Sebastian Pokutta's Blog

Mathematics and related topics

Are twitter and friends increasing volatility in the market?

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Recently browsing the internet I found google insights, somewhat the bigger brother of google trends. There you can compare not only the trends of certain words but you can also split the results into various time / location buckets and compare them. For example you can compare the searches run in the US for “carribean” to the ones for “recession” from Jan 2007 until today resulting in something like this (blue -> carribean / red -> recession):

Picture 2

One can see that queries for “carribean” already started to drop in Jan 2008 and dropped significantly further in Sep 2008 while the ones for recession started to significantly rise in Aug/Sep 2008. In hindsight it is easy to see patterns – just search long enough – and it is not clear if they constitute any correlation.

Further, while interesting for a lot of applications, historical information is not well suited for making predictions. But there are also other services such as twitter and facebook out there where users pour in tons of data in real time. Especially the latter can be easily searched in real time for trends and phrases as well. New information is quickly propagated through the network and made available to millions of people combing for specific phrases such as, e.g., “oil” or “oil price”. The following trend search is from Twist, a twitter trend service. For any point in time a click reveals the post written – everything updated in real time:

Picture 3

Now, having information on price changes and “market research” available even faster and more immediate than ever before (and not only for those with Bloomberg or Reuters access) one might suspect that the volatility in the market increases as people might act more impulsively and emotionally (as often claimed e.g., in behavorial finance) especially if prices go down. Having a delay in the information processing chains smoothens the trading behavior, effectively reducing volatility. If these delays are reduced to instanteneous information availability (short term) volatility increases.

Another, maybe even more critical problem could be that using twitter and other mass-publication-of-micro-information services the pump-and-dump strategies for microcaps, which are illegal (under most jurisdictions), can be performed even more effectively than ever before. As spam filters got more and more effective pump-and-dump via spamming got harder and harder. But with micro-blogging the whole story changes. By definition there are no spammers as you follow somebody and you do not get unsolicitated emails/spam. Due to this there might be some special legal issues here that deserve extra attention: When somebody is writing a tweet to spread wrong information concealed as “personal opinion” and millions eavesdrop, can the person be held responsibility if wrong information leads, e.g., to a fire sale? The story goes even a bit further: other people might re-tweet or copy the story multiplying the number of readers and adding credibility to it as more and more versions of it are out there (a turbo-charged version of the Matthew effect and its generalizations) – who is going to reconstruct the time line when money is at stake and a decision has to be taken now?

Probably soon hedge funds will pop up trading these noises by mining millions of tweets for signals trying to extract some cash from the market.

Written by Sebastian

July 24, 2009 at 8:53 pm

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