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The role of jumps in volatility spillovers in foreign exchange markets: meteor shower and heat waves revisited

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Abstract

This paper extends the previous literature on geographic (heat waves) and intertemporal (meteor showers) foreign exchange volatility transmission to characterize the role of jumps and cross-rate propagation. We employ heterogeneous autoregressive (HAR) models to capture the quasi-long-memory properties of volatility and the Shapley-Owen R2 measure to quantify the contributions of components. We conclude that meteor showers are more influential than heat waves, that jumps play a modest but significant role in volatility transmission and that significant, bidirectional cross-rate volatility transmission exists. Finally, we illustrate what types of news weaken or strengthen heat wave and meteor shower effects with sensitivity analysis.

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  • Jerome Lahaye & Christopher J. Neely, 2014. "The role of jumps in volatility spillovers in foreign exchange markets: meteor shower and heat waves revisited," Working Papers 2014-034, Federal Reserve Bank of St. Louis.
    • Handle: RePEc:fip:fedlwp:2014-034
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    2. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.
    3. Su, Fei & Wang, Xinyi & Yuan, Yulin, 2022. "The intraday dynamics and intraday price discovery of bitcoin," Research in International Business and Finance, Elsevier, vol. 60(C).
    4. 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.
    5. Su, Fei, 2021. "Conditional volatility persistence and volatility spillovers in the foreign exchange market," Research in International Business and Finance, Elsevier, vol. 55(C).
    6. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018.
    7. Su, Fei & Zhang, Jingjing, 2018. "Global price discovery in the Australian dollar market and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 35-55.
    8. Weijia Peng & Chun Yao, 2022. "Co-Jumps, Co-Jump Tests, and Volatility Forecasting: Monte Carlo and Empirical Evidence," JRFM, MDPI, vol. 15(8), pages 1-21, July.
    9. repec:uts:finphd:38 is not listed on IDEAS

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    More about this item

    Keywords

    intraday; volatility; euro; exchange rates; transmission; dollar.; jumps; periodicity; yen; meteor shower; realized; heat wave;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • F65 - International Economics - - Economic Impacts of Globalization - - - Finance
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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