What we can learn from tweets which predict movement of euro-dollar currency pair?

Interesting paper. As traders share their predictions across asset classes on social media, it leads to research opportunities.

Vahid Gholampour and Eric van Wincoop analyse tweets that predict Euro-Dollar rates. They find that Tweets get the direction right but not the magnitude:

We focus on opinions posted on Twitter, because Twitter is widely used to express opinions about asset prices. Several anecdotal stories suggest that this information can be important. For example, on 13 August 2013, Carl Icahn, an activist investor, tweeted about his large position in Apple. As a result, Apple shares increased in value by more than 4% in a few seconds. We investigate what can be learned from Twitter by considering two and a half years of tweets that expressed opinions about the euro-dollar exchange rate.


We find that the direction of exchange rate changes is predicted by tweets in a way that is statistically significant. This suggests that there was information content in the tweets. But we also find that Twitter sentiment does not predict the magnitude of future exchange rate changes in a statistically significant way. Such predictability would be needed to develop trading strategies from this data. This absence of predictability based on a data-only approach is not surprising, because exchange rates are notoriously hard to predict. Twitter sentiment is only directional, and the data sample covers only two and a half years.

Also, Sharpe ratio for Tweet based trades is high indicating one could make money:

The large Sharpe ratios that we find suggest that there are significant gains from trading strategies based on Twitter sentiment. We can compare the Sharpe ratio from the TSI trading strategy to that of the popular currency carry-trade strategy based on interest differentials. Burnside et al. (2010) reported an average annualized Sharpe ratio of 0.44 for 20 currencies against the dollar based on a carry-trade strategy. A Sharpe ratio in the range [1.59, 1.78] is clearly very high by any reasonable standard. The methodology developed here could easily be applied to other currencies or portfolios of currencies, as well as other financial markets such as the stock market.



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