Can social microblogging be used to forecast intraday exchange rates?

Papaioannou, Panagiotis; Russo, Lucia; Papaioannou, George P.; Siettos, Constantinos

doi:10.1007/s11066-013-9079-3

Cited by 25 publications

(16 citation statements)

References 64 publications

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“…In the same vein of short term effects, P. Papaioannou, Russo, Papaioannou, and Siettos (2013) use Twitter information to model and predict high frequency daily fluctuations of the EUR/USD exchange rate. They notice, first, that more and more studies challenge the efficient market hypothesis and suggest including information gathered from social media into time series models to forecast exchange rates.…”

Section: Using Social Media To Forecast Stock Pricesmentioning

confidence: 99%

The Effects of Donald Trump’s Tweets on US Financial and Foreign Exchange Markets

Colonescu¹

2018

AJBE

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Twitter is the US president's, Donald Trump, preferred media for communicating his thoughts to his followers. This project looks at the effect of the daily flow of Donald Trump's tweets on the US financial and foreign exchange markets, represented by the Dow Jones Industrial Average (DJI) index and some exchange rates, over the period of Donald Trump's ongoing presidency. Using text mining techniques, some correlation is found between various moving average window lengths of tweet content and the DJI index. Some short term and lasting effects are also detected on US-Canada and US composite exchange rates.

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Section: Using Social Media To Forecast Stock Pricesmentioning

confidence: 99%

The Effects of Donald Trump’s Tweets on US Financial and Foreign Exchange Markets

Colonescu¹

2018

AJBE

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“…Papaioannou, Russo, Papaioannou, and Siettos (2013) analyze 20,250 tweets related to the EUR/USD exchange rate over the period (2010)(2011) to extract information about the types of orders that each Twitter user had made, and the target-price of each of these orders. The findings provide supportive evidence of the role of this information in predicting the very short (intra-daily) foreign exchange rate.…”

Section: Twitter Sentiment/information and Exchange Ratesmentioning

confidence: 99%

Twitter, Investor Sentiment and Capital Markets: What Do We Know?

Ali¹

2018

IJEF

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Nowadays, the social media play a central role not only in "de-asymmetrizing" the information between firms and investors but also in influencing the emotional response to this information. The social media have provided firms with the opportunity to construct their image and stimulate significant attention and positive emotional responses (i.e. celebrity firm). Investors also become no longer passive participants; they can now communicate, re-tweet, comment, mention, react to information and express their sentiment/views. Theoretically, this should exert a positive impact on information diffusion and so the market efficiency. However, as the social media also significantly influence the public mood and emotional response to any new information/news, several behavioral explanations contradicting with the concept of market efficiency (e.g. investor sentiment and herding behavior) become more reasonable. The study aims at providing a literature review and synthesis of research on the impact of social media sentiment in the context of capital markets, scrutinizing the theoretical understanding of this impact, underlining the methodological challenges related to extracting the sentiment, and reviewing the main empirical findings on the impact in the context of Twitter and StockTwits, which will enable researchers to evaluate and classify existing studies, obtain useful insight into the theoretical understanding of the impact of social media sentiment, hence spurring further theoretical and empirical research.

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“…Papaioannou et al [5] reported that the information gleaned from microblogging platforms such as Twitter can enhance the forecasting efficiency of Intraday exchange rates. The analysis has shown that efficient market hypothesis supports the analysis of public discussions on Twitter, and vice versa.…”

Section: Efficient Market Hypothesismentioning

confidence: 99%

A Study on Efficient Market Hypothesis to Predict Exchange Rate Trends Using Sentiment Analysis of Twitter Data

Komariah¹,

Machbub²,

Prihatmanto³

et al. 2016

Journal of Korea Multimedia Society

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Efficient Market Hypothesis (EMH), states that at any point in time in a liquid market security prices fully reflect all available information. This paper presents a study of proving the hypothesis through daily Twitter sentiments using the hybrid approach of the lexicon-based approach and the naïve Bayes classifier. In this research we analyze the currency exchange rate movement of Indonesia Rupiah vs US dollar as a way of testing the Efficient Market Hypothesis. In order to find a correlation between the prediction sentiments from Twitter data and the actual currency exchange rate trends we collect Twitter data every day and compute the overall sentiment to label them as positive or negative. Experimental results have shown 69% correct prediction of sentiment analysis and 65.7% correlation with positive sentiments. This implies that EMH is semi-strong Efficient Market Hypothesis, and that public information provide by Twitter sentiment correlate with changes in the exchange market trends.

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Can social microblogging be used to forecast intraday exchange rates?

Cited by 25 publications

References 64 publications

The Effects of Donald Trump’s Tweets on US Financial and Foreign Exchange Markets

The Effects of Donald Trump’s Tweets on US Financial and Foreign Exchange Markets

Twitter, Investor Sentiment and Capital Markets: What Do We Know?

A Study on Efficient Market Hypothesis to Predict Exchange Rate Trends Using Sentiment Analysis of Twitter Data

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