分布式点对点(peer to peer,P2P)电能交易能促进能源就近达到供需平衡,在保证公平性的同时提高电网利用效率。该文提出P2P电能交易模型,并基于非对称纳什谈判(asymmetric nash bargaining,ANB)理论研究合作收益分配机制。首先,建立P2P...分布式点对点(peer to peer,P2P)电能交易能促进能源就近达到供需平衡,在保证公平性的同时提高电网利用效率。该文提出P2P电能交易模型,并基于非对称纳什谈判(asymmetric nash bargaining,ANB)理论研究合作收益分配机制。首先,建立P2P电能交易双方合作模型,二者通过合作产生合作剩余,然后基于非对称纳什谈判理论构建交易双方的收益分配模型,使得合作收益能在买卖双方间得到合理分配,最后通过算例验证所提合作博弈模型的有效性。仿真结果表明,交易双方通过合作,可以较大幅度提高各主体的运行效益以及合作联盟的整体效益,也能体现P2P电能交易卖方和买方在联盟中贡献大小的差异,可以更合理地分配合作收益。展开更多
In this paper, the author considers a new Loss-distribution-approach model, in which the over-dispersed operational risks are modeled by the compound negative binomial process. In the single dimensional case, asymptot...In this paper, the author considers a new Loss-distribution-approach model, in which the over-dispersed operational risks are modeled by the compound negative binomial process. In the single dimensional case, asymptotic expansion for the quantile of compound negative binomial process is explored for computing the capital charge of a bank for operational risk. Moreover, when the dependence structure between different risk cells is modeled by the Frank copula, this approach is extended to the multi-dimensional setting. A practical example is given to demonstrate the effectiveness of approximation results.展开更多
This paper presents the first formal comparison of Value at risk(VaR)forecasting perfor-mance across various high-frequency volatility models and conventional benchmarks using daily data in the crude oil futures marke...This paper presents the first formal comparison of Value at risk(VaR)forecasting perfor-mance across various high-frequency volatility models and conventional benchmarks using daily data in the crude oil futures market.Our analysis reveals the following key findings:(1)High-frequency data significantly enhance the accuracy of VaR forecasts.Specifically,the realized-GARCH(generalized autoregressive conditional hetero-skedasticity)model that incorporates 5-s realized bipower variation(BPV)outperforms all other models.(2)Not all realized measures are equally effective for VaR forecasting.The 5-s BPV model consistently outperforms other realized measures in forecasting VaR.(3)The choice of sampling frequency plays a crucial role in the performance of realized measures when forecasting VaR.(4)Many more sophisticated realized measures fail to surpass the simple 5-min realized variance(RV)model in forecasting VaR in the crude oil futures market.展开更多
文摘分布式点对点(peer to peer,P2P)电能交易能促进能源就近达到供需平衡,在保证公平性的同时提高电网利用效率。该文提出P2P电能交易模型,并基于非对称纳什谈判(asymmetric nash bargaining,ANB)理论研究合作收益分配机制。首先,建立P2P电能交易双方合作模型,二者通过合作产生合作剩余,然后基于非对称纳什谈判理论构建交易双方的收益分配模型,使得合作收益能在买卖双方间得到合理分配,最后通过算例验证所提合作博弈模型的有效性。仿真结果表明,交易双方通过合作,可以较大幅度提高各主体的运行效益以及合作联盟的整体效益,也能体现P2P电能交易卖方和买方在联盟中贡献大小的差异,可以更合理地分配合作收益。
基金supported by the National Natural Science Foundation of China under Grant No.11201001 in partthe Science Research Grant of Shaanxi Province under Grant No.2011JM1019the Foundation Research Project of Engineering University of CAPF under Grant No.WJY201304
文摘In this paper, the author considers a new Loss-distribution-approach model, in which the over-dispersed operational risks are modeled by the compound negative binomial process. In the single dimensional case, asymptotic expansion for the quantile of compound negative binomial process is explored for computing the capital charge of a bank for operational risk. Moreover, when the dependence structure between different risk cells is modeled by the Frank copula, this approach is extended to the multi-dimensional setting. A practical example is given to demonstrate the effectiveness of approximation results.
文摘This paper presents the first formal comparison of Value at risk(VaR)forecasting perfor-mance across various high-frequency volatility models and conventional benchmarks using daily data in the crude oil futures market.Our analysis reveals the following key findings:(1)High-frequency data significantly enhance the accuracy of VaR forecasts.Specifically,the realized-GARCH(generalized autoregressive conditional hetero-skedasticity)model that incorporates 5-s realized bipower variation(BPV)outperforms all other models.(2)Not all realized measures are equally effective for VaR forecasting.The 5-s BPV model consistently outperforms other realized measures in forecasting VaR.(3)The choice of sampling frequency plays a crucial role in the performance of realized measures when forecasting VaR.(4)Many more sophisticated realized measures fail to surpass the simple 5-min realized variance(RV)model in forecasting VaR in the crude oil futures market.
