Results 21 to 30 of about 3,030,006 (223)

Intraday Value-at-Risk [PDF]

open access: yes, 2000
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.
openaire   +3 more sources

Multi-Variate Risk Measures under Wasserstein Barycenter

open access: yesRisks, 2022
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
doaj   +1 more source

Normality and Its Verification as a Basic Prerequisite for the Application of VaR [PDF]

open access: yesSHS Web of Conferences, 2021
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
doaj   +1 more source

Risk assessment of microgrid aggregators considering demand response and uncertain renewable energy sources

open access: yesJournal of Modern Power Systems and Clean Energy, 2019
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
doaj   +1 more source

Presenting a Model for Multiple-Step-Ahead-Forecasting of Volatility and Conditional Value at Risk in Fossil Energy Markets [PDF]

open access: yesAUT Journal of Modeling and Simulation, 2018
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
doaj   +1 more source

Value-at-risk

open access: yesThe Journal of Risk Finance, 2010
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
  +6 more sources

THE ROLE OF VALUE AT RISK IN THE MANAGEMENT OF ASSET AND LIABILITIES [PDF]

open access: yesAnnals of the University of Oradea: Economic Science, 2012
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

open access: yesStatistical Theory and Related Fields, 2020
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
doaj   +1 more source

Improving Value-at-Risk prediction under model uncertainty

open access: yes, 2020
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
core   +1 more source

Predicting Returns, Volatilities and Correlations of Stock Indices Using Multivariate Conditional Autoregressive Range and Return Models

open access: yesMathematics, 2022
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
doaj   +1 more source

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