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Can social microblogging be used to forecast intraday exchange rates?

Author

Listed:
  • Panagiotis Papaioannnou
  • Lucia Russo
  • George Papaioannou
  • Constantinos Siettos

Abstract

The Efficient Market Hypothesis (EMH) is widely accepted to hold true under certain assumptions. One of its implications is that the prediction of stock prices at least in the short run cannot outperform the random walk model. Yet, recently many studies stressing the psychological and social dimension of financial behavior have challenged the validity of the EMH. Towards this aim, over the last few years, internet-based communication platforms and search engines have been used to extract early indicators of social and economic trends. Here, we used Twitter's social networking platform to model and forecast the EUR/USD exchange rate in a high-frequency intradaily trading scale. Using time series and trading simulations analysis, we provide some evidence that the information provided in social microblogging platforms such as Twitter can in certain cases enhance the forecasting efficiency regarding the very short (intradaily) forex.

Suggested Citation

  • Panagiotis Papaioannnou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Papers 1310.5306, arXiv.org.
    • Handle: RePEc:arx:papers:1310.5306
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    1. Iori, Giulia, 2002. "A microsimulation of traders activity in the stock market: the role of heterogeneity, agents' interactions and trade frictions," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 269-285, October.
    2. Milgrom, Paul & Stokey, Nancy, 1982. "Information, trade and common knowledge," Journal of Economic Theory, Elsevier, vol. 26(1), pages 17-27, February.
    3. Jacob Gyntelberg & Mico Loretan & Tientip Subhanij & Eric Chan, 2010. "Private information, stock markets, and exchange rates," BIS Papers chapters, in: Bank for International Settlements (ed.), The international financial crisis and policy challenges in Asia and the Pacific, volume 52, pages 186-210, Bank for International Settlements.
    4. MacDonald, Ronald & Taylor, Mark P., 1994. "The monetary model of the exchange rate: long-run relationships, short-run dynamics and how to beat a random walk," Journal of International Money and Finance, Elsevier, vol. 13(3), pages 276-290, June.
    5. Philippe Bacchetta & Eric Van Wincoop, 2006. "Can Information Heterogeneity Explain the Exchange Rate Determination Puzzle?," American Economic Review, American Economic Association, vol. 96(3), pages 552-576, June.
    6. Groen, Jan J. J., 2000. "The monetary exchange rate model as a long-run phenomenon," Journal of International Economics, Elsevier, vol. 52(2), pages 299-319, December.
    7. Menzie D. Chinn & Guy Meredith, 2004. "Monetary Policy and Long-Horizon Uncovered Interest Parity," IMF Staff Papers, Palgrave Macmillan, vol. 51(3), pages 409-430, November.
    8. Chaboud, Alain P. & Wright, Jonathan H., 2005. "Uncovered interest parity: it works, but not for long," Journal of International Economics, Elsevier, vol. 66(2), pages 349-362, July.
    9. Carpenter, Jeffrey P, 2002. "Evolutionary Models of Bargaining: Comparing Agent-Based Computational and Analytical Approaches to Understanding Convention Evolution," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 25-49, February.
    10. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    11. Markus Knauff & Claudia Budeck & Ann G Wolf & Kai Hamburger, 2010. "The Illogicality of Stock-Brokers: Psychological Experiments on the Effects of Prior Knowledge and Belief Biases on Logical Reasoning in Stock Trading," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-6, October.
    12. Armin Shmilovici & Yoav Kahiri & Irad Ben-Gal & Shmuel Hauser, 2009. "Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 33(2), pages 131-154, March.
    13. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
    14. Anders Johansen, 2004. "Origin of Crashes in 3 US stock markets: Shocks and Bubbles," Papers cond-mat/0401210, arXiv.org.
    15. Johan Almenberg & Ken Kittlitz & Thomas Pfeiffer, 2009. "An Experiment on Prediction Markets in Science," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-7, December.
    16. Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
    17. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    18. Erika Corona & Sabrina Ecca & Michele Marchesi & Alessio Setzu, 2008. "The Interplay Between Two Stock Markets and a Related Foreign Exchange Market: A Simulation Approach," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 99-119, September.
    19. Hon, Mark T. & Strauss, Jack K. & Yong, Soo-Keong, 2007. "Deconstructing the Nasdaq bubble: A look at contagion across international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(3), pages 213-230, July.
    20. Steiglitz, Ken & Shapiro, Daniel, 1998. "Simulating the Madness of Crowds: Price Bubbles in an Auction-Mediated Robot Market," Computational Economics, Springer;Society for Computational Economics, vol. 12(1), pages 35-59, August.
    21. Marsili, Matteo & Raffaelli, Giacomo, 2006. "Risk bubbles and market instability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 18-22.
    22. Kuan, Chung-Ming & Liu, Tung, 1995. "Forecasting Exchange Rates Using Feedforward and Recurrent Neural Networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 347-364, Oct.-Dec..
    23. Johansen, Anders, 2004. "Origin of crashes in three US stock markets: shocks and bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 135-142.
    24. Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.
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    2. Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis & Diamantaras, Konstantinos, 2015. "Market sentiment and exchange rate directional forecasting," Algorithmic Finance, IOS Press, vol. 4(1-2), pages 69-79.
    3. Constantin Colonescu, 2018. "The Effects of Donald Trump's Tweets on US Financial and Foreign Exchange Markets," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 4(4), pages 375-388, October.
    4. Dietmar Janetzko, 2014. "Predictive modeling in turbulent times – What Twitter reveals about the EUR/USD exchange rate," Netnomics, Springer, vol. 15(2), pages 69-106, September.
    5. Dietmar Janetzko, 2014. "Using Twitter to Model the EUR/USD Exchange Rate," Papers 1402.1624, arXiv.org.

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