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Modeling exchange rate return volatility of RMB/USD using GARCH family models

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  • Agya Atabani Adi

Abstract

The paper examines volatility of RMB exchange rate return of onshore and offshore markets. The onshore rate covered 4/01/2008–5/09/2016 while offshore spanned 31/12/2008-22/09/2016, the returns were not normally distributed and were integrated of order zero I(0). The Ljung-Box Q statistics depicts the presence of autocorrelation in return series and Ljung-Box Q2 statistics of power transformed for conditional heteroscedasticity for lags of 6, 12 and 20 all indicated the presence of conditional heteroscedascity. The exchange rates volatility was persistent in both markets. However, offshore return was more persistent while leverage effects exist in both markets. Asymmetry power Autoregressive conditional Heteroscedastic (APARCH) model was the best model for forecasting purposes in both markets while Glosten, Jogannathan and Rankle, Generalized Autoregressive conditional Heteroscedastic (GJR-GARCH) model and Integrated Generalized Autoregressive conditional Heteroscedastic (I-GARCH) were the worst models in onshore and offshore return markets respectively. APARCH model should be adopted for future studies.

Suggested Citation

  • Agya Atabani Adi, 2019. "Modeling exchange rate return volatility of RMB/USD using GARCH family models," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 17(2), pages 169-187, April.
  • Handle: RePEc:taf:jocebs:v:17:y:2019:i:2:p:169-187
    DOI: 10.1080/14765284.2019.1600933
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    Cited by:

    1. KHATTAB Ahmed & SALMI Yahya, 2021. "Modeling Sources of Asymmetry in the Volatility of the Moroccan Dirham Exchange Rate," Applied Economics and Finance, Redfame publishing, vol. 8(4), pages 31-41, July.
    2. Emmanuel Afuecheta & Idika E. Okorie & Saralees Nadarajah & Geraldine E. Nzeribe, 2024. "Forecasting Value at Risk and Expected Shortfall of Foreign Exchange Rate Volatility of Major African Currencies via GARCH and Dynamic Conditional Correlation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 271-304, January.

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