scholarly journals Non-parametric estimation of time varying AR(1)–processes with local stationarity and periodicity

2018 ◽  
Vol 12 (2) ◽  
pp. 2323-2354 ◽  
Author(s):  
Jean-Marc Bardet ◽  
Paul Doukhan
Author(s):  
Jinguo Gong ◽  
Weiou Wu ◽  
David McMillan ◽  
Daimin Shi

AbstractThe correlation structure of financial assets is a key input with regard to portfolio and risk management. In this paper, we propose a non-parametric estimation method for the time-varying copula parameter. This is achieved in two steps: first, displaying the marginal distributions of financial asset returns by applying the empirical distribution function; second, by implementing the local likelihood method to estimate the copula parameters. The method for obtaining the optimal bandwidth through a maximum pseudo likelihood function and a statistical test on whether the copula parameter is time-varying are also introduced. A simulation study is conducted to show that our method is superior to its contender. Finally, we verify the proposed estimation methodology and time-varying statistical test by analysing the dynamic linkages between the Shanghai, Shenzhen and Hong Kong stock markets.


2009 ◽  
Vol 20 (2) ◽  
pp. 111-130 ◽  
Author(s):  
Ronaldo Dias ◽  
Nancy L. Garcia ◽  
Angelo Martarelli

2002 ◽  
Vol 335 (2) ◽  
pp. 183-188 ◽  
Author(s):  
Vilijandas Bagdonavičius ◽  
Algis Bikelis ◽  
Vytautas Kazakevičius ◽  
Mikhail Nikulin

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