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Can social microblogging be used to forecast intraday exchange rates?

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  • Panagiotis Papaioannou
  • 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. Toward 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. Copyright Springer Science+Business Media New York 2013

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  • Panagiotis Papaioannou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Netnomics, Springer, vol. 14(1), pages 47-68, November.
    • Handle: RePEc:kap:netnom:v:14:y:2013:i:1:p:47-68
    DOI: 10.1007/s11066-013-9079-3
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    2. Zhou, Wen, 2023. "Did Donald Trump's tweets on Sino–U.S. Trade affect the offshore RMB exchange rate?," Finance Research Letters, Elsevier, vol. 58(PA).
    3. 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.
    4. 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.
    5. Dietmar Janetzko, 2014. "Using Twitter to Model the EUR/USD Exchange Rate," Papers 1402.1624, arXiv.org.
    6. Thomas Dierckx & Jesse Davis & Wim Schoutens, 2020. "Using Machine Learning and Alternative Data to Predict Movements in Market Risk," Papers 2009.07947, arXiv.org.

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