Long memory estimation in a non-Gaussian bivariate process
作者：
Highlights：
• We analyze fluctuations of foreign currency exchange rates and to identify / describe the dependence structure in stochastic processes.
• We focus on the dependence relationship between two currencies and the stochastic process underlying them.
• A general novel methodology is introduced for bivariate financial time series possibly possessing heavy tails.
• This methodology can be used as powerful tool to improve the prediction of exchange rate fluctuations.
摘要
•We analyze fluctuations of foreign currency exchange rates and to identify / describe the dependence structure in stochastic processes.•We focus on the dependence relationship between two currencies and the stochastic process underlying them.•A general novel methodology is introduced for bivariate financial time series possibly possessing heavy tails.•This methodology can be used as powerful tool to improve the prediction of exchange rate fluctuations.
论文关键词：Non-Gaussian process,Student t distribution,Copula function,Hurst parameter,Discrete wavelet transform,GTCLM model
论文评审过程：Received 2 February 2021, Revised 10 December 2021, Accepted 12 December 2021, Available online 30 December 2021, Version of Record 30 December 2021.
论文官网地址：https://doi.org/10.1016/j.amc.2021.126871
