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[av_heading tag='h1' padding='0' heading='Social Market Analytics' color='custom-color-heading' style='blockquote modern-quote modern-centered' custom_font='#ffffff' size='50' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='0,0,0px,0' av_uid='av-14fby'][/av_heading]

[av_heading heading='A Leader in Unstructured Financial Data' tag='h4' style='blockquote modern-quote modern-centered' size='' subheading_active='' subheading_size='15' margin='25px,,15,' padding='5' color='custom-color-heading' custom_font='#ffffff' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' av_uid='av-k798s1w5' admin_preview_bg=''][/av_heading]

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[av_heading tag='h1' padding='0' heading='Mission Statement' color='custom-color-heading' style='blockquote modern-quote modern-centered' custom_font='#ffffff' size='50' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='0px,0px,25px ,0px' av_uid='av-tgjtu'][/av_heading]

[av_heading heading='‘Be the Leader in Unstructured Financial Data’' tag='h6' style='blockquote modern-quote modern-centered' size='20' subheading_active='' subheading_size='15' margin='0px,0px,25px ,0px' padding='0' color='custom-color-heading' custom_font='#ffffff' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' av_uid='av-k74yiigs' admin_preview_bg=''][/av_heading]

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SMA has built Intellectual Property in four Major FinTech Areas:

Natural Language Processing, Textual Parsing, Topic Modeling, and Source Accuracy

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[av_heading tag='h3' padding='0' heading='About SMA' color='custom-color-heading' style='blockquote modern-quote modern-centered' custom_font='#000000' size='40' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='' av_uid='av-b8gzp'][/av_heading]

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Founded in 2011, Social Market Analytics, Inc. (SMA) goal was to harness the massive amount of unstructured financial data across both Alternative and Traditional sources into machine readable feeds and market intelligence

SMA’s DNA goes back to its predecessor firm Quantitative Analytics Inc. (QA Direct) which was acquired by Thomson Reuters (Refinitiv)

SMA provides the financial and marketing communities with new data sources to evaluate financial data sets, enhance returns, and reduce risk
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SMA’s Patented process is unique in the emerging field of AI, Machine Learning, Natural Language Processing, NLP Sentiment, Textual Parsing, Topic Modeling, and Source Rating

SMA data is specifically designed and developed to integrate with existing quantitative models commonly used in the financial industry

SMA delivers quantitative metrics through RESTful JSON APIs with latencies from 300 milliseconds to extended baselines. SMA data is delivered at the Security (Ticker) level across all Asset Classes
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[av_heading tag='h3' padding='0' heading='Alternative Data Products' color='custom-color-heading' style='blockquote modern-quote' custom_font='#000000' size='24' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin=''][/av_heading]

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SMA was one of the first firms to normalize Social Media into Predictive JSON API data feeds.  Twitter and StockTwits are processed into two separate APIs. Out-of-sample point-in-time historical data for back testing goes back to December 1, 2011
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[av_heading tag='h3' padding='0' heading='Traditional Data Products' color='custom-color-heading' style='blockquote modern-quote' custom_font='#000000' size='24' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin=''][/av_heading]

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SMA is changing the way Traditional data sets are ingested by turning any document into machine readable textual data with quantitative metric overlays.  SMA delivers Real Time APIs and provides historical baselines for quantitative analysis go back as far as 1996
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[av_iconlist_item title='Social Media APIs' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-ns7xb6']

SMA supports Quantitative Trading across Long Only and L/S, Market Making, Algorithmic Execution, Asset Management, TCA, Risk, Research, and Market Intelligence

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[av_iconlist_item title='SMA S-Factor API Feed' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-mcv2o2']

SMA S-Factor API Feed aggregates Tweets and makes a comparison to baseline to deliver 15 metrics every minute.  Snapshots can be requested at different frequencies based on a 24H lookback with a 20D baseline with decay

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[av_iconlist_item title='SMA Activity API Feed' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-l01yhu']

SMA Activity API Feed isolates and aggregates information every minute and allows clients to create their own baselines and metrics.  Ideal for both HFT for Market Making and Algo Execution and longer baselines for both trading Weekly, Monthly, and Quarterly Long Only and L/S

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[av_iconlist_item title='SMA Tweet Level API Feed' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-jj6nz6']

SMA Tweet Level API Feed delivers SMA metrics at the Tweet level from our Natural Language Processing Sentiment Scoring and SMA’s Account Rating Algorithm.  Delivered in 300 milliseconds after receiving the Tweet from Twitter or StockTwits

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[av_iconlist_item title='SMA Lexical API Feed' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-gu02wi']

SMA Lexical API Feed is an enhanced version of the Tweet Level feed.  The Lexical Feed also contains a phrase level break down of each Tweet.  The data is delivered through the API in 300 milliseconds after receiving the Tweet from Twitter or StockTwits

