IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/21122.html
   My bibliography  Save this paper

High-frequency, Algorithmic Spillovers Between NASDAQ and Forex

Author

Listed:
  • 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
    Note: IFM
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w21122.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gradojevic, Nikola & Erdemlioglu, Deniz & Gençay, Ramazan, 2020. "A new wavelet-based ultra-high-frequency analysis of triangular currency arbitrage," Economic Modelling, Elsevier, vol. 85(C), pages 57-73.
    2. Hughes, John S & Liu, Jing & Liu, Jun, 2005. "Information, Diversification, and Cost of Capital," University of California at Los Angeles, Anderson Graduate School of Management qt82j2d59r, Anderson Graduate School of Management, UCLA.
    3. Marcelo Pinheiro, 2005. "Informational asymmetries and a multiplier effect on price correlation and trading," Annals of Finance, Springer, vol. 1(4), pages 395-421, October.
    4. Wu, Zhen-Xing & Gau, Yin-Feng & Chen, Yu-Lun, 2023. "Price discovery and triangular arbitrage in currency markets," Journal of International Money and Finance, Elsevier, vol. 137(C).
    5. Takatoshi Ito & Kenta Yamada & Misako Takayasu & Hideki Takayasu, 2020. "Execution Risk and Arbitrage Opportunities in the Foreign Exchange Markets," NBER Working Papers 26706, National Bureau of Economic Research, Inc.
    6. Gehrig, Thomas & Jackson, Matthew, 1998. "Bid-ask spreads with indirect competition among specialists," Journal of Financial Markets, Elsevier, vol. 1(1), pages 89-119, April.
    7. Lei Wu & Kuan Xu & Qingbin Meng, 2021. "Information flow and price discovery dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 329-367, January.
    8. Frijns, Bart & Indriawan, Ivan & Tourani-Rad, Alireza, 2018. "The interactions between price discovery, liquidity and algorithmic trading for U.S.-Canadian cross-listed shares," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 136-152.
    9. Säfvenblad, Patrik, 1997. "Lead-Lag Effects When Prices Reveal Cross-Security Information," SSE/EFI Working Paper Series in Economics and Finance 189, Stockholm School of Economics.
    10. Giovanni Cespa, 2008. "Information Sales and Insider Trading with Long‐Lived Information," Journal of Finance, American Finance Association, vol. 63(2), pages 639-672, April.
    11. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    12. Alex Frino & Michael Garcia & Zeyang Zhou, 2020. "Impact of algorithmic trading on speed of adjustment to new information: Evidence from interest rate derivatives," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 749-760, May.
    13. Yu-Lun Chen & Yin-Feng Gau & Wen-Ju Liao, 2016. "Trading activities and price discovery in foreign currency futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 793-818, May.
    14. Chen, Yu-Lun & Gau, Yin-Feng, 2015. "Foreign exchange market intervention and price discovery," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 214-227.
    15. Ibikunle, Gbenga & Aquilina, Matteo & Diaz-Rainey, Ivan & Sun, Yuxin, 2021. "City goes dark: Dark trading and adverse selection in aggregate markets," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 1-22.
    16. Ligot, Stephanie & Gillet, Roland & Veryzhenko, Iryna, 2021. "Intraday volatility smile: Effects of fragmentation and high frequency trading on price efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    17. Jing Nie, 2019. "High‐Frequency Price Discovery and Price Efficiency on Interest Rate Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(11), pages 1394-1434, November.
    18. Roszkowska Paulina & Prorokowski Łukasz, 2013. "Model of Financial Crisis Contagion: A Survey-based Simulation by Means of the Modified Kaplan-Meier Survival Plots," Folia Oeconomica Stetinensia, Sciendo, vol. 13(1), pages 22-55, December.
    19. Ibikunle, Gbenga, 2018. "Trading places: Price leadership and the competition for order flow," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 178-200.
    20. Arumugam, Devika & Krishna Prasanna, P., 2021. "Commonality and contrarian trading among algorithmic traders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:nbr:nberwo:21122. See general information about how to correct material in RePEc.

    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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.