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Jumps in equilibrium prices and asymmetric news in foreign exchange markets

Author

Listed:
  • Imane El Ouadghiri

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Remzi Uctum

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this paper we examine the intraday effects of surprises from scheduled macroeconomic announcements and unscheduled event news on six major exchange rate excess returns (jumps) using a Tobit model with conditionally heteroskedastic errors that we extend so as to account for asymmetries. Besides this novel model, our approach embodies several important features: we perform Lee and Mykland's (2012) non-parametric test procedure to filter out microstructure noise from observed exchange rates and extract jumps as the significant "equilibrium" returns; various categories of information news from different geographical regions are exploited; the hypothesis of a leverage effect on foreign exchange jumps due to asymmetric volatility shocks is examined. We found that the most influential scheduled macroeconomic news are globally related to the US job markets, output growth indicators and public debt, whereas significant event news include announcements of bank failures and government rescue plans. Surprises impact Forex jumps for about one third as a result of rather pessimistic forecasts due to the crisis period analyzed. For most of the currencies the hypothesis that negative volatility shocks have a-greater impact on volatility than positive shocks of the same magnitude is validated, reflecting markets' concern about the costs implied by central bank's stabilization policies. Our findings provide evidence that the major foreign exchange markets are not efficient
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Suggested Citation

  • Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01411808, HAL.
    • Handle: RePEc:hal:journl:hal-01411808
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    2. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš, 2019. "Central bank announcements and realized volatility of stock markets in G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 117-135.
    3. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    4. El Ouadghiri, Imane & Peillex, Jonathan, 2018. "Public attention to “Islamic terrorism” and stock market returns," Journal of Comparative Economics, Elsevier, vol. 46(4), pages 936-946.
    5. Barda, Kelly, 2020. "Analyser la performance financière des indices boursiers environnementaux [Analyzing financial performance of green stock market indices]," MPRA Paper 102537, University Library of Munich, Germany.
    6. Mendiela, Pauline, 2021. "Information security breaches and financial market reaction: the French case," MPRA Paper 105029, University Library of Munich, Germany.
    7. Alexandra Huang, 2019. "Déterminants des encours nationaux socialement responsables : Une analyse exploratoire internationale," Working Papers hal-02242796, HAL.
    8. Gong, Xiaoli & Zhuang, Xintian, 2017. "Pricing foreign equity option under stochastic volatility tempered stable Lévy processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 83-93.
    9. Grabowski, Wojciech & Welfe, Aleksander, 2020. "The Tobit cointegrated vector autoregressive model: An application to the currency market," Economic Modelling, Elsevier, vol. 89(C), pages 88-100.
    10. Gong, Xiaoli & Zhuang, Xintian, 2017. "Measuring financial risk and portfolio reversion with time changed tempered stable Lévy processes," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 148-159.
    11. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).

    More about this item

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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