Dynamic value-at-risk models and the peaks-over-threshold method for market risk measurement: an empirical investigation during a financial crisis

2012 ◽  
Vol 6 (2) ◽  
pp. 3-45 ◽  
Author(s):  
Marco Bee
Keyword(s):  
At Risk ◽  
Financial Crisis ◽  
Value At Risk ◽  
Empirical Investigation ◽  
Market Risk ◽  
Risk Measurement ◽  
Peaks Over Threshold ◽  
Threshold Method ◽  
Risk Models

scholarly journals Market Risk Measurement

2020 ◽  
Author(s):  
Emese Lazar ◽  
Ning Zhang
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Preliminary Analysis ◽  
Risk Measures ◽  
Market Risk ◽  
Capital Requirements ◽  
Risk Measurement ◽  
Regulatory Framework ◽  
Bank Capital ◽  
Bank Capital Requirements

This chapter presents a preliminary analysis on how some market risk measures dramatically increased during the COVID-19 pandemic, with measures computed over longer horizons experiencing more pronounced effects. We provide examples when regulatory market risk measurement proved to be suboptimal, overestimating risk. A further issue was the large number of Value-at-Risk ‘exceptions’ during the first few months of the crisis, which normally leads to overinflated bank capital requirements. The current regulatory framework should address these problems by suggesting improvements to the calculation of risk measures and/or by modifying the rules which determine capital requirements to make them appropriate and realistic in crisis situations.

scholarly journals Extreme value theory in emerging markets: Evidence from the Montenegrin stock exchange

2015 ◽  
Vol 60 (206) ◽  
pp. 87-116 ◽  
Author(s):  
Julija Cerovic ◽  
Vesna Karadzic
Keyword(s):  
At Risk ◽  
Stock Market ◽  
Extreme Value Theory ◽  
Value At Risk ◽  
Emerging Market ◽  
Value Theory ◽  
Extreme Value ◽  
Peaks Over Threshold ◽  
Threshold Method ◽  
Block Maxima

The concept of Value at Risk(VaR) estimates the maximum loss of a financial position at a given time for a given probability. This paper considers the adequacy of the methods that are the basis of extreme value theory in the Montenegrin emerging market before and during the global financial crisis. In particular, the purpose of the paper is to investigate whether the peaks-over-threshold method outperforms the block maxima method in evaluation of Value at Risk in emerging stock markets such as the Montenegrin market. The daily return of the Montenegrin stock market index MONEX20 is analyzed for the period January 2004 - February 2014. Results of the Kupiec test show that the peaks-over-threshold method is significantly better than the block maxima method, but both methods fail to pass the Christoffersen independence test and joint test due to the lack of accuracy in exception clustering when measuring Value at Risk. Although better, the peaks-over-threshold method still cannot be treated as an accurate VaR model for the Montenegrin frontier stock market.

A COMPARISON OF SOME UNIVARIATE MODELS FOR VALUE-AT-RISK AND EXPECTED SHORTFALL

2007 ◽  
Vol 10 (06) ◽  
pp. 1043-1075 ◽  
Author(s):  
CARLO MARINELLI ◽  
STEFANO D'ADDONA ◽  
SVETLOZAR T. RACHEV
Keyword(s):  
At Risk ◽  
Extreme Value Theory ◽  
Value At Risk ◽  
Value Theory ◽  
Extreme Value ◽  
Expected Shortfall ◽  
Stable Laws ◽  
Peaks Over Threshold ◽  
Threshold Method ◽  
Block Maxima

We compare in a backtesting study the performance of univariate models for Value-at-Risk (VaR) and expected shortfall based on stable laws and on extreme value theory (EVT). Analyzing these different approaches, we test whether the sum–stability assumption or the max–stability assumption, that respectively imply α–stable laws and Generalized Extreme Value (GEV) distributions, is more suitable for risk management based on VaR and expected shortfall. Our numerical results indicate that α–stable models tend to outperform pure EVT-based methods (especially those obtained by the so-called block maxima method) in the estimation of Value-at-Risk, while a peaks-over-threshold method turns out to be preferable for the estimation of expected shortfall. We also find empirical evidence that some simple semiparametric EVT-based methods perform well in the estimation of VaR.

scholarly journals Pomiar ryzyka rynkowego miarą wartoś​ci zagrożonej. Metoda kombinowania prognoz ​

2018 ◽  
pp. 183-198
Author(s):  
Piotr Mazur
Keyword(s):  
At Risk ◽  
Financial Institutions ◽  
Value At Risk ◽  
Risk Measure ◽  
Market Risk ◽  
Risk Measurement ◽  
Conditional Value At Risk ◽  
Parametric Methods ◽  
Combining Forecasts

