Wavelet-based multi-resolution GARCH model for financial spillover effects

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

This study proposes a wavelet-based multi-resolution BEKK-GARCH model to investigate spillover effects across financial markets. Compared with traditional multivariate GARCH analysis, the proposed model can identify or decompose cross-market spillovers on multiple resolutions. Taking two highly correlated indices, the NASDAQ (U.S.) and TWSI (Taiwan composite stock index) for analysis, the empirical results show that the NASDAQ returns strongly predict the movements of TWSI on the raw data level, but via wavelet-based multi-resolution analysis we find that the prediction power unevenly spreads over each time scale, and the spillover patterns are totally different as that revealed on the raw data level. The direction and magnitude of return and volatility spillovers significantly vary with their time scales. Considering the fact that heterogeneous groups of investors trade on different time horizons, the results of this study help investors to uncover the complex pattern of return and volatility spillovers on their own horizon, and make a good hedge on their risk.

Original languageEnglish
Pages (from-to)2529-2539
Number of pages11
JournalMathematics and Computers in Simulation
Volume81
Issue number11
DOIs
Publication statusPublished - 2011 Jul 1

Fingerprint

Stock Index
GARCH Model
Taiwan
Multiresolution
Volatility
Horizon
Wavelets
Time Scales
Composite
Multivariate GARCH
Multiresolution analysis
Multiresolution Analysis
Composite materials
Financial Markets
Vary
Decompose
Predict
Prediction
Model
Movement

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)
  • Numerical Analysis
  • Modelling and Simulation
  • Applied Mathematics

Cite this

@article{2cf236b0b6754ad78f1e5e10be9d61d3,
title = "Wavelet-based multi-resolution GARCH model for financial spillover effects",
abstract = "This study proposes a wavelet-based multi-resolution BEKK-GARCH model to investigate spillover effects across financial markets. Compared with traditional multivariate GARCH analysis, the proposed model can identify or decompose cross-market spillovers on multiple resolutions. Taking two highly correlated indices, the NASDAQ (U.S.) and TWSI (Taiwan composite stock index) for analysis, the empirical results show that the NASDAQ returns strongly predict the movements of TWSI on the raw data level, but via wavelet-based multi-resolution analysis we find that the prediction power unevenly spreads over each time scale, and the spillover patterns are totally different as that revealed on the raw data level. The direction and magnitude of return and volatility spillovers significantly vary with their time scales. Considering the fact that heterogeneous groups of investors trade on different time horizons, the results of this study help investors to uncover the complex pattern of return and volatility spillovers on their own horizon, and make a good hedge on their risk.",
author = "Huang, {Shian Chang}",
year = "2011",
month = "7",
day = "1",
doi = "10.1016/j.matcom.2011.04.003",
language = "English",
volume = "81",
pages = "2529--2539",
journal = "Mathematics and Computers in Simulation",
issn = "0378-4754",
publisher = "Elsevier",
number = "11",

}

Wavelet-based multi-resolution GARCH model for financial spillover effects. / Huang, Shian Chang.

In: Mathematics and Computers in Simulation, Vol. 81, No. 11, 01.07.2011, p. 2529-2539.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Wavelet-based multi-resolution GARCH model for financial spillover effects

AU - Huang, Shian Chang

PY - 2011/7/1

Y1 - 2011/7/1

N2 - This study proposes a wavelet-based multi-resolution BEKK-GARCH model to investigate spillover effects across financial markets. Compared with traditional multivariate GARCH analysis, the proposed model can identify or decompose cross-market spillovers on multiple resolutions. Taking two highly correlated indices, the NASDAQ (U.S.) and TWSI (Taiwan composite stock index) for analysis, the empirical results show that the NASDAQ returns strongly predict the movements of TWSI on the raw data level, but via wavelet-based multi-resolution analysis we find that the prediction power unevenly spreads over each time scale, and the spillover patterns are totally different as that revealed on the raw data level. The direction and magnitude of return and volatility spillovers significantly vary with their time scales. Considering the fact that heterogeneous groups of investors trade on different time horizons, the results of this study help investors to uncover the complex pattern of return and volatility spillovers on their own horizon, and make a good hedge on their risk.

AB - This study proposes a wavelet-based multi-resolution BEKK-GARCH model to investigate spillover effects across financial markets. Compared with traditional multivariate GARCH analysis, the proposed model can identify or decompose cross-market spillovers on multiple resolutions. Taking two highly correlated indices, the NASDAQ (U.S.) and TWSI (Taiwan composite stock index) for analysis, the empirical results show that the NASDAQ returns strongly predict the movements of TWSI on the raw data level, but via wavelet-based multi-resolution analysis we find that the prediction power unevenly spreads over each time scale, and the spillover patterns are totally different as that revealed on the raw data level. The direction and magnitude of return and volatility spillovers significantly vary with their time scales. Considering the fact that heterogeneous groups of investors trade on different time horizons, the results of this study help investors to uncover the complex pattern of return and volatility spillovers on their own horizon, and make a good hedge on their risk.

UR - http://www.scopus.com/inward/record.url?scp=79959319611&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79959319611&partnerID=8YFLogxK

U2 - 10.1016/j.matcom.2011.04.003

DO - 10.1016/j.matcom.2011.04.003

M3 - Article

AN - SCOPUS:79959319611

VL - 81

SP - 2529

EP - 2539

JO - Mathematics and Computers in Simulation

JF - Mathematics and Computers in Simulation

SN - 0378-4754

IS - 11

ER -