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[av_iconlist_item title='SMA Dashboard' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-fkgmua']

SMA’s Dashboard is highly customizable across all asset classes.  The Dashboard supports a Watchlist with a Tweet stream, live Market Sentiment Snapshot, Daily Pre-Open and Pre-Close Reports, Sentiment and Tweet Volume Charts at the Security, Sector, and Index Level

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[av_iconlist_item title='Alerts and Accuracy Feed' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-62fbiq']

SMA delivers highly Customized Alerts 24/7 to SMS and e-mail on U.S. and LSE Equities, ETFs, Commodity and Financial Futures, FX Spot and Futures Pairs, and Crypto Currencies.  SMA curates the most impactful Tweets driving the Predictive Sentiment change in SMS text and e-mail

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[av_iconlist_item title='Consulting and Customized Products' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-d35m3m']

Not all Clients can ingest data via a JSON API.  SMA supports Macro, Credit, and Event Driven Funds through consulting and customized products, reports, and programmatic delivery of data visuals

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[av_iconlist_item title='Machine Readable Filings
(in Partnership with S&P Global Market Intelligence)' link='' linktarget='' linkelement='' icon='ue812' font='entypo-fontello' av_uid='av-27x91x']
SEC Edgar Filings and International Reports Parsed into Machine-Readable text released in Real Time with historical baselines going back to 1996 with Word Counts and Sentiment across Parts, Items, Subsections, Footnotes, and Table of Contents.
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In addition to Listed Securities, SMA covers large Multi-National Private Companies to very Early Stage Start-ups.  SMA’s Topic Model Engine produces Machine Learning ‘Inclusions’ and ‘Exclusions’. Downstream, SMA Sentiment NLP, Volume, and other metrics are applied
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SMA Data supports Advertising and Market Intelligence.  SMA’s platform was built for analyzing unstructured data on the Topic Model Engine to provide pinpoint Advertising and drilled-down Market Intelligence 
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Custom Indices across Cboe, Long Only, L/S, ESG, Block Chain, CC Index, Regulatory Filings, Sectors, Market Caps
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Parsed tabular data using SEC Edgar’s new format for tagging Financial Filing Data
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[av_heading tag='h2' padding='0' heading='SMA Sentiment NLP' color='custom-color-heading' style='blockquote modern-quote' custom_font='#ffffff' size='24' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='' av_uid='av-2n73w'][/av_heading]

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SMA started with Stanford Tokenization and discovered that we would have to build our own Machine Learning Natural Language Processing platform.  SMA uses a multi-pass approach combining techniques like stemming and lemmatization. SMA’s environment is supervised and unsupervised, and uses programmatic regression analysis

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[av_heading tag='h2' padding='0' heading='SMA Parsing Engine' color='custom-color-heading' style='blockquote modern-quote' custom_font='#ffffff' size='24' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='' av_uid='av-21q9o'][/av_heading]

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SMA has built a general document parser to produce structured data in the form of machine-readable JSON.  Algorithms and historical baselines can be built to generate Alpha and actionable Market Intelligence 
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[av_heading tag='h2' padding='0' heading='SMA Topic Engine' color='custom-color-heading' style='blockquote modern-quote' custom_font='#ffffff' size='24' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='' av_uid='av-5hms'][/av_heading]

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To capture information related to a Security, Private Company, or Custom Topic, SMA has built a Real Time Machine Learning Topic Model Engine that uses Collocation to identify Inclusions and Exclusions.  Topics are constructed using a rules-based system grounded in qualitative knowledge
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[av_heading tag='h2' padding='0' heading='SMA Source Rating' color='custom-color-heading' style='blockquote modern-quote' custom_font='#ffffff' size='24' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='' av_uid='av-tayo'][/av_heading]

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It is not just what is being said in Traditional and Social Media, it is who is saying it. SMA has developed a twelve-factor algorithm to score each source before inclusions in sentiment and volume metrics. The ability to eliminate spam, bad bots, bad actors produces a pure data set 
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[av_heading tag='h3' padding='0' heading='Team' color='custom-color-heading' style='blockquote modern-quote modern-centered' custom_font='#ffffff' size='50' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='0px,0px,35px ,0px' av_uid='av-14vst'][/av_heading]

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Founded in 2011, Social Market Analytics, Inc. has been in Warehousing, Normalizing, and Productizing Data since our predecessor firm Quantitative Analytics, Inc. (QA Direct) was acquired by Thomson Reuters.  SMA's team has both Financial and FinTech background

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[av_heading tag='h3' padding='10' heading='Management Team' color='' style='blockquote modern-quote modern-centered' custom_font='' size='40' subheading_active='' subheading_size='15' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='' av_uid='av-3b059'][/av_heading]

