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High-frequency, Algorithmic Spillovers Between NASDAQ and Forex

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  • Takatoshi Ito
  • Masahiro Yamada

Abstract

We empirically examine the order flows spillovers between Nasdaq and the Forex markets in 2008 and 2009. With emphasis on a role of high-frequency traders (HFTs) who aggregate information between the two markets as well as within each market, our results show that HFTs in Nasdaq trade intensively on the market-wide information more rapidly than other market participants, and that their order flows contain more information about the Forex rates than those of the Forex themselves. As a result, order flows by HFTs in Nasdaq significantly lead those in the Forex activities. Reflecting each market's exposures to the common shocks during the Global Financial crisis, these spillovers vary over time, and HFTs have increased their influences. These empirical results are consistent with theoretical predictions of the rational expectations model of multi-asset trading.

Suggested Citation

  • Takatoshi Ito & Masahiro Yamada, 2015. "High-frequency, Algorithmic Spillovers Between NASDAQ and Forex," NBER Working Papers 21122, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:21122
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    References listed on IDEAS

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    1. Ito, Takatoshi & Hashimoto, Yuko, 2006. "Intraday seasonality in activities of the foreign exchange markets: Evidence from the electronic broking system," Journal of the Japanese and International Economies, Elsevier, vol. 20(4), pages 637-664, December.
    2. Takatoshi Ito & Kenta Yamada & Misako Takayasu & Hideki Takayasu, 2012. "Free Lunch! Arbitrage Opportunities in the Foreign Exchange Markets," NBER Working Papers 18541, National Bureau of Economic Research, Inc.
    3. Laura E. Kodres & Matthew Pritsker, 2002. "A Rational Expectations Model of Financial Contagion," Journal of Finance, American Finance Association, vol. 57(2), pages 769-799, April.
    4. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    5. Admati, Anat R, 1985. "A Noisy Rational Expectations Equilibrium for Multi-asset Securities Markets," Econometrica, Econometric Society, vol. 53(3), pages 629-657, May.
    6. Caballe, Jordi & Krishnan, Murugappa, 1994. "Imperfect Competition in a Multi-security Market with Risk Neutrality," Econometrica, Econometric Society, vol. 62(3), pages 695-704, May.
    7. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
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    Cited by:

    1. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    2. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.

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    More about this item

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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