Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
This paper presents an integrated granular framework of wavelet decomposition, DCC-GARCH, ADCC-GARCH, Diks-Panchenko nonlinear Granger’s causality and Diebold-Yilmaz spillover assessment techniques to understand temporal correlation, causal interplay and spillovers among volatile financial time series data exhibiting nonparametric behavior. | A wavelet approach towards examining dynamic association causality and spillovers International Journal of Data and Network Science 3 2019 23 36 Contents lists available at GrowingScience International Journal of Data and Network Science homepage www.GrowingScience.com ijds A wavelet approach towards examining dynamic association causality and spillovers Indranil Ghosha and Tamal Datta Chaudhuria a Calcutta Business School Diamond Harbour Road Bishnupur 743503 24 Paraganas South West Bengal India CHRONICLE ABSTRACT Article history This paper presents an integrated granular framework of wavelet decomposition DCC-GARCH Received October 2 2018 ADCC-GARCH Diks-Panchenko nonlinear Granger s causality and Diebold-Yilmaz spillover Received in revised format Octo- assessment techniques to understand temporal correlation causal interplay and spillovers among ber 20 2018 volatile financial time series data exhibiting nonparametric behavior. The exercise has been car- Accepted November 29 2018 Available online ried out on daily closing observations of eight financial time series. Wavelet decomposition has November 30 2018 been used to generate time varying components in which the other research models are applied to Keywords extract the interactive pattern of interaction to ascertain short and long run nexus. The findings Dynamic Association rationalize the effectiveness of the presented research framework. Causality Spillover Wavelet Decomposition Diks-Panchenko Test 2019 by the authors licensee Growing Science Canada. Diebold-Yilmaz Test 1. Introduction In today s globalized world markets have become interlinked through financial capital flows market sentiment contagion reflecting present and expected macroeconomic prospects of different economies information flows on political movements trade policies and prices of essential commodities like crude oil. Time series of certain variables contain such information and a proper analysis of these time series can improve .
