The Experts below are selected from a list of 57894 Experts worldwide ranked by ideXlab platform
S Velusami - One of the best experts on this subject based on the ideXlab platform.
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dmlhflc dual mode linguistic Hedge fuzzy logic controller for an isolated wind diesel hybrid power system with bes battery energy storage unit
Energy, 2010Co-Authors: Mohamed Thameem M Ansari, S VelusamiAbstract:Design of DMLHFLC (dual mode linguistic Hedge fuzzy logic controller) for an isolated wind–diesel hybrid power system with BES (battery energy storage) unit is proposed in this paper. The design methodology is a hybrid model based on the concepts of linguistic Hedges and hybrid genetic algorithm-simulated annealing algorithms. Dual-mode concept is also incorporated in this proposed controller because it can improve the system performance. The system is simulated and the results are compared with proportional plus integral controller and FLC (fuzzy logic controller). Sensitivity analysis and robustness of the controller is tested. The results prove the effectiveness of the proposed controller.
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dual mode linguistic Hedge fuzzy logic controller for an isolated wind diesel hybrid power system with superconducting magnetic energy storage unit
Energy Conversion and Management, 2010Co-Authors: Md Thameem M Ansari, S VelusamiAbstract:Abstract A design of dual mode linguistic Hedge fuzzy logic controller for an isolated wind–diesel hybrid power system with superconducting magnetic energy storage unit is proposed in this paper. The design methodology of dual mode linguistic Hedge fuzzy logic controller is a hybrid model based on the concepts of linguistic Hedges and hybrid genetic algorithm-simulated annealing algorithms. The linguistic Hedge operators are used to adjust the shape of the system membership functions dynamically and can speed up the control result to fit the system demand. The hybrid genetic algorithm–simulated annealing algorithm is adopted to search the optimal linguistic Hedge combination in the linguistic Hedge module. Dual mode concept is also incorporated in the proposed controller because it can improve the system performance. The system with the proposed controller was simulated and the frequency deviation resulting from a step load disturbance is presented. The comparison of the proportional plus integral controller, fuzzy logic controller and the proposed dual mode linguistic Hedge fuzzy logic controller shows that, with the application of the proposed controller, the system performance is improved significantly. The proposed controller is also found to be less sensitive to the changes in the parameters of the system and also robust under different operating modes of the hybrid power system.
Md Thameem M Ansari - One of the best experts on this subject based on the ideXlab platform.
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dual mode linguistic Hedge fuzzy logic controller for an isolated wind diesel hybrid power system with superconducting magnetic energy storage unit
Energy Conversion and Management, 2010Co-Authors: Md Thameem M Ansari, S VelusamiAbstract:Abstract A design of dual mode linguistic Hedge fuzzy logic controller for an isolated wind–diesel hybrid power system with superconducting magnetic energy storage unit is proposed in this paper. The design methodology of dual mode linguistic Hedge fuzzy logic controller is a hybrid model based on the concepts of linguistic Hedges and hybrid genetic algorithm-simulated annealing algorithms. The linguistic Hedge operators are used to adjust the shape of the system membership functions dynamically and can speed up the control result to fit the system demand. The hybrid genetic algorithm–simulated annealing algorithm is adopted to search the optimal linguistic Hedge combination in the linguistic Hedge module. Dual mode concept is also incorporated in the proposed controller because it can improve the system performance. The system with the proposed controller was simulated and the frequency deviation resulting from a step load disturbance is presented. The comparison of the proportional plus integral controller, fuzzy logic controller and the proposed dual mode linguistic Hedge fuzzy logic controller shows that, with the application of the proposed controller, the system performance is improved significantly. The proposed controller is also found to be less sensitive to the changes in the parameters of the system and also robust under different operating modes of the hybrid power system.
Kevin Dowd - One of the best experts on this subject based on the ideXlab platform.
