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Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting

Author

Listed:
  • Yuruixian Zhang

    (School of Business and Economics, University Putra Malaysia, Serdang 43400, Malaysia)

  • Wei Chong Choo

    (School of Business and Economics, University Putra Malaysia, Serdang 43400, Malaysia
    Laboratory of Computational Statistics and Operations Research, Institute for Mathematical Research, Serdang 43400, Malaysia)

  • Yuhanis Abdul Aziz

    (School of Business and Economics, University Putra Malaysia, Serdang 43400, Malaysia)

  • Choy Leong Yee

    (School of Business and Economics, University Putra Malaysia, Serdang 43400, Malaysia)

  • Cheong Kin Wan

    (Faculty of Business, Economics and Accounting, HELP University, Kuala Lumpur 50490, Malaysia)

  • Jen Sim Ho

    (School of Business and Economics, University Putra Malaysia, Serdang 43400, Malaysia)

Abstract

Even though both symmetric and asymmetric conceptions of news impacts are well-established in the disciplines of economics and financial markets, the effects of combining multiple news shocks on the volatility of tourism demand have not yet been delved into or gauged in any tourist destination. This work hypothesises and verifies that the news impact curve (NIC), conditional heteroscedastic volatility models, and multiple news shocks are suitable for forecasting the volatility of the Malaysian tourist industry. Among them, three primarily volatility models (GARCH, EGARCH, and GJRGARCH) are used in conjunction with five financial news shocks (FFNSs), namely the Kuala Lumpur Composite Index (KLCI), the United States Dollar Index (DXY), the stock performance of 500 large companies listed on stock exchanges (S&P500), Crude Oil (CO), and Gold Price (GP). Among the most significant findings of this study are the demonstration of monthly seasonality using conditional mean equations, asymmetry effects in EGARCH-FFNSs, and GJRGARCH-FFNSs models in conditional variance equations and 50 NICs, and the GARCH-FFNSs model’s evaluation of the persistence influence of news shocks on monthly visitor arrivals in Malaysia. The GJRGARCH-FFNSs model is the best model for Malaysian tourism demand volatility forecasting accuracy. Furthermore, KLCI and Gold Price have the most substantial impact on the number of tourists to Malaysia. In addition, it should be emphasised that the methodological framework utilised in this study can be a useful tool for creating and forecasting the performance of symmetry and asymmetry impacts on tourism demand volatility.

Suggested Citation

  • Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Cheong Kin Wan & Jen Sim Ho, 2022. "Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting," JRFM, MDPI, vol. 15(7), pages 1-47, June.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:7:p:279-:d:846424
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    References listed on IDEAS

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