Momentum, Mean-Reversion and Social Media: Evidence from StockTwits and Twitter

22 Pages Posted: 1 Jul 2018 Last revised: 22 Jul 2018

See all articles by Shreyash Agrawal

Shreyash Agrawal

Massachusetts Institute of Technology (MIT), Students

Pablo Azar

Massachusetts Institute of Technology, Sloan School of Management, Students

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Taranjit Singh

Massachusetts Institute of Technology (MIT), Students

Date Written: June 17, 2018

Abstract

We analyze the relation between stock market liquidity and real-time measures of sentiment obtained from the social-media platforms StockTwits and Twitter. Linear regression analysis shows that extreme sentiment corresponds to higher demand and lower supply of liquidity, with negative sentiment having a much larger effect on demand and supply than positive sentiment. An intraday event study shows that booms and panics end when bullish and bearish sentiment reach extreme levels, respectively. After extreme sentiment, prices become more mean-reverting and spreads narrow. To quantify the magnitudes of these effects, we conduct a historical simulation of a market-neutral mean-reversion strategy that uses social-media information to determine its portfolio allocations. Our results suggest that the demand and supply of liquidity are influenced by investor sentiment, and that market makers who can keep their transaction costs to a minimum are able to profit by using extreme bullish and bearish emotions in social media as a real-time barometer for the end of momentum and a return to mean reversion.

Keywords: Sentiment, Market Liquidity, Social Media, Twitter, StockTwits, Mean Reversion, Momentum

JEL Classification: G11, G12

Suggested Citation

Agrawal, Shreyash and Azar, Pablo and Lo, Andrew W. and Singh, Taranjit, Momentum, Mean-Reversion and Social Media: Evidence from StockTwits and Twitter (June 17, 2018). Available at SSRN: https://ssrn.com/abstract=3197874 or http://dx.doi.org/10.2139/ssrn.3197874

Shreyash Agrawal

Massachusetts Institute of Technology (MIT), Students ( email )

Cambridge, MA
United States

Pablo Azar

Massachusetts Institute of Technology, Sloan School of Management, Students ( email )

Cambridge, MA 02139
United States

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Stata Center
Cambridge, MA 02142
United States

Taranjit Singh

Massachusetts Institute of Technology (MIT), Students ( email )

Cambridge, MA
United States

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