Results 21 to 30 of about 3,030,006 (223)
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics and high-frequency duration models) and non-parametric (empirical quantile, extreme distributions models) Value-at-Risk (VaR) techniques to intraday data for three stocks traded on the NewY ork Stock Exchange.
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Multi-Variate Risk Measures under Wasserstein Barycenter
When the uni-variate risk measure analysis is generalized into the multi-variate setting, many complex theoretical and applied problems arise, and therefore the mathematical models used for risk quantification usually present model risk.
M. Andrea Arias-Serna +2 more
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Normality and Its Verification as a Basic Prerequisite for the Application of VaR [PDF]
If we start to deal with the topics of investing or trading in the financial markets, sooner or later we will encounter the topic of risk. Risk is one of the basic input variables in assessing the suitability and profitability of an investment and ...
Chutka Jan, Vagner Ladislav
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In power market environment, the growing importance of demand response (DR) and renewable energy source (RES) attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.
Tirthadip Ghose +2 more
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Presenting a Model for Multiple-Step-Ahead-Forecasting of Volatility and Conditional Value at Risk in Fossil Energy Markets [PDF]
Fossil energy markets have always been known as strategic and important markets. They have a significant impact on the macro economy and financial markets of the world.
E. Mohammadian Amiri, S. B. Ebrahimi
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Value at risk (VaR) is one of the most widely used models in risk management. It is based on probability and statistics. VaR can be characterized as a maximum expected loss, given some time horizon and within a given confidence interval. Its utility is in providing a measure of risk that illustrates the risk inherent in a portfolio with multiple risk ...
Christian Gourieroux, Joann Jasiak
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THE ROLE OF VALUE AT RISK IN THE MANAGEMENT OF ASSET AND LIABILITIES [PDF]
ALM is the management of risk at enterprise level, the models used in ALM can be static or dynamic: single period-static models, multiple period static model, single period stochastic model, multi period stochastic model. While single period-static don't
Petria Nicolae +2 more
doaj
Optimal reinsurance designs based on risk measures: a review
Reinsurance is an effective way for an insurance company to control its risk. How to design an optimal reinsurance contract is not only a key topic in actuarial science, but also an interesting research question in mathematics and statistics.
Jun Cai, Yichun Chi
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Improving Value-at-Risk prediction under model uncertainty
Several well-established benchmark predictors exist for Value-at-Risk (VaR), a major instrument for financial risk management. Hybrid methods combining AR-GARCH filtering with skewed-$t$ residuals and the extreme value theory-based approach are ...
Peng, Shige +2 more
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This paper extends the conditional autoregressive range (CARR) model to the multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets.
Shay Kee Tan +2 more
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