 99%

Forecasting volatility with empirical similarity and Google Trends

Hamid,

Heiden

2015

Journal of Economic Behavior & Organization

120

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Section: Var-forecastingmentioning

confidence: 99%

Forecasting volatility with empirical similarity and Google Trends

Hamid,

Heiden

2015

Journal of Economic Behavior & Organization

120

View full text Add to dashboard Cite

“…The test is easily applicable and has shown improvement compared to the univariate procedures in the performance assessment of VaR. Colletaz et al (2013) have developed a new method for validation of the risk model, called, risk map (RM). This method calculates both the number and the size of the extreme losses and graphically sums all information on performances of the risk model.…”

Section: Source: Basel Committee On Banking Supervision: "Supervisorymentioning

confidence: 99%

Risk model backtesting

Terzić¹,

Milojević²

2016

Ekonomika

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EKONOMIKA МЕЂУНАРОДНИ ЧАСОПИС ЗА ЕКОНОМСКУ ТЕОРИЈУ И ПРАКСУ И ДРУШТВЕНА ПИТАЊАЧасопис излази четири пута годишње ИЗДАВАЧ: Друштво економиста "Економика" Ниш СУИЗДАВАЧИ: Економски факултет у Приштини, Факултет за услужни бизнис -Сремска Каменица, Институт за економику пољопривреде -Београд, Факултет за пословне студије и право -Београд, Факултет за трговину и банкарство, Универзитет Алфа -Београд, Савез економиста Србије -Друштво економиста Ниш. ГЛАВНИ И ОДГОВОРНИ УРЕДНИК:Проф. IntroductionIt is important for a financial institution to monitor the volatilities of the market variables (interest rates, exchange rates, equity prices, commodity prices, etc.) on which the value of its portfolio depends. Financial institutions are faced with various forms of risk. In order to control, manage and measure risks, they have been actively engaged in the financial risk management process. The risk management function contributes to better risk management within banks, through continuous measurement of risk of the current portfolio of financial assets and other exposures, as well as by taking steps, either directly or in cooperation with other functions of the bank, in order to reduce the possibility of loss. From the regulator's perspective, the size and the risk of the bank's assets are one of the most important determinants for defining the amount of the necessary capital of the bank.The globalization of the financial market has led to the need for the globalization of the supervision system of the financial sector. Regulatory bodies are in charge of protection of the financial system against catastrophic events, which could be source of systematic risk. In the last couple of years, the central issue of risk management is to determine the capital adequacy for financial institutions, in order to protect themselves against the market risk. The assessment of the market risk is a complex and an extremely important task for each and every credit institution. This increased focus on risk management has led to the development of various methods and tools for the risk measurement, which financial institutions are faced with.Financial risk management has truly undergone a revolution in the last couple of years, which has been intiated by the introduction of Value at Risk (hereinafter: VaR), a new method for measuring one aspect of the financial risk, the market risk. In the light of the recent financial crisis, measuring of the market risk is drawing even more attention and is becoming more and more significant. The last global, financial crisis has shown that systems for management and calculation of exposure to such risks, have significantly failed, and has therefore forced banks to take certain steps for the purpose of forming efficient internal approaches and methods for market risk management. Risk managers are attempting to revise the previous methods, given that they feel that one of the most important causes of the recent crisis is the actual poor risk management.Market risk arises primarily from the bank's trading operati...

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“…Th e test is easily applicable and has shown improvement compared to the univariate procedures in the performance assessment of VaR. Colletaz et al (2013) have developed a new method for the risk model validation, called, risk mapping (RM). Th is method calculates both the number and the size of the extreme losses and graphically sums all information on performances of the risk model.…”

Section: Tabel 1 Basel Backtesting Rulesmentioning

confidence: 99%

Methods of Validating the Models for Measuring Market Risk – Backtesting

Terzić¹,

Milojević²,

Jeremić³

2015

Proceedings of the 1st International Scientific Conference - FINIZ 2015

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This paper analyses the methods for validation of risk model and provides an overview of the present literature related to the validation and evaluation of VaR model success. The importance of validating a risk model originates from the fact that financial institutions are authorised by regulatory bodies to use in-house models for the evaluation of VaR and assess capital adequacy based on that. To that end, the regulator has also developed the so-called "traffic light "approach for model back testing. However, the latest financial crisis has shown that such an approach to model validation did not provide good evaluations of VaR model, which severely underestimated risk and led to failure of many banks throughout the world. Due to that, academic literature is more than ever focused on reviewing and developing new techniques and procedures for the risk model verification. Therefore, the aim of this paper is to offer a comparative overview of market risk validation models that have evolved over the last few years.

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The Risk Map: A new tool for validating risk models

Cited by 67 publications

References 34 publications

Forecasting volatility with empirical similarity and Google Trends

Forecasting volatility with empirical similarity and Google Trends

Risk model backtesting

Methods of Validating the Models for Measuring Market Risk – Backtesting

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