The article discusses the measurement of market risk by Value at Risk method. Value at Risk measure is an important element of risk measurement mainly for financial institutions but can also be used by other companies. The Value at Risk is presented together with its alternative Conditional Value at Risk. The main methods of VaR estimation were divided into nonparametric, parametric and semi-parametric methods. The next part of the article presents a method of combining forecasts, which can be used in the context of forecasting Value at Risk.

scholarly journals Evaluasi Kualitas Pengungkapan Value at Risk Perbankan Indonesia

2019 ◽  
pp. 276
Author(s):  
Buddi Wibowo ◽  
Hasna Fadhila
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Simulation Method ◽  
Market Risk ◽  
Risk Measurement ◽  
Risk Level ◽  
Risk Disclosure ◽  
Historical Simulation ◽  
Risk Disclosures

Market risk measurement of bank investment portfolios is a still problem not only among practitioners, but  also among academicians. The accuracy and quality of market risk disclosures are important issues because  transparency of the bank risk level encourages market control in the form of market discipline and it also  improve the quality of risk management carried out internally by the bank. This research measures the quality of Value at Risk disclosures carried out by Indonesian banks. The accuracy of Value at Risk in this research is measured from the Value at Risk component which contains information of yield volatility of bank trading treasury activities. To measure Value at Risk disclosure, this research runs various methods of Value at Risk measurement. This research shows Historical Simulation is a Value at Risk method that is most widely used by Indonesia banks. The empirical test results show that the Value at Risk parametric method using asymmetric volatility have better quality than the Value at Risk Historical Simulation method. This research shows that Value at Risk as measured by Historical Simulation method contains the least information of bank trading treasury yields. Keywords: value at risk; disclosure; market risk; volatility

Portfolio Market Risk Assessment Using Value-at-Risk (VaR) Method – Historical Stimulation

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Sergei Radukanov ◽  
◽  
◽  
Keyword(s):  
Risk Assessment ◽  
At Risk ◽  
Value At Risk ◽  
Theoretical Aspect ◽  
Market Risk ◽  
Risk Measurement ◽  
Gamble Company ◽  
Historical Simulation ◽  
Toyota Motor Corporation

One of the main VaR methods on theoretical aspect – Historical Simulation to Portfolio is explained in this article. Portfolio market risk measurement is carried out towards the shares of the particular companies – The Procter & Gamble Company (PG), Toyota Motor Corporation (TM) and Nokia Corporation (NOK).

scholarly journals Application of Exogenous Liquidity Risk Models to Analyze Single Assets

2020 ◽  
Vol 1 (1) ◽  
pp. 24-30
Author(s):  
Yasir Salih ◽  
Riaman Riaman ◽  
Komar Komar ◽  
Alit Kartiwa
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Liquidity Risk ◽  
Risk Measurement ◽  
Risk Models ◽  
Market Participants ◽  
Calculation Results ◽  
Japanese Yen ◽  
The Cost

Exogenous liquidity risk measurement is a measurement of liquidity risk that affects all market participants and is not affected by the actions of any other actors. Exogenous liquidity risk measurement is usually called the Cost of Liquidity (COL). The main problem is how the level of liquidity of one currency against other currencies and the effect of liquidity risk on VaR (Value at Risk) on a single asset. This thesis examines the importance of liquidity risk on a single asset. Combining basic VaR and liquidity risk will result in more effective calculations. The model used is to add the basic VaR value with the Cost of Liquidity (COL) or also called Liquidity VaR (L-VaR). The calculation results show the different effects of liquidity for each country's currency. Indonesian Rupiah (IDR) is the currency that has the highest liquidity component compared to the Japanese Yen (JPY) and the Thai Baht (THB). The lower the liquidity component of a currency, the currency is very liquid, and the Japanese Yen (JPY) is the most liquid currency compared to the Indonesian Rupiah (IDR) and the Thai Baht (THB).

scholarly journals Value at Risk and Market Risk: Case of the Regional Securities Exchange

2020 ◽  
Vol 7 (6) ◽  
pp. 19
Author(s):  
Mouhamadou Saliou Diallo
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Financial Crisis ◽  
Value At Risk ◽  
Composite Index ◽  
Market Risk ◽  
Management Approach ◽  
Portfolio Risk ◽  
Confidence Levels ◽  
Determining Factor

The study of the BRVM market risk using the VaR method is a determining factor in assessing the performance of our equity portfolio composed of the BRVM composite index and the BRVM10 index. It has enabled us, with the help of Basel regulations, to use backtesting to determine the minimum amount of capital that an investor must hold per day to protect against risk. The kupiec test enables us to determine the reliability of VaR calculated at different confidence levels. The result of our study confirms, using the extreme VaR method, the robustness of our threshold-based portfolio risk management approach. It also confirms the problem of market attractiveness during times of financial crisis.

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