Markit study confirms social media sentiment measures are effective signals of future stock performance
Markit, a leading global diversified provider of financial information services, today announced that it has partnered with Social Market Analytics (SMA) to provide new signals of investor sentiment designed to help customers inform their trading strategies or investment process. The social media indicators enhance the Markit Research Signals suite of more than 400 investment factors which can be used by customers to evaluate the expected performance of stocks-based sentiment indicators.
An analytical study of the social media signals entitled “#Alpha: Extracting Market Sentiment from 140 Characters” concluded that the signals accurately and consistently predict future stock returns. From December 2011 to November 2013, Markit’s analysis found positive social media sentiment stocks have shown cumulative returns of 76% while negative sentiment stocks have returned -14%.
Markit’s social media indicators are based on SMA’s analysis of the text content in daily Twitter posts. Tweets are filtered for financial trading relevance and scored for market sentiment content. Using aggregate Tweet data to identify potential buy and sell candidates, the indicators gauge investor outlook on stocks covering the following broad categories: tweet sentiment, tweet volume, relative value, changing sentiment and dispersion.
Tim Sargent, Managing Director and Head of Markit Indices, said: “In today’s exceptionally competitive investment arena, timely new insights are key to investment success. We are pleased to offer our customers SMA’s social media indicators which our research shows will differentiate their investment research and strategies."
Joe Gits, President and CEO of Social Market Analytics, added: “We’re delighted to have been selected by Markit to be their exclusive provider of social sentiment signals. Their vetting and testing process is rigorous, so it is significant that their independent study found our social sentiment signals highly predictive of specific stock movement.”
SMA data analyses social media streams to estimate market sentiment. SMA’s patent pending process extracts relevant tweets, validates the source and evaluates the meaning. Metrics are converted into actionable indicators called S-FactorsTM designed to capture financial market sentiment.
Markit has introduced 22 social media indicators, using SMA sentiment data, to its existing library of 400 factors. Markit’s factors span 12 categories, including measures of relative value, earnings momentum, earnings quality and price momentum. These signals are included in Markit’s factor analytics platform, a fully integrated research and signal management platform which allows seamless custom model building and strategy deployment for equity and fixed income.
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