Social Market Analytics partners with IHS Markit to distribute our S-Factor data through the IHS Markit Research Signals Feed. Recently, IHS Markit added our LSE 1000 Equity S-Factor Feed to their data offerings. In conjunction with the launch IHS Markit authored a research paper exploring the predictive nature of the SMA S-Factor data on LSE equity securities. We are thrilled with the outcome of this independent research showing the predictive nature of Twitter based factors. Below is summary of the paper conclusion section.
Download the paper here: https://cdn.ihs.com/www/pdf/0219/Social_media_indicators_in_the_UK.pdf
IHS Markit focused primarily on the SMA's S-Score and S-Volume sentiment metrics. SMA S-Scores open-to-close return spreads at the +/-2 tail averaged .097%, persistent to 10-day (.177%) and 20-day (.298%) holding periods. On a cumulative basis, we report a pre-close spread return of 75% for buy rated stocks versus 6% for sell rated stocks and 9% for the market. Results were robust to filters on minimum Tweets and to long-only strategies. Applying the S-Volume > 1 filter, open to close spreads for the +/-2 tail strategy average .83%, and exceeded the stand-alone factor results at each of the longer holding periods. For buy portfolios, S-Score (with S-Volume >1) open-to-close excess returns at the +2 tail averaged .044% (0.049%) and increased in general with each incremental extension in holding period reaching 0.296% (0.389%) at 20 days, confirming the benefits of signal to long-only portfolio managers.
Lastly IHS Markit researched one of their proprietary SMA based metrics, Relative Standard Deviation of Indicative Tweet Volume. They also found strong results, Stocks with volatile Tweet volume pre-market tend to outperform open-to-close (spread:0.224%, excess return 0.07%), while these stocks also outperform over longer time horizons, reaching a spread of .342% out to 20 days (excess return: .196%).
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Thanks,
Joe
