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Extreme returns: The case of currencies

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  • Osler, Carol
  • Savaser, Tanseli

Abstract

Financial market crashes can occur even in the absence of news. This paper highlights four properties of price-contingent trading that increase the frequency of such events. Price-contingent trading is common across financial market, since it includes algorithmic trading, technical trading, and dynamic option hedging. The four properties we consider are: (1) high kurtosis in the distribution of order sizes; (2) clustering of trades within the day; (3) clustering of trades at certain prices; and (4) feedback between trading and returns. The paper estimates the relative importance of these factors using data from the foreign exchange market. Calibrated simulations indicate that interactions among these factors are at least as important as any single one. Among individual factors, the orders' size distribution and feedback effects have the strongest influence. Overall, price-contingent trading could account for half of realized excess kurtosis. The paper suggests that extreme returns unaccompanied by news are statistically inevitable in the presence of price-contingent trading.

Suggested Citation

  • Osler, Carol & Savaser, Tanseli, 2011. "Extreme returns: The case of currencies," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2868-2880, November.
  • Handle: RePEc:eee:jbfina:v:35:y:2011:i:11:p:2868-2880
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    Cited by:

    1. Lallouache, Mehdi & Abergel, Frédéric, 2014. "Tick size reduction and price clustering in a FX order book," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 488-498.
    2. Patrick Steffen Michelberger & Jan Hendrik Witte, 2015. "Foreign Exchange Market Microstructure and the WM/Reuters 4pm Fix," Papers 1501.07778, arXiv.org, revised Feb 2016.
    3. Erdemlioglu, Deniz & Laurent, Sébastien & Neely, Christopher J., 2015. "Which continuous-time model is most appropriate for exchange rates?," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 256-268.
    4. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    5. King, Michael R. & Osler, Carol L. & Rime, Dagfinn, 2013. "The market microstructure approach to foreign exchange: Looking back and looking forward," Journal of International Money and Finance, Elsevier, vol. 38(C), pages 95-119.
    6. Cotter, John & Dowd, Kevin, 2010. "Intra-day seasonality in foreign exchange market transactions," International Review of Economics & Finance, Elsevier, vol. 19(2), pages 287-294, April.
    7. Gradojevic, Nikola & Erdemlioglu, Deniz & Gençay, Ramazan, 2017. "Informativeness of trade size in foreign exchange markets," Economics Letters, Elsevier, vol. 150(C), pages 27-33.
    8. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.

    More about this item

    Keywords

    Crash risk Fat tails Exchange rates High frequency Microstructure Jump process Value-at-risk;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • F3 - International Economics - - International Finance

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