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2010
In this chapter we review the main market risk measurement tool used in banking, known as value-at-risk (VaR). The review looks at the three main methodologies used to calculate VaR, as well as some of the key assumptions used in the calculations, including those on the normal distribution of returns, volatility levels and correlations. We also discuss
Moorad Choudhry +4 more
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In this chapter we review the main market risk measurement tool used in banking, known as value-at-risk (VaR). The review looks at the three main methodologies used to calculate VaR, as well as some of the key assumptions used in the calculations, including those on the normal distribution of returns, volatility levels and correlations. We also discuss
Moorad Choudhry +4 more
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Artifactual unit root behavior of Value at risk (VaR)
Statistics & Probability Letters, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chan, Ngai Hang, Sit, Tony
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BANKPEDIA REVIEW, 2013
The value at risk (VaR) measures the risk of loss associated to financial assets. For a given time period (normally ranging from 1 to 10 days), and with a given probability confidence (generally equal to 95% or 99%); this measure represents the maximum loss the investor can suffer when holding financial assets.
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The value at risk (VaR) measures the risk of loss associated to financial assets. For a given time period (normally ranging from 1 to 10 days), and with a given probability confidence (generally equal to 95% or 99%); this measure represents the maximum loss the investor can suffer when holding financial assets.
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VaR (Value at Risk) Model [PDF]
Romanian Statistical Review Supplement, 2012 The VaR model represents a significant progress in risk analysis, among the improvements it brings we can outline the attempt to measure risk itself in terms of an eventual loss, instead of focusing on gain-based approach.
Vergil VOINEAGU, Danut CULETU
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Conditional Expectile: An Alternative to Value at Risk (VaR)
SSRN Electronic Journal, 2021Various risk measures have been reviewed against the criteria commonly accepted by financial researchers and practitioners: coherence, elicitability, comonotonic additivity, and intuitiveness. It follows that the only risk measure that is both coherent and elicitable is an Expectile based risk measure. But unlike the VaR measure, the Expectile does not
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Range-based models in estimating value-at-risk (VaR) [PDF]
Philippine Review of Economics, 2008 This paper introduces new methods of estimating Value-at-Risk (VaR) using range-based GARCH (general autoregressive conditional heteroskedasticity) models. These models, which could be based on either the Parkinson range or the Garman-Klass range, are applied to ten stock market indices of selected countries in the Asia-Pacific region.
Mapa, Dennis, Beronilla, Nikkin
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Value-at-Risk dynamics: a copula-VAR approach
The European Journal of Finance, 2019In financial research and among risk management practitioners the estimation of a correct measure of the Value-at-Risk still proves interesting.
Giovanni de Luca +2 more
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LIMITATIONS OF VALUE-AT-RISK (VAR) FOR BUDGET ANALYSIS
2004Value-at-risk (VaR) is increasingly being applied to problems in agriculture, especially valuation of crop insurance and agricultural lending risk exposure. VaR conveys the probability that losses exceeding a threshold will likely occur within a specified timeframe. However, it does not provide the expected value of losses, should they happen.
Gustafson, Cole R., Gustafson, Cole R.
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Introduction to Var (Value-At-Risk)
1999Modern financial theory is based on several important principles, two of which are no-arbitrage and risk aversion. The single major source of profit is risk. The expected return depends heavily on the level of risk of an investment. Although the idea of risk seems to be intuitively clear, it is difficult to formalize it.
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Review on Three New Value at Risk (VaR) Models
Advances in Economics, Management and Political Sciences, 2023The emergence of financial derivatives complicates traditional financial products and increases financial market volatility. Individuals and financial institutions are both exposed to more complex and uncontrollable risks in this environment. Because of the risk's uncertainty, we must use reasonable methods to predict and estimate it in order to ...
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