DocumentCode
3158045
Title
Notice of Retraction
Weather derivatives pricing based on Ornstein-Uhlenbeck model under time series assumption
Author
Yong Li ; Min Xia ; Juan Liu
Author_Institution
Sch. of Econ. & Manage., Tongji Univ., Shanghai, China
fYear
2011
fDate
8-10 Aug. 2011
Firstpage
6087
Lastpage
6090
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As an innovative product in foreign financial market, weather derivatives provide new ways for risk managing and transference. Its pricing is a core problem in researches. This paper applies the Ornstein-Uhlenbeck model, combining by time series assumption to simulate the variance of weather process, estimates the parameters using Shanghai´s temperature data of years 1951-2009. Then the accuracy of this model will be testified. The result indicated that which can improve the accuracy of temperature forecasting level and complete weather derivatives pricing process reasonably by adopting Monte Carlo simulation.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As an innovative product in foreign financial market, weather derivatives provide new ways for risk managing and transference. Its pricing is a core problem in researches. This paper applies the Ornstein-Uhlenbeck model, combining by time series assumption to simulate the variance of weather process, estimates the parameters using Shanghai´s temperature data of years 1951-2009. Then the accuracy of this model will be testified. The result indicated that which can improve the accuracy of temperature forecasting level and complete weather derivatives pricing process reasonably by adopting Monte Carlo simulation.
Keywords
Monte Carlo methods; innovation management; international finance; pricing; risk management; stochastic processes; time series; weather forecasting; Monte Carlo simulation; Ornstein-Uhlenbeck model; Shanghai temperature data; foreign financial market; risk management; risk transference; temperature forecasting; time series; weather derivatives pricing; Indexes; Mathematical model; Meteorology; Pricing; Temperature distribution; Temperature measurement; Time series analysis; Monte Carlo simulation; Ornstein-Uhlenbeck model; time series; weather derivatives;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location
Dengleng
Print_ISBN
978-1-4577-0535-9
Type
conf
DOI
10.1109/AIMSEC.2011.6009754
Filename
6009754
Link To Document