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Forecasting the variance of stock index returns using jumps and cojumps

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  • Clements, Adam
  • Liao, Yin

Abstract

Modeling and forecasting the variance of asset returns is an important issue in many financial applications. Previous studies have examined the roles of both the continuous and jump components of the total variance in forecasting. This paper considers how index-level jumps and cojumps can be used across index constituents for forecasting the variance of index-level returns. A range of jump and cojump detection methods, based on daily and intraday data, are used. Moving beyond the magnitudes of the past index jumps used in existing models, it is found that incorporating the estimated jump intensity from a point process model leads to forecast accuracy gains. Another important contribution is the finding that cojumps across underlying constituent stocks are also useful for forecasting index-level behaviour. Improvements in forecast performance are particularly apparent on the days when jumps or cojumps occur.

Suggested Citation

  • Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
  • Handle: RePEc:eee:intfor:v:33:y:2017:i:3:p:729-742
    DOI: 10.1016/j.ijforecast.2017.01.005
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    4. Ran Xiao, 2019. "Essays on Price Discovery and Volatility Dynamics in Emerging Market Currencies," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2019, January.
    5. Elie Bouri, 2019. "The Effect of Jumps in the Crude Oil Market on the Sovereign Risks of Major Oil Exporters," Risks, MDPI, Open Access Journal, vol. 7(4), pages 1-15, December.
    6. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    7. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    8. Arif, Muhammad & Naeem, Muhammad Abubakr & Farid, Saqib & Nepal, Rabindra & Jamasb, Tooraj, 2020. "Diversifier or More? Hedge and Safe Haven Properties of Green Bonds During COVID-19," Working Papers 1-2021, Copenhagen Business School, Department of Economics.
    9. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.

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