• International Commerce and Information Review
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• v.9 no.2
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• pp.65-86
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• 2007

This paper reviews the properties and application methods of widely used types of risk measures, identifies the rationale and business-side effects of hedging, derives the theoretical formula of optimal hedging ratio, and analyzes the various functional aspects of VaR(Value-at-risk) as a risk measure and a hedging tool. Especially this paper focuses on the characteristics of VaR compared with other risk measures in terms of their own principal determinants and identifies its stronger aspects in the dimension of hedging strategy tools. As well, this paper provides the detailed processes deriving the optimal hedge ratios based on the distributional parameters and risk factors. In addition, this paper presents the detailed and substantial processes of estimating the minimum variance hedge ratio and minimum-VaR hedge ratio using the actual data and shows that the minimum variance hedge ratio proves helpful for many cases although it is not appropriate for the non-linear portfolio including the option contracts. We demonstrate the trade-off relationship between the minimum variance hedge strategy and the minimum-VaR hedge strategy in their hedging costs and performances through calculation of the respective VaRs and variances of unhedged and hedged portfolios and the optimal hedge ratio and hedging effectiveness values for the given long position in US Dollar with the short position in Euro.

• Management Science and Financial Engineering
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• v.17 no.2
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• pp.99-129
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• 2011

This paper analytically studies how to choose hedging instrument for firms with steady operating cash flows from value maximization perspective. I derive a formula to determine option's optimal strike that makes hedged cash flow have the best monetary payoff given a hedger's view on the underlying asset. I find that not only the expected mean but also the expected standard deviation of the underlying asset in relation to the forward price and the implied volatility play a crucial role in making optimal hedging decision. Higher moments play a certain part in hedging decision but to a lesser degree.

• Environmental and Resource Economics Review
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• v.26 no.4
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• pp.499-517
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• 2017

The purpose of this article is to show profit margin hedging can be an optimal strategy in crude oil purchasing. This study theoretically analyzes profit margin hedging strategy is optimal in crude oil purchasing using expected target utility function and conducts simulations to show if the profit margin hedging is profitable. In addition, this study tests existence of mean reversion of crude oil futures prices to confirm the theory that profit margin hedging is more profitable than other strategies, such as always hedging or buying at expiration with spot price, if futures prices are mean reverting. The simulation results show that the expected utility of profit margin hedging higher than other strategies. Although we cannot find any evidence that crude oil futures prices follow mean reverting process, we can conclude that profit margin hedging can be optimal strategy in crude oil purchasing based on theoretical proof and simulation results.

• Journal of Environmental Policy
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• v.12 no.4
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• pp.93-117
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• 2013

We analyze the optimal hedge ratio and hedge effectiveness with different periodic times between spot and futures on EUA and CER based on EU-ETS. The Main finding are as follows. The first, hedging model which considers the time-varying variance is not more accurate than non-time-varying hedging models. The second, optimal hedge ratios are different even though hedge effectiveness is similar for the hedging purpose. The third, hedge effectiveness has uncertainty if hedge period is short. In case of EUA it needs to over 6 weeks and CER needs to over 7 weeks. The fourth, cross hedge with CER futures is not suitable for profit ratios.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.501-510
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• 2002

During drought or impending drought period, the reservoir operation method is required to incorporate demand-management policy rule. The objective of this study is focused to the development of demand reduction rule by incorporating hedging-effect for a single reservoir system. To improve the performance measure of the objective function and constraints, we could incorporate three risk performance criteria proposed by Hashimoto et al. (1982) by mixed-integer programming and also incorporate successive linear programming to overcome nonlinear hedging term from the previous study(Shih et al., 1994). To verify this model, this hedging rule was applied to the Daechung multi-purpose dam. As a result, we could evaluate optimal hedging parameters and monthly trigger volumes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.712-717
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• 2011

Option issuers generally utilize Dynamic Delta Hedging(DDH) technique to avoid the risk resulting from continuously changing option value. DDH duplicates payoff of option position by adjusting hedge position according to the delta value from Black-Scholes(BS) model in order to maintain risk neutral state. DDH, however, is not able to guarantee optimal hedging performance because of the weaknesses caused by impractical assumptions inherent in BS model. Therefore, this study presents a methodology for dynamic option hedge using artificial neural network(ANN) to enhance hedging performance and show the superiority of the proposed method using various computational experiments.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.293-310
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• 2007

Recently a risk measure pricing and hedging is replacing a utility-based maximization problem in the literature. In this paper, we treat the optimal problem of risk measure pricing and hedging in the friction market, i.e. in the presence of transaction costs. The risk measure pricing is also verified with the contexts in the literature.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.987-1000
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• 2011

We show how the dynamic optimization problem with the capital constraint can be reduced to the problem to find an optimal modified claim $\tilde{\psi}H$ where $\tilde{\psi}$ is a randomized test in the static problem. Coherent risk measure is used as risk measure in the $L^{\infty}$ random variable spaces. The paper is written in expository style to some degree. We use an average risk of measure(AVaR), which is a special coherent risk measure, to see how to hedge the modified claim in a complete market model.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.413-428
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• 2012

Every contingent claim is unable to be replicated in the incomplete markets. Shortfall risk is considered with some risk exposure. We show how the dynamic optimization problem with the capital constraint can be reduced to the problem to find an optimal modified claim $\tilde{\psi}H$ where$\tilde{\psi}H$ is a randomized test in the static problem. Convex and coherent risk measures defined in the Orlicz hearts spaces, $M^{\Phi}$, are used as risk measure. It can be shown that we have the same results as in [21, 22] even though convex and coherent risk measures defined in the Orlicz hearts spaces, $M^{\Phi}$, are used. In this paper, we use Fenchel duality Theorem in the literature to deduce necessary and sufficient optimality conditions for the static optimization problem using convex duality methods.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2236-2244
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• 2018

We make optimal consecutive offer curves for an energy storage system (ESS) integrated wind power producer (WPP) in the co-optimized day-ahead energy and regulation markets. We build the offer curves by solving multi-stage stochastic optimization (MSSO) problems based on the scenarios of pairs consisting of real-time price and wind power forecasts through the progressive hedging method (PHM). We also use the rolling horizon method (RHM) to build the consecutive offer curves for several hours in chronological order. We test the profitability of the offer curves by using the data sampled from the Iberian Peninsula. We show that the offer curves obtained by solving MSSO problems with the PHM and RHM have a higher profitability than offer curves obtained by solving deterministic problems.