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[av_image src='https://contextanalytics-ai.com/wp-content/uploads/2018/05/joe-gits.jpg' attachment='124' attachment_size='full' align='center' styling='no-styling' hover='' link='' target='' caption='' font_size='' appearance='' overlay_opacity='0.4' overlay_color='#000000' overlay_text_color='#ffffff' copyright='' animation='fade-in' av_uid='av-jhouo300' admin_preview_bg=''][/av_image]

[av_heading tag='h3' padding='0' heading='Joe Gits CFA' color='' style='blockquote modern-quote' custom_font='' size='28' subheading_active='subheading_below' subheading_size='16' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='10px,0px,0px,0px' av_uid='av-2kojd']
CEO and Co-Founder
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Joe is a pioneer in the emergence and growth of quantitative trading systems. Prior to launching Social Market Analytics, Inc. (SMA), he co-founded Quantitative Analytics, Inc. (QA Direct), a market-leading provider of integrated database solutions for quantitative researchers and traders
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[av_image src='https://contextanalytics-ai.com/wp-content/uploads/2018/05/umair-rafiq.jpg' attachment='209' attachment_size='full' align='center' styling='no-styling' hover='' link='' target='' caption='' font_size='' appearance='' overlay_opacity='0.4' overlay_color='#000000' overlay_text_color='#ffffff' copyright='' animation='fade-in' av_uid='av-jhouo300' admin_preview_bg=''][/av_image]

[av_heading tag='h3' padding='0' heading='Umair Rafiq ' color='' style='blockquote modern-quote' custom_font='' size='28' subheading_active='subheading_below' subheading_size='16' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='10px,0px,0px,0px' av_uid='av-24561']
CTO
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Umair joined from Thomson Reuters and brings extensive experience in developing Financial Applications across various platforms and design architectures.  Umair's work focuses on large scale Server Applications and the development of SMA's Intellectual Property
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[av_image src='https://contextanalytics-ai.com/wp-content/uploads/2018/05/kim-gits.jpg' attachment='125' attachment_size='full' align='center' styling='no-styling' hover='' link='' target='' caption='' font_size='' appearance='' overlay_opacity='0.4' overlay_color='#000000' overlay_text_color='#ffffff' copyright='' animation='fade-in' av_uid='av-jhouo300' admin_preview_bg=''][/av_image]

[av_heading tag='h3' padding='0' heading='Kim Herndon ' color='' style='blockquote modern-quote' custom_font='' size='28' subheading_active='subheading_below' subheading_size='16' custom_class='' admin_preview_bg='' av-desktop-hide='' av-medium-hide='' av-small-hide='' av-mini-hide='' av-medium-font-size-title='' av-small-font-size-title='' av-mini-font-size-title='' av-medium-font-size='' av-small-font-size='' av-mini-font-size='' margin='10px,0px,0px,0px' av_uid='av-1ck6t']
CFO
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Kim holds SMA accountable to shareholders and manages the company’s financial operation.  Kim has a B.S. from Indiana University and an MBA from University of Chicago.  Kim has worked at Continental Bank, First Chicago, Bank of Montreal, and JP Morgan as a credit analyst and in derivatives
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Doug has spent his career in investment bank investor services prime finance and futures focused on global equities and fixed income having lived in Chicago, London, and Tokyo.  Doug brings a Trading and CRM focus to SMA's data and its global growth in both alternative and traditional data 
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Monthly Portfolio using Twitter Raw-S

December 6, 2023

Using Social Sentiment from Twitter messages can enhance security selection. Aggregating raw sentiment over monthly periods can be used to create portfolios that outperform industry benchmarks by over 3% annually.

UDT Overview

November 29, 2023

The UDT innovative platform is designed to enhance the flow of information from unique sources, providing a comprehensive view for users seeking valuable insights. This blog aims to delve into the various features and tools offered by the UDT, showcasing how it significantly enhances daily market intelligence.   

OpenAI Twitter Sentiment

November 20, 2023

Beginning Friday, 11/17/23, alerts triggered on abnormally high volume for OpenAI. These alerts showed an abnormally high volume for the topic. This was in response to the Tweet below, which is a statement by the OpenAI board, which explains CEO Sam Altman has departed the company.

Cape PDF Extraction Blog

November 15, 2023

CAPE parses financial metrics in a wide range of unique PDF formats. When dealing with a large volume of PDFs or PowerPoint slides, manually sifting through all these metrics and comparing them can be a time-consuming endeavor. CAPE saves time to spend more time on analysis and move faster than competitors.

