SMA Team - Context Analytics - Page 2

Weekly S-Volume Lookback for Daily Trading

July 28, 2022

The goal of this research project was to aggregate sentiment factors to maximize future stock returns. The factor used for this project was an aggregate of S-Volume, which is the raw number of indicative Tweets in the previous 24 hours by company. Sentiment data is taken from the 3:40 PM ET timestamp (20 minutes before […]

GMRF Increases Coverage to Include ESG Documents

July 18, 2022

Social Market Analytics released U.S. Machine Readable Filings (MRF) in partnership with S&P Global Market Intelligence in April 2020. Machine Readable Filings is the first product to provide parsed textual data of SEC Edgar Regulatory Filings at the Document, Part, Item, Section, and Notes level with historical baselines back to 2006. Global Machine Readable Filings (GMRF) was released in April 2021 […]

Using Twitter Sentiment for Day Trading

June 21, 2022

My name is Campbell Taylor. I am a rising senior and a Statistics major at The Ohio State University. Through my first few weeks as a Quantitative Research Intern for Social Market Analytics I’ve been exposed to alternative data and its applications in the financial market. In this research, I created a day trading strategy […]

S-Factor Introduction Video Blog

May 10, 2022

Our S-factor metrics have harnessed the power of social media to benefit investors. The online discussions of the Stockmarket online greatly effects the market. By filtering through over 500 million tweets a day, SMA metrics ingests the full firehose for topics of interest from Twitter, Stocktwits and more with 10+ years or out of sample […]

SMA Launches TSX Asset Class to Social Media Feeds

April 12, 2022

Social Market Analytics converts textual data into quantitative signals for the investment community. To complement our U.S. Equity feed, we recently launch a Twitter based sentiment feed covering the largest TSX (Toronto Stock Exchange) equities. The initial universe included 233 TSX equities, and recently expanded to include an additional 200+ equities. The out-of-sample date for […]

Ukraine War Impact on Corporate Filings

March 21, 2022

Social Market Analytics released U.S. Machine Readable Filings (MRF) in partnership with S&P Global Market Intelligence in April 2020. Machine Readable Filings is the first product to provide parsed textual data of SEC Edgar Regulatory Filings at the Document, Part, Item, Section, and Notes level with historical baselines back to 2006. Global Machine Readable Filings (GMRF) […]

Alpha Around the World: Insights into Global Annual Reports

November 1, 2021

Social Market Analytics (SMA) has created the Global Machine Readable Filings (GMRF) dataset in partnership with S&P Global Market Intelligence. GMRF provides parsed textual data broken down to sections along with metrics like word count and sentiment on annual and interim reports for companies around the world. Extraneous information such as images, tables, and page […]

S-Score's Performance on Recent Earnings

September 14, 2021

In this analysis we are testing whether SMA’s S-Factor data is accurate predicting price movements in equities during earnings season. The dataset we look at includes all US Equities in SMA’s universe, covering over 4,500 equites, that released earnings between 1/13/2020 and 8/16/2021. We first looked at Open-to-Close returns after earnings have been released. […]

Global MRF - The First of its Kind

July 28, 2021

Social Market Analytics, Inc. (SMA) in April 2021 released Global Machine Readable Filings (GMRF) in partnership with S&P Global Market Intelligence. Global Machine Readable Filings is the first product to provide parsed textual data of over 200 Countries Company Annual Reports, Quarterly Report, Semi-Annual and Financial Supplements across ~1.6M documents. This blog will explore details […]

Using Twitter Social Media for One-Month Holding Periods

June 21, 2021

Social Market Analytics, Inc. (SMA) has been warehousing and normalizing social media signals, called S-Factors, since December 2011. SMA has collected nearly 10 years of out-of-sample data, which allows back tests of longer holding periods. SMA’s typical S-Factors are a daily view on social sentiment and is great at predicting subsequent price movement in securities […]

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