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ANN-Time Varying GARCH Model: Simulations and Application in Modelling Temperature for Weather Derivatives
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作者 Elias K. Karuiru John Mwaniki Kihoro +1 位作者 Thomas Mageto Anthony Gichuhi Waititu 《Open Journal of Statistics》 2022年第3期433-441,共9页
In economics and finance, minimising errors while building an abstract representation of financial assets plays a critical role due to its application in areas such as risk management, decision making and option prici... In economics and finance, minimising errors while building an abstract representation of financial assets plays a critical role due to its application in areas such as risk management, decision making and option pricing. Despite the many methods developed to handle this problem, modelling processes with fixed and random periodicity still remains a major challenge. Such methods include Artificial Neural networks (ANN), Fuzzy Inference system (FIS), GARCH models and their hybrids. This study seeks to extend literature of hybrid ANN-Time Varying GARCH model through simulations and application in modelling weather derivatives. The study models daily temperature of Kenya using ANN-Time Varying GARCH (1, 1), Time Lagged Feedforward neural network (TLNN) and periodic GARCH family models. Mean square error (MSE) and coefficient of determination R<sup>2</sup> were used to determine performance of the models under study. Results obtained show that the ANN-Time Varying GARCH model gives the best results. 展开更多
关键词 Artificial Neural Network Time Varying GARCH weather derivatives TEMPERATURE
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Rational Identification of Lightning Derivative Disasters by Strong Convective Weather Monitoring Data in Southern China——A Case Study in Guangzhou Development Region
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作者 Chen Xiao Lin Yan Cheng Ming 《Meteorological and Environmental Research》 CAS 2015年第2期16-19,共4页
Analytic method and identification direction for rational identification of lightning derivative disasters by strong convective weather monitoring data in southern China were introduced. Taking identification cases of... Analytic method and identification direction for rational identification of lightning derivative disasters by strong convective weather monitoring data in southern China were introduced. Taking identification cases of lightning disaster in Guangzhou Development Region as the background,according to the characteristics in the region that large high-precision enterprises were more,lightning derivative disasters occurred frequently in thunderstorm season,and the actual situation that time of the affected enterprise applying for lightning disaster scene identification lagged,combining Technical Specifications of Lightning Disaster Investigation( QX / T103-2009),qualitative analysis method of lightning derivative disaster was put forward under the weather condition of strong convection in southern China by using weather monitoring data( Doppler sounding radar data,lightning positioning monitoring data,atmospheric electric field data,rainfall data,wind direction and force),and was optimized by technical means( " metallographic method" and " remanence law"). The research could put forward efficient and convenient analytical thinking and method for lightning derivative disaster,and further optimize accuracy and credibility of lightning disaster investigation. 展开更多
关键词 Strong convection weather monitoring data Lightning derivative disaster Identification China
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