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longevity hedging 101 a framework for longevity basis risk analysis and Hedge effectiveness
The North American Actuarial Journal, 2011Co-Authors: Guy Coughlan, Marwa Khalafallah, Sumit Kumar, Andrew J G Cairns, David Blake, Kevin DowdAbstract:Abstract Basis risk is an important consideration when hedging longevity risk with instruments based on longevity indices, since the longevity experience of the Hedged exposure may differ from that of the index. As a result, any decision to execute an index-based Hedge requires a framework for (1) developing an informed understanding of the basis risk, (2) appropriately calibrating the hedging instrument, and (3) evaluating Hedge effectiveness. We describe such a framework and apply it to a U.K. case study, which compares the population of assured lives from the Continuous Mortality Investigation with the England and Wales national population. The framework is founded on an analysis of historical experience data, together with an appreciation of the contextual relationship between the two related populations in social, economic, and demographic terms. Despite the different demographic profiles, the case study provides evidence of stable long-term relationships between the mortality experiences of the two ...
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longevity hedging 101 a framework for longevity basis risk analysis and Hedge effectiveness
Social Science Research Network, 2011Co-Authors: Guy Coughlan, Marwa Khalafallah, Sumit Kumar, Andrew J G Cairns, David Blake, Kevin DowdAbstract:Basis risk is an important consideration when hedging longevity risk with instruments based on longevity indices, since the longevity experience of the Hedged exposure may differ from that of the index. As a result, any decision to execute an index-based Hedge requires a framework for (1) developing an informed understanding of the basis risk, (2) appropriately calibrating the hedging instrument, and (3) evaluating Hedge effectiveness. We describe such a framework and apply it to a U.K. case study, which compares the population of assured lives from the Continuous Mortality Investigation with the England and Wales national population. The framework is founded on an analysis of historical experience data, together with an appreciation of the contextual relationship between the two related populations in social, economic, and demographic terms. Despite the different demographic profiles, the case study provides evidence of stable long-term relationships between the mortality experiences of the two populations. This suggests the important result that high levels of Hedge effectiveness should be achievable with appropriately calibrated, static, index-based longevity Hedges. Indeed, this is borne out in detailed calculations of Hedge effectiveness for a hypothetical pension portfolio where the basis risk is based on the case study. A robustness check involving populations from the United States yields similar results.
Guy Coughlan - One of the best experts on this subject based on the ideXlab platform.
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longevity hedging 101 a framework for longevity basis risk analysis and Hedge effectiveness
The North American Actuarial Journal, 2011Co-Authors: Guy Coughlan, Marwa Khalafallah, Sumit Kumar, Andrew J G Cairns, David Blake, Kevin DowdAbstract:Abstract Basis risk is an important consideration when hedging longevity risk with instruments based on longevity indices, since the longevity experience of the Hedged exposure may differ from that of the index. As a result, any decision to execute an index-based Hedge requires a framework for (1) developing an informed understanding of the basis risk, (2) appropriately calibrating the hedging instrument, and (3) evaluating Hedge effectiveness. We describe such a framework and apply it to a U.K. case study, which compares the population of assured lives from the Continuous Mortality Investigation with the England and Wales national population. The framework is founded on an analysis of historical experience data, together with an appreciation of the contextual relationship between the two related populations in social, economic, and demographic terms. Despite the different demographic profiles, the case study provides evidence of stable long-term relationships between the mortality experiences of the two ...
