Use case: Intelligent news tagging for retail investor activity monitoring


 Following the GameStop (GME) Reddit saga and retail investors’ massive involvement, some equities experience unprecedented volatility that particularly exposes investors with short positions.


Flag potential retail activity on portfolio listings & quantitative investment strategies.


  • Python/R
  • Natural Language Processing


A dashboard that automatically gathers and analyses data from 9’000 news sources (incl. Reddit and Google trends) producing early warning signals of potential retail activity. In connection with Cleo’s portfolio engine, the signals are crossed with institution’s equity portfolio and provide live feedback and risk flags based on Cleo’s simulation engine. The data scrapping tool can also be used in combination with our option lab that is linked with live option data. This allows to detect trading opportunities based on underpriced tail risks. The strategy makes multiple small bets that have a high payoff and an underpriced probability of occurrence.


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