Monthly Portfolio using Twitter S-Buzz

November 8, 2023

Messages from Twitter provide useful information for security selection. Aggregating these messages and creating social sentiment scores can yield insights. Using Context Analytics Twitter S-Buzz score, customers can create portfolios that outperform the market.

Press Release Widget Case Study

November 1, 2023

The UDT's Press Release Widget allows users to sort and filter information based on the negativity percentage. This capability can be a vital tool for investors and analysts to stay ahead of market events and mitigate risk. By monitoring the negativity ratio and the number of hits, and cross-referencing with other tools like ThemeX, investors can identify potentially market-moving events early on, allowing for informed decisions.

US Aerospace & Defense Blog

October 18, 2023

United States defense and military weapons manufacturers are publicly traded companies. Consequently, when global tensions escalate securities in this sector become more volatile and followed. Several defense stocks have seen an uptick in value due to current Middle East tensions.

StockTwits Daily Quintiles: S-Score * S-Buzz Combo Factor

October 12, 2023

Context Analytics’ S-Factor feed is the company’s most mature product. Our offering of 10+ years of sample data and 15 different sentiment factors makes this dataset unique and ideal for back testing. With this dataset, users can harness the power of social media in financial markets.

Extension: 8-K Negativity Percentage

October 4, 2023

As a follow-up to last week's 8-K Negativity Percentage blog last week, we developed a threshold strategy utilizing the Negativity Percentage. Instead of categorizing companies into tertiles, we employed a static threshold of 60% to identify companies with exceedingly negative filings. We found there is a correlation between negative 8-K filings and subsequent poor market performance.

8-K Negativity Percentage

September 28, 2023

An 8-K filing is a report filed by publicly traded companies with the U.S. Securities and Exchange Commission (SEC) to announce significant events or material information. They often contain negative news decision-makers need to react swiftly. In this blog, we explore the importance of 8-K filings, the potential negative information they can contain, and the significance of analyzing them for risk assessment.

CAPE Provides a Significant Advantage for VC firms

September 20, 2023

CAPE serves as a powerful tool that transforms financial pitch decks into easily machine-readable data. Through standardization and centralization, CAPE enables swift analysis, allowing investors to dedicate more time to identifying promising investment opportunities.

Weekly ThemeX Index: Accepted Resignation

September 13, 2023

Within the Context Analytics Unstructured Data Terminal, ThemeX allows users to uncover critical insights from government filings, including our recent findings on the phrase “Accepted Resignation”. Our analysis reveals a clear and significant negative correlation between the phrase and short-term returns.

Daily Portfolio using Sentiment Thresholds on StockTwits Data

September 7, 2023

Social Sentiment can be leveraged to enhance stock selection and identify price movements. Using metrics from Context Analytics, customers can utilize metrics like S-Score and S-Buzz to create strategies with reduced risk.

Context Analytics Launches CAPE: Revolutionizing Financial Data Extraction for Private Equity and Venture Capital Firms

September 5, 2023

StockTwits S-Score Quintiles

August 31, 2023

Context Analytics' S-Factor feed is a suite of metrics that describe Social Sentiment from messages on a social media platform separated by source. With this dataset, users can harness the power of social media in financial markets.

Crypto Daily S-Score

August 24, 2023

As the cryptocurrency market matures, Context Analytics provides a way for traders to harness sentiment and make well-informed decisions, ultimately enhancing their success in this domain.

UDT Case Study: Maui Wildfires

August 21, 2023

Context Analytics' Unstructured Data Terminal (UDT) has the potential to recognize risks and facilitate swift responses to such dire events in the future. This case study examines what we found regarding the devastating wildfires that spread through Maui, more specifically Hawaiian Electric Industries (HEI). The events of the wildfires unveil numerous layers that can be analyzed through UDT.  The UDT can be a helpful tool in aiding decision-makers and risk assessors in comprehensively navigating ongoing crises.

StockTwits and Twitter Quintiles Combo

August 16, 2023

Context Analytics investigates blending the Twitter and StockTwits S-Score into one metric for trading. With this dataset, users can harness the power of social media in financial markets.

S-Score Thresholds

August 9, 2023

Twitter can be leveraged to enhance stock selection and identify intraday price movements. A more extreme S-Score threshold can improve portfolio returns too.

StockTwits Real Estate Indicator

August 2, 2023

Explore the behavior of the real estate market using sentiment metrics from Context Analytics. By analyzing sentiment from StockTwits, the study identifies negative days and employs a strategy to enhance index performance.

Enhancing Momentum Trading with StockTwits Sentiment and Volume

July 24, 2023

StockTwits is a social media platform primarily focused on financial discussions and market-related topics. As a social media platform focused on investing and trading discussions, it provides a wealth of user-generated content expressing opinions, emotions, and sentiments related to various stocks and assets. By analyzing the messages and interactions on Stocktwits, sentiment analysis tools can gauge the overall mood and sentiment surrounding specific stocks or financial instruments. This information can be valuable for traders and investors seeking to understand market trends, shifts in sentiment, and potential market reactions.

