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Today I will explore decile groupings based on S-Scores, and  plot cumulative subsequent returns. We typically focus on an S-Score > 2 for subsequent positive movements in stock prices, and an S-Score < -2 for negative movements in stock price.

Our metrics identify when a conversation becomes significantly more positive or negative than normal.  Most stocks have normal conversations on any given day.  On these days there are other factors driving the security. “Normal” conversation securities will typically follow the market, as you see in the SMA data set.  High sentiment out-performs and low sentiment under-performs,  Open to Close, and Close to Close, across Twitter and StockTwits.

The only filter we add is that the prior day’s closing price must be above $5, to avoid penny stocks.  Total return time series are used for returns, and time series are equal weighted.

The first chart illustrates subsequent Open to Close returns based on S-Score deciles at 9:10 a.m. Eastern time. As you can see, the deciles are in order with top decile securities out-performing and bottom decile securities under-performing.  SPY is represented by the black line and the universe is blue.

Twitter-Pre-Open

Pre-Market Close deciles are below.  S-Scores are taken at 3:40 p.m. Eastern and Close to Close returns are calculated.  Again, high S-Score securities out-perform and low S-Score securities under-perform, with the universe in the middle.

Twitter-Pre-Close-Close

StockTwits is the largest chat community for active traders.  Its users are professional traders discussing long and short positions. The below chart looks at S-Score decile returns based on StockTwits conversations.

Data is consistent across deciles.  A unique characteristic of the StockTwits feed is that there are significant short conversations.  The lowest two deciles have negative returns.  This is a function of the StockTwits community being able to short securities by direct short selling or taking net short options positions.

StockTwits PreOpen

Pre-market close deciles are below.

StockTwits CLose-close

To learn more about Social Market Analytics and the products we offer please visit our website, or contact us here.

Thanks,

Joe

People seem surprised that Britain voted to exit the EU.  We at SMA with our partners the CBOE are not nearly as surprised as everyone else.  Russell Rhoads from the CBOE has been blogging and Tweeting with SMA data for two weeks that it looks like the Brexit is going to happen.  Let’s look at the timeline.  Again, this is not a post analysis, these Tweets were out there 2 weeks ago!

Brexit Post on June 8, 2016:

Russell Rhoads, from CBOE wrote a blog about Brexit using the using SSE, the results indicated that an Exit is going to be the result of the vote.

Brexit1

The update from our partners at CBOE talked about the huge increase in Twitter volume about #brexit. One of the key observations was the #VoteLeave campaign had gained far more popularity than the remain campaign. To everyone who was looking, Twitter had shown the signs of a British Exit.

Brexit2

The final post on June 22 talked about strong social media indicators towards the exit. The #VoteLeave campaign has dwarfed the conversations of every other opinion, including the BBC debate. The prediction turned out to be true.

Brexit3

Twitter is the premier leading source of information and SMA can help you make sense of it.  Please contact SMA for more information at contactus@socialmarketanalytics.com