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Which continuous-time model is most appropriate for exchange rates?

Author

Listed:
  • Deniz Erdemlioglu

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Sébastien Laurent

    (LKB (Lhomond) - Laboratoire Kastler Brossel - FRDPENS - Fédération de recherche du Département de physique de l'Ecole Normale Supérieure - ENS Paris - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique - UPMC - Université Pierre et Marie Curie - Paris 6 - CNRS - Centre National de la Recherche Scientifique, GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Christopher J. Neely

Abstract

This paper evaluates the most appropriate ways to model diffusion and jump features of high-frequency exchange rates in the presence of intraday periodicity in volatility. We show that periodic volatility distorts the size and power of conventional tests of Brownian motion, jumps and (in)finite activity. We propose a correction for periodicity that restores the properties of the test statistics. Empirically, the most plausible model for 1-min exchange rate data features Brownian motion and both finite activity and infinite activity jumps. Test rejection rates vary over time, however, indicating time variation in the data generating process. We discuss the implications of results for market microstructure and currency option pricing.

Suggested Citation

  • Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2015. "Which continuous-time model is most appropriate for exchange rates?," Post-Print hal-01457402, HAL.
    • Handle: RePEc:hal:journl:hal-01457402
    DOI: 10.1016/j.jbankfin.2015.09.014
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    Cited by:

    1. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    2. Kam Fong Chan & Phil Gray & Zheyao Pan, 2021. "The profitability of trading on large Lévy jumps," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 627-635, June.
    3. Hizmeri, Rodrigo & Izzeldin, Marwan & Urga, Giovanni, 2025. "Identifying the underlying components of high-frequency data: Pure vs jump diffusion processes," Journal of Empirical Finance, Elsevier, vol. 81(C).
    4. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    5. Jérôme Lahaye & Christopher Neely, 2020. "The Role of Jumps in Volatility Spillovers in Foreign Exchange Markets: Meteor Shower and Heat Waves Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 410-427, April.

    More about this item

    Keywords

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G01 - Financial Economics - - General - - - Financial Crises

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