Lightspeed/Context Analytics Widgets

July 12, 2023

Context Analytics works with brokerage firms to bring the uncorrelated and predictive power of social media to their customers. For this blog we will explore the CA widget implementation for Lightspeed Trader.    

Changes in Risk Section of SEC Filings Impact Future Returns

June 29, 2023

By examining the Magnitude of Word Count Percentage Change metric, investors can gain a deeper understanding of a company's potential risks. The research findings indicate that companies with fewer changes in their risk sections tend to outperform the market, while those with more changes underperform compared to the overall market.

Context Analytics’ S-Score: Quintiles

June 21, 2023

Context Analytics’ Social Sentiment has been predictive over the last 10+ years. This blog explores the monotonic relationship between Social Sentiment and subsequent price action on US Equities.  

Weekly Raw Sentiment Long Only

June 15, 2023

Social Sentiment from Twitter can be used over multiple trading horizons. Using aggregations of Tweet sentiment from the previous 5 market days is predictive of weekly returns. A Long only portfolio using weekly raw sentiment outperforms the S&P 500 by 4.5% annually over the 5+ year period.

UDT Case Study – Coinbase Lawsuit

June 6, 2023

The SEC's lawsuit against Coinbase was not entirely unforeseen. This blog covers the potential signals using the Unstructured Data Terminal.

Daily Event Detector: Using Twitter and StockTwits for Alpha

June 1, 2023

Traders utilize sentiment factors from both Twitter and StockTwits to confirm social sentiment or identify high message volume securities. Using sentiment from two unique sources provides a strong signal. A sample long only portfolio with no overnight position yields cumulative returns greater than 70% since the beginning of 2022.

Daily Open-to-Close Long/Short Strategy : Raw-S

May 24, 2023

Context Analytics has a variety metrics derived from Social Media feeds such as Twitter and StockTwits. Here we look at the simplest and most raw sentiment factor: Raw-S. Recently, Raw-S has been highly predictive of market returns at the Open. This Daily strategy using only S&P 500 stocks yields a Long/Short that has outperformed SPY by 30% since 2022.

Monthly Sentiment Index – S&P 500

May 18, 2023

Even on the most liquid stocks, Context Analytics’ Social Sentiment provides an edge. Using only S&P 500 constituents, this Monthly Social Sentiment Index outperforms the market by over 2.5% annually over the past 5+ years.

Intraday Alpha - Expansion

May 10, 2023

Fast acting information distributed through social media sites like Twitter can improve investors’ returns. Using Social Sentiment data intraday allows traders to outperform market benchmarks within minutes of information being released.  

Intraday Alpha

May 4, 2023

Using intraday Social Sentiment monitoring can inform traders of any changes in market conditions and help them act fast. Stocks that have extremely positive sentiment from recent Twitter conversation, outperform the market over the subsequent hours.

Context Analytics S-Score Performance by Sector

April 26, 2023

Context Analytics’ Social Sentiment Score, S-Score, has been a consistent predictor of excess return and underperformance over the sector average over the last 10 years.  

Context Analytics Releases Standard Headings in Global Annual Reportsprp

April 25, 2023

Context Analytics Releases Standard Headings in Global Annual Reports

April 25, 2023

Context Analytics US Equity Open-to-Close with Performance Statistics

April 19, 2023

Context Analytics daily sentiment Long/Short portfolio without overnight risk yields 80% return since the beginning of 2022. When overlayed with historical security performance statistics, that adds over 25% to its cumulative return over this period.

ThemeX Search on EVs

April 12, 2023

Companies and individuals are increasingly focused on electric vehicles (EV) to contribute to a more sustainable future. With the increased investments in the electric vehicle, which companies are most impacted? With ThemeX, investors can identify keywords and phrases to examine how trends impact a variety of companies across industries and sectors.

Context Analytics TSX Asset Class on StockTwits

April 5, 2023

Context Analytics has developed its S-Factor and Activity feeds on TSX securities sourced from StockTwits messages. This aggregates StockTwits conversations on Canadian securities using our patented NLP. From a historical backtest, over the past 4+ years, the spread between TSX securities in the highest and lowest S-Score quintile yields a return of over 140%.

Context Analytics Open-to-Close Performance Update

March 29, 2023

Context Analytics daily sentiment portfolio without overnight risk yields 75% return since the beginning of 2022, outperforming the S&P 500 which had a negative return over the same period.

ThemeX Exploration of SVB Press Releases

March 22, 2023

In the third part of our SVB series we are going to use ThemeX to explore press releases related to SVB.

