A growing body of industry and academic research demonstrates that media sentiment has an independent and uncorrelated influence on stock prices versus traditional quantitative factors. Now there's a model that effectively extracts the predictive potential of news and social media tone and distills it into simple 1-100 daily percentile rankings for thousands of U.S. stocks.
Listen to this webinar, and see how easy it is to leverage news and social media sentiment into alpha-generating insights. With the Starmine MarketPsych Media Sentiment (MMS) model, we'll look at the fascinating web of causality between news, sentiment, fundamentals, and stock prices.
Anthony Luciani is a quantitative analyst at MarketPsych where he researches media sentiment data, investor behavioural biases, and their predictive significance across asset classes. Prior to MarketPsych, he received his Master's in Financial Mathematics and Computation at the University of Leicester in the UK and worked with OptiRisk Systems in the field of sentiment analysis. During his work on the StarMine MarketPsych Media Sentiment data, Anthony integrated investor sentiment with financial theory to develop outperforming stock ranking models
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