IDEAS home Printed from
   My bibliography  Save this paper

Uncertainty and Volatility Jumps in the Pound-Dollar Exchange Rate: Evidence from Over One Century of Data


  • Konstantinos Gkillas

    (Department of Business Administration, University of Patras, Patras, Greece)

  • Rangan Gupta

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

  • Dimitrios Vortelinos

    () (Lincoln Business School, University of Lincoln, Lincoln, UK)


In this paper, we analyse the role of economic uncertainty, in predicting volatility jumps in the pound-dollar exchange rate over the monthly period of 1900:02 to 2018:05, with the jumps computed using daily data over the same period. Standard linear Granger causality test fail to detect any evidence of uncertainty causing volatility jumps. But given strong evidence of nonlinearity and structural breaks between jumps and economic uncertainty, we next use a nonparametric causality-in-quantiles test, given the misspecification of the linear model. Using this data-driven robust approach, we detect overwhelming evidence of uncertainty causing volatility jumps of the dollar-pound exchange rate over its entire conditional distribution, with the strongest effect observed at the lowest considered conditional quantile. In addition, our results are, in general, found to be robust to alternative measures of uncertainty, jumps generated at daily frequency based on shorter-samples of intraday data, and across three other dollar-based exchange rates.

Suggested Citation

  • Konstantinos Gkillas & Rangan Gupta & Dimitrios Vortelinos, 2018. "Uncertainty and Volatility Jumps in the Pound-Dollar Exchange Rate: Evidence from Over One Century of Data," Working Papers 201843, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201843

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch & Seong-Min Yoon, 2020. "OPEC News and Jumps in the Oil Market," Working Papers 202053, University of Pretoria, Department of Economics.

    More about this item


    Exchange Rates; Volatility Jumps; Uncertainty;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pre:wpaper:201843. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rangan Gupta). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.