Social Sentiment on Silicon Valley Bank Collapse

March 15, 2023

Previously, we discussed how investors could have seen the collapse of SIVB coming through regulatory filings. There were multiple red flags throughout recent 8-Ks and 10-K that pointed towards SIVB being exposed to risk. Today, we will look at how Social Sentiment created by Context Analytics played a role in capturing the dramatic shift in SIVB’s price.

Regulatory Filings on Silicon Valley Bank Collapse

March 14, 2023

With the collapse of Silicon Valley Bank, Context Analytics wanted to see if there were any warning signs in regulatory documents that could have hinted towards this event. SIVB’s (SVB Financial Group) stock price dropped 34% from market close on Wednesday, March 8th to market open on March 9th and a total of 60% overall.

Crypto Market Indicator on BTC and ETH

March 8, 2023

Bitcoin (BTC) and Ethereum (ETH) are the two largest cryptocurrencies by market capitalization. One advantage to trading these two cryptocurrencies is the liquidity, allowing investors to be in and out of positions quickly with the ability to short the asset.

ThemeX Index: Increased Recurring Revenue

March 1, 2023

By using Context Analytics’ ThemeX search capabilities, users can create custom portfolios from its results. A search on ‘Increased Recurring Revenue’ yields a variety of securities that are grouped into a Monthly Long Only portfolio which outperforms the market by over 4.5% annually over a 10+ year sample.    

Sentiment Weighted Futures Portfolio

February 22, 2023

Using Twitter sentiment and volume metrics in the Commodities market can enhance portfolio performance. A sample portfolio using only Context Analytics S-Factors, decreases risk while also outperforming the benchmark 80% over a 7-year period.

ETF S-Score overlayed with Performance Statistics

February 15, 2023

Context Analytics provides predictive Social Sentiment data on ETFs through its S-Factor feed. When overlayed with S-Factor Performance statistics, returns are enhanced by over 4% annually.

Overnight Social Sentiment Daily Trading Strategy

February 1, 2023

S-Factors enables users to dissect single stock sentiment as expressed on social media. By tracking which securities have increasing or decreasing sentiment, users can create a strategy that yields over 30% annually over the past 5 years.

Context Analytics Textual Data for Academics Available on Dewey Data

January 31, 2023

Social Sentiment Combo: Using Twitter and StockTwits Sentiment

January 19, 2023

Users can create a combined Sentiment factor predictive of market returns using Context Analytics Twitter and StockTwits S-Factor feeds. Using sentiment factors from two unique sources confirms the accuracy of data and provides a strong signal.

Context Analytics Introduces Private Company Database

January 9, 2023

2022 Review: Context Analytics’ Social Sentiment S-Factor Performance

January 9, 2023

This past year, Context Analytics Social Sentiment metrics enhanced stock selection and strategy returns. A daily Long/Short trading strategy with no after-hours risk led to an annual return of more than 50% compared to the 2022 bear market. We review the performance of 2022 S-Factors and give users different ways of utilizing these unique Social Sentiment metrics.

ESG Trends to Look for in 2023

December 21, 2022

In this blog, we explore how to utilize Context Analytics technology to stay on top of key developments and trends in ESG in 2023.

Derivative Factors: Monotonic Relationships using S-Factors

December 14, 2022

Context Analytics looks at a variety of derivative metrics from its Social Sentiment feed to analyze prediction power. Here, we look at the daily change in sentiment score paired with its Twitter buzz. On a large universe, this factor demonstrates its monotonic relationship with 1-day price returns.  

Partner Widgets provided by Context Analytics

December 6, 2022

Examples and descriptions of some of the social sentiment widgets we have created for our partners.  

ThemeX reveals low prices in used cars will effect which companies

November 29, 2022

With the price of used cars recently declining, which companies will be most greatly impacted? With Context Analytics (CA) ThemeX, investors can pinpoint key words and phrases to see how trends can affect an array of companies across multiple sectors and industries.

Twitter Blue: Why Verification doesn’t influence Social Sentiment

November 22, 2022

Twitter’s new ‘Twitter Blue’ product allows users to pay for verification to gain more influence on the platform. This does not affect Context Analytics’ Social Sentiment metrics because ‘Verified’ is not a factor in our Account Rating Algorithm.  

Context Analytics Data on the FTX Collapse

November 14, 2022

The collapse of FTX sent shockwaves around the Crypto world. Context Analytics’ tools were able to identify red flags in the company hours before the collapse of FTX and FTX token.

Unveiling Insights on UDT

November 8, 2022

Using the Unstructured Data Terminal (UDT), users can discover insights in textual data sourced from Earnings Calls, Regulatory Filings, and Social Media. We explore findings on MNST earnings from the previous week.

