AI Trendsetter YUKKA Lab Launches Its Market Sentiment Analysis Tools at Finovate London

  • Artificial Intelligence
  • 20.02.2018 09:10 am

Market sentiments tend to change a few weeks before the market follows. That’s not news but so far sentiment analysis tools were delayed and imprecise. YUKKA Lab changes this dramatically.

The company will launch its new YUKKA News &  Trend Lab cockpit and API/Interface at Finovate London, March 6-8.  

The Natural Language Processing (NLP) and machine learning (ML) based software sifts through millions of financial news items across the globe searching for swings of sentiment in the financial market.

YUKKA Lab’s technology is based on algorithms that fully automated, in real-time and without any emotions allow users to reliably anticipate market moods, opinions and trends and adjust strategies accordingly. Sentiments are fed only from audited sources and renowned financial news such as AWP (+ AWP Archiv), dpa-AFX, NewsEdge by Acquire Media. YUKKA does not include Social media to avoid manipulation by for example “Fake News”. This improves the quality of data and reduces noise and manipulation.

These newly launched products are already successfully applied to the first sentiment-based fund, the Sentiment SICAV Europe 600, which is being managed by Belvoir Capital. Plus Falcon Private Bank can talk about how with the new early detection system, the YUKKA News & Trend Lab complements their broadly based investment process in an important area: the market sentiment. Thanks to YUKKA Lab’s innovative approach, it gives Falcon’s investment processes a head start over traditional approaches.

The Finovate YUKKA demo will be on Tuesday, March 6th during session one (which runs from 8.45am to 190.15am).

Andreas Pusch, CEO & Founder and Oliver Berchtold, CBD & Co-Founder, are also available for 1-to-1 interviews at the show and/or are happy to give you a preview via GoToMeeting before the show. Should you want to test the software at your own pace, please get in touch for a review login.

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