Proceedings of 9th International Business and Social Science Research Conference
6 - 8 January, 2014, Novotel World Trade Centre, Dubai, UAE, ISBN: 978-1-922069-41-2
Social Chatter and Asset Bubbles: The Rise and fall of Bitcoin
Alexis Antoniades, Touhami Abi* and Mohamed Al-Hinai
In November of 2008, a research paper was posted on server by a person calling himself Satoshi
Nakamoto describing how he had created a new digital coin called bitcoin. In the paper, Satoshi explained
how he solved the challenges that doomed past attempts to introduce virtual currencies. Satoshi's ability to
overcome challenges faced by previous digital currencies in addition to the implications of the financial
crisis of 2008 and that in Europe starting from 2011, helped Bitcoin to gain popularity and appreciate in
value.
In this project we study how social media and social chatter have contributed to the rise and fall of bitcoin.
What is nice about the bitcoin bubble is that we can follow online chatter on twitter and see how changes in
the amount of chatter relates to the changing value of bitcoin. To our understanding, this is the first study
on asset bubbles that uses data from social media to check how chatter affects prices. Several studies in
finance look at the impact of media attention on asset prices (e.g. stock mentions on Wall Street Journal,
Bloomberg, Jim Cramer on CNBC and Yahoo Fiannce), but these studies do not consider asset bubbles
and consider only mainsteam media and even when social media are considered (such as Yahoo
Finance), those media are specific to a target audience inlike Tweeter which is inclussive to all kinds of
audiences. Moreover, since bubbles are formed when the public starts speculating into an asset, then, it is
more appropriate to use social media such as Tweeter in order to capture the disscussion of the general
public and understand its implications on the formation of asset bubbles.
We empirically test whether social chatter correlates with the rise in value of bitcoin. We do find that time
series for Tweets are cointegrated with price of Bitcoin. We condact a Granger causality test in order to
determine the direction of the correlation in order to understand whether price of Bitcoin pulls disscussion
or disscussion pulls price during asset bubbles. A Chow test was applied to check for structural breaks in
the relation between periods, and a Vector Error Correction Model (VECM) was estimated for each period.
We finaly conduct a forecasting exercise in order to determine whether social chatter helps predict Bitcoin
price by using different models such as Vector Autoregressive Model (VAR) and VECM. We find that
adding Tweets improves forecast.
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*
Mr. Touhami Abi, School of Foreign Service, Georgetown University, Doha, Qatar.