Social Market Analytics Has Changed Their Name to Context Analytics to Reflect the Evolving Needs of Their Clients

November 1, 2022

Recent S-Score Open-to-Close Performance on US Equities

October 31, 2022

With current market volatility, we are frequently asked how our data is performing. This blog goes over charts YTD Open-To-Close return of common stocks with an S-Score > 2 or S-Score <-2 prior to Market Open.

Daily Twitter Sentiment: A Comparison of Universe Performance

October 24, 2022

Our S-Score is predictive across all universes and market caps. For daily holding periods, a strategy with a universe of all Market Caps and only S&P 500 stocks both outperform the overall market.

Twitter vs StockTwits: A Comparison of Daily S-Score Returns

October 19, 2022

Our S-Score creates a once a day Long/Short trading strategy that outperforms the market by over 30% (with minimal risk) since the start of 2020. With messages sourced from Twitter and StockTwits, these two distinct data feeds unveil hidden alpha from the social masses.

Can Social Media Inform Corporate Decisions? Evidence from Merger Withdrawals∗

October 12, 2022

Social media informs corporate decisions by studying the decision of firm management to withdraw an announced merger. Findings imply that social media is not a sideshow, but an important aspect of firm information environment.

SMA Classifications Data for Daily Trading Strategy

October 10, 2022

Using SMA Classifications feed we created a Daily Long/Short strategy that has outperformed SPY by over 4.5% annually over the past 5 years.

Increasing Transparency in Investments with ESG Reports

October 3, 2022

Due to climate and social challenges, companies have begun shifting priorities to include Environmental, Social and Governance (ESG) initiatives into their business practices. ESG reports inform investors on how companies are implementing ESG policies.

Which companies are impacted by Nord Stream Pipeline?

September 27, 2022

A few hours ago it was announced that there was a leak in the Nord Stream Gas Pipeline. With our Unstructured Data Terminal, we quickly found which companies could be impacted by this event.

Using Social Sentiment to Weight S&P 500 Constituents

September 19, 2022

Using SMA’s Social Sentiment to tilt weights of S&P 500 constituents monthly enhances index performance by over 1.5% annually.

Alpha in SMA Machine Readable Filings

September 7, 2022

We explore how SMA’s unique factors from SEC Regulatory Filings can be predictive of quarterly price returns. Document length and Sentiment are calculated and compared to historical baselines to identify alpha.

Using ThemeX to Understand Mentions of Recession in Corporate Filings

August 31, 2022

In this video we demonstrate how easy-to-use and powerful the ThemeX tool is on the Unstructured Data Terminal. We use ThemeX to search filings, transcripts and social media for macro insights on the impact of a recession.

Predictive Power of Sentiment on Earnings Q&A Extension

August 24, 2022

As a follow up to our previous blog we now explore how quantifying textual data from the Q&A portion of Earnings Call Transcripts with sentiment analysis can provide insights to future stock price movement over quarterly holding periods.

JLN PODCAST: SOCIAL MARKET ANALYTICS CEO JOE GITS REFLECTS ON COMPANY GROWTH AND NEW FEATURE

August 10, 2022

Predictive Power of Sentiment on Earnings Q&A

August 9, 2022

Earnings calls are one of the most important communications with investors.. SMA applies our patented sentiment metrics to earnings calls to make the analyzation process more efficient. We find excess returns with very positive sentiment when isolating the Q&A section.

General Market Indicator: Volatility of Sentiment Helpful in Predicting Overall Market Performance

August 3, 2022

A high volatility of sentiment on Twitter indicates potential uncertainty from investors on the direction of securities. An aggregate volatility calculates the uncertainty of the market in general. Since the Covid-19 pandemic, the aggregate volatility is helpful in predicting the general market direction.

Weekly S-Volume Lookback for Daily Trading

July 28, 2022

A week look-back of the S-Volume factor identifies securities that are hot topics on twitter. Securities with a high aggregate S-Volume score consistently outperforms those with a low S-Volume score. Being talked about matters.

GMRF Increases Coverage to Include ESG Documents

July 18, 2022

SMA is proud to announce that in Partnership with S&P Global we are releasing a full set of ESG documents as part of GMRF. In this blog, we introduce the exclusive library of ESG Documents and the content within them.

Using Twitter Sentiment for Day Trading

June 21, 2022

Stock prices tend to follow the follow the movement of their sentiment on twitter, especially when it contradicts the overnight pricing momentum. Adding sentiment to a momentum trading strategy improved the annualized return of the long position by 12% and the short position by 8%.

S-Factor Introduction Video Blog

May 10, 2022

In our first video blog we explain how our S-Factor feed uses the Twitter firehose to build trading signals, dashboards and widgets to help investors increase alpha.

