Results 11 to 20 of about 141,957 (262)
Comparison of Electricity Spot Price Modelling and Risk Management Applications
Energies, 2020 In dealing with sharp changes in electricity prices, contract planning is considered as a vital risk management tool for stakeholders in deregulated power markets.
Ethem Çanakoğlu, Esra Adıyeke
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Multi-Variate Risk Measures under Wasserstein Barycenter
Risks, 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
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Determining Systemic Risk of Banks, Financial Services, and Insurance Firms of Pakistan
JISR Management and Social Sciences & Economics, 2018 This paper contributes on the literature of systemic risk by investigating the extent of financial distress injected by banks, financial services, and insurance firms in the financial system of Pakistan.
Shumaila Zeb, Abdul Rashid
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Hedging Conditional Value at Risk with options [PDF]
European Journal of Operational Research, 2015 We present a method of hedging Conditional Value at Risk of a position in stock using put options. The result leads to a linear programming problem that can be solved to optimise risk hedging.
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Using Entropy to Forecast Bitcoin’s Daily Conditional Value at Risk
Proceedings, 2019 Conditional value at risk (CVaR), or expected shortfall, is a risk measure for investments according to Rockafellar and Uryasev. Yamai and Yoshiba define CVaR as the conditional expectation of loss given that the loss is beyond the value at risk (VaR ...
Hellinton H. Takada +3 more
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Mathematics, 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
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Statistical Learning with Conditional Value at Risk
CoRR, 2020 We propose a risk-averse statistical learning framework wherein the performance of a learning algorithm is evaluated by the conditional value-at-risk (CVaR) of losses rather than the expected loss. We devise algorithms based on stochastic gradient descent for this framework.
Tasuku Soma, Yuichi Yoshida
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Optimization with Multivariate Conditional Value-at-Risk Constraints [PDF]
Operations Research, 2013 For many decision-making problems under uncertainty, it is crucial to develop risk-averse models and specify the decision makers' risk preferences based on multiple stochastic performance measures (or criteria). Incorporating such multivariate preference rules into optimization models is a fairly recent research area.
Nilay Noyan, Gábor Rudolf
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Presenting a Model for Multiple-Step-Ahead-Forecasting of Volatility and Conditional Value at Risk in Fossil Energy Markets [PDF]
AUT 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
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Fractal and Fractional, 2022 Risk management is very important for individual investors or companies. There are several ways to measure the risk of investment. Prices of risky assets vary rapidly and randomly due to the complexity of finance market. Random interval is a good tool to
Jinping Zhang, Keming Zhang
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