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longevity hedging 101 a framework for longevity basis risk analysis and Hedge effectiveness
Social Science Research Network, 2011Co-Authors: Guy Coughlan, Marwa Khalafallah, Sumit Kumar, Andrew J G Cairns, David Blake, Kevin DowdAbstract:Basis risk is an important consideration when hedging longevity risk with instruments based on longevity indices, since the longevity experience of the Hedged exposure may differ from that of the index. As a result, any decision to execute an index-based Hedge requires a framework for (1) developing an informed understanding of the basis risk, (2) appropriately calibrating the hedging instrument, and (3) evaluating Hedge effectiveness. We describe such a framework and apply it to a U.K. case study, which compares the population of assured lives from the Continuous Mortality Investigation with the England and Wales national population. The framework is founded on an analysis of historical experience data, together with an appreciation of the contextual relationship between the two related populations in social, economic, and demographic terms. Despite the different demographic profiles, the case study provides evidence of stable long-term relationships between the mortality experiences of the two populations. This suggests the important result that high levels of Hedge effectiveness should be achievable with appropriately calibrated, static, index-based longevity Hedges. Indeed, this is borne out in detailed calculations of Hedge effectiveness for a hypothetical pension portfolio where the basis risk is based on the case study. A robustness check involving populations from the United States yields similar results.
Gurdip Bakshi - One of the best experts on this subject based on the ideXlab platform.
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delta Hedged gains and the negative market volatility risk premium
Review of Financial Studies, 2003Co-Authors: Gurdip Bakshi, Nikunj KapadiaAbstract:We investigate whether the volatility risk premium is negative by examining the statistical properties of delta-Hedged option portfolios (buy the option and Hedge with stock). Within a stochastic volatility framework, we demonstrate a correspondence between the sign and magnitude of the volatility risk premium and the mean delta-Hedged portfolio returns. Using a sample of S&P 500 index options, we provide empirical tests that have the following general results. First, the delta-Hedged strategy underperforms zero. Second, the documented underperformance is less for options away from the money. Third, the underperformance is greater at times of higher volatility. Fourth, the volatility risk premium significantly affects delta-Hedged gains, even after accounting for jump fears. Our evidence is supportive of a negative market volatility risk premium. Copyright 2003, Oxford University Press.
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delta Hedged gains and the negative market volatility risk premium
Review of Financial Studies, 2003Co-Authors: Gurdip Bakshi, Nikunj KapadiaAbstract:We investigate whether the volatility risk premium is negative by examining the statistical properties of delta-Hedged option portfolios (buy the option and Hedge with stock). Within a stochastic volatility framework, we demonstrate a correspondence between the sign and magnitude of the volatility risk premium and the mean delta-Hedged portfolio returns. Using a sample of S&P 500 index options, we provide empirical tests that have the following general results. First, the delta-Hedged strategy underperforms zero. Second, the documented underperformance is less for options away from the money. Third, the underperformance is greater at times of higher volatility. Fourth, the volatility risk premium significantly affects delta-Hedged gains, even after accounting for jump fears. Our evidence is supportive of a negative market volatility risk premium. The notion that volatility of equity returns is stochastic has a firm footing in financial economics. However, a less than understood phenomenon is whether volatility risk is compensated, and whether this compensation is higher or lower than the risk-free rate. Is the risk from changes in market volatility positively correlated with the economy-wide pricing kernel process? If so, how does it affect the equity and option markets? Evidence that market volatility risk premium may be nonzero can be motivated by three empirical findings: Purchased options are Hedges against significant market declines. This is because increased realized volatility coincides with downward market moves [French, Schwert, and Stambaugh (1987) and Glosten, Jagannathan,
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delta Hedged gains and the negative market volatility risk premium
Social Science Research Network, 2001Co-Authors: Nikunj Kapadia, Gurdip BakshiAbstract:We investigate whether the volatility risk premium is negative by examining the statistical properties of delta-Hedged option portfolios (buy the option and Hedge with stock). Within a stochastic volatility framework, we demonstrate a correspondence between the sign and magnitude of the volatility risk premium and the mean delta-Hedged portfolio returns. Using a sample of S&P 500 index options, we provide empirical tests that have the following general results. First, the delta-Hedged strategy underperforms zero. Second, the documented underperformance is less for options away from the money. Third, the underperformance is greater at times of higher volatility. Fourth, the volatility risk premium significantly affects delta-Hedged gains even after accounting for jump-fears. Our evidence is supportive of a negative market volatility risk premium.
