Research on Correlation between Bitcoin and Gold Price Based on Copula Function

2021 ◽  
Vol 10 (03) ◽  
pp. 507-517
Author(s):  
媛 陈
Keyword(s):  
Author(s):  
Gabriel Ribeiro ◽  
Marcos Yamasaki ◽  
Helon Vicente Hultmann Ayala ◽  
Leandro Coelho ◽  
Viviana Mariani

2011 ◽  
Author(s):  
Jan Walters Kruger ◽  
Angelo Joseph ◽  
Abraham Aphane
Keyword(s):  

2014 ◽  
Author(s):  
Lei Ming ◽  
Shenggang Yang ◽  
Cheng Cheng
Keyword(s):  

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
T. Mesbahzadeh ◽  
M. M. Miglietta ◽  
M. Mirakbari ◽  
F. Soleimani Sardoo ◽  
M. Abdolhoseini

Precipitation and temperature are very important climatic parameters as their changes may affect life conditions. Therefore, predicting temporal trends of precipitation and temperature is very useful for societal and urban planning. In this research, in order to study the future trends in precipitation and temperature, we have applied scenarios of the fifth assessment report of IPCC. The results suggest that both parameters will be increasing in the studied area (Iran) in future. Since there is interdependence between these two climatic parameters, the independent analysis of the two fields will generate errors in the interpretation of model simulations. Therefore, in this study, copula theory was used for joint modeling of precipitation and temperature under climate change scenarios. By the joint distribution, we can find the structure of interdependence of precipitation and temperature in current and future under climate change conditions, which can assist in the risk assessment of extreme hydrological and meteorological events. Based on the results of goodness of fit test, the Frank copula function was selected for modeling of recorded and constructed data under RCP2.6 scenario and the Gaussian copula function was used for joint modeling of the constructed data under the RCP4.5 and RCP8.5 scenarios.


2006 ◽  
Vol 05 (03) ◽  
pp. 483-493 ◽  
Author(s):  
PING LI ◽  
HOUSHENG CHEN ◽  
XIAOTIE DENG ◽  
SHUNMING ZHANG

Default correlation is the key point for the pricing of multi-name credit derivatives. In this paper, we apply copulas to characterize the dependence structure of defaults, determine the joint default distribution, and give the price for a specific kind of multi-name credit derivative — collateralized debt obligation (CDO). We also analyze two important factors influencing the pricing of multi-name credit derivatives, recovery rates and copula function. Finally, we apply Clayton copula, in a numerical example, to simulate default times taking specific underlying recovery rates and average recovery rates, then price the tranches of a given CDO and then analyze the results.


Lingua ◽  
1983 ◽  
Vol 59 (2-3) ◽  
pp. 197-207 ◽  
Author(s):  
Mushira Eid
Keyword(s):  

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