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Forecasting (Good and Bad) Realized Exchange-Rate Volatility: Is there a Role for Realized Skewness and Kurtosis?

Author

Listed:
  • Konstantinos Gkillas

    (Department of Business Administration, University of Patras – University Campus, Rio, Greece)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Hamburg, Germany)

Abstract

This study investigates U.S. political cycles and the impact, thereof on stock market volatility in advanced economies (Canada, France, Germany, Italy, Japan, Switzerland and the U.K.) using monthly data over the period January 1921 to December 2017. Overall, the results indicate that the type (Democratic or Republican) of presidential administration does play a role in the behaviour of stock returns, and volatility, but the results and direction of the impact are sample specific. In general, the results tend to suggest an increase in returns and volatility of other stock markets when there is a democratic government in the U.S. This study suggests that there is a need for market participants to start analysing the trajectory of a certain election, beginning at the proposed event window, in order to manage their risks and be at a stable position during these periods of uncertainties.

Suggested Citation

  • Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2018. "Forecasting (Good and Bad) Realized Exchange-Rate Volatility: Is there a Role for Realized Skewness and Kurtosis?," Working Papers 201879, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201879
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    2. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 303-315, March.

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    More about this item

    Keywords

    Exchange rates; Realized volatility; Forecasting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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