SMA Launches TSX Asset Class to Social Media Feeds

April 12, 2022

This blog discusses the launch of SMA's TSX Asset class and alpha generated from this data set

Ukraine War Impact on Corporate Filings

March 21, 2022

In this blog we discuss the impact that the war in Ukraine has on EDGAR and Global Filings. We analyze the impact using the ThemeX feature on our newly released Unstructured Data Terminal.

Alpha Around the World: Insights into Global Annual Reports

November 1, 2021

In this blog we explore the returns of word count and sentiment within global annual reports using Global Machine Readable Filings

S-Score's Performance on Recent Earnings

September 14, 2021

In this blog, we test the predictability of SMA's S-Score data on price movement during earnings season

SMA Named Most Innovative Illinois Based NLP Firm

August 11, 2021

Global MRF – The First of its Kind

July 28, 2021

This blog demonstrates the offerings and unique features of Global Machine Readable Filings. 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.

Using Twitter Social Media for One-Month Holding Periods

June 21, 2021

This blog is about using SMA's S-Factors to aggregate and create long-term Social Media signals utilized for a Monthly Trading Strategy.

What is an S-Score? Answered by Investopedia

June 7, 2021

Rare Earth Metals – Machine Readable Filings (MRF) Expose U.S. Domestic Shortage

May 24, 2021

In this blog we analyze the conversations of Rare Earth Metals within SEC Edgar Filings, using SMA’s complex topic modeling in the new Machine Readable Filings (MRF).

Analysis of SPAC Returns using Twitter Volume

May 17, 2021

In this blog we explore the return characteristics of special acquisition corps using metrics from our new SPACs as an Asset Class data feed.

SPAC – SMA Releases Real Time Quantitative SPAC S-Factor Data Feed

May 11, 2021

U.S. Filings: No News is Good News

May 4, 2021

Textual Consistency Matters and the Market Rewards It: Firms with the most year-over-year textual similarity outperformed those with the least similarity by 4.18% in the MD&A section and by 5.26% in the Risk Factors section annually after accounting for commonly used risk strategies.

Our CTO Umair Rafiq joined the Chicago Office

May 1, 2021

Fidelity Launches Digital Assets Analytics Platform

April 29, 2021

Analysis of Subsequent returns on Short Squeeze Conversations

April 20, 2021

In the wake of the recent GameStop (GME) short squeeze, we received a lot of inbound questions on social media’s predictive power for short squeezes. This blog explores subsequent return characteristics in the SMA Short Squeeze data feed.

Hiding in Plain Sight – Risks That Are Overlooked

March 31, 2021

10-Q & 10-K filings are a vital source of information, but their length and complexity may result in investors overlooking important details. In the latest report, the Quantamental Research group uses Natural Language Processing to identify companies that have made significant changes to the “Risk Factors” section of their corporate filings.

S&P Global Market Intelligence Expands Textual Data Suite With Global Machine Readable Filings Via Xpressfeed™

March 30, 2021

SMA Short Squeeze Data Feed

February 22, 2021

Since the now famous GameStop (GME) short squeeze we have received inquiries about Twitter’s ability to identify short squeezes.  This blogs introduces SMA's Short Squeeze Data Feed, a product that helps identify stocks prior to their squeeze.

Robots on Wall Street Wrestle With Confusing World of Reddit

February 22, 2021

Robots on Wall Street Wrestle With Confusing World of Reddit

February 22, 2021

How MRF Filings Improves on Raw Edgar Downloads

February 2, 2021

In this blog we look at how SMA's Machine Readable Filings (MRF) product improves on raw EDGAR downloads. MRF offers a concise and efficient way to analyze text in corporate filings.

University of Illinois MSFE Practicum - Analysis of Stock Return Trends Based On 8-K Sentiment Metrics

January 14, 2021

This paper is an analysis of the Machine Readable Filings (MRF) 8-K dataset to predict future U.S. Equity returns.  SMA partnered with S&P Global Market Intelligence to provide textual data in U.S. SEC EDGAR filings broken down by heading with text underneath (i.e. Parts, Items). We look at the predictive power of the 8-K data set on the Document as well as the Item levels, including Word Count and Sentiment fields.

University of Illinois MSFE Student Practicum Group Wins Competition with SMA MRF 8-K Filing Research Project

January 14, 2021

SMA Futures Data Sanities

January 4, 2021

This blog will explore the predictive nature of our Futures Twitter based sentiment factors by tracking Futures contracts' Settle-to-Settle performance based on SMA's sentiment metrics.

Thematic Investing using Machine Readable Filings (MRF)

December 1, 2020

In this blog we will be illustrating the power of SMA’s complex topic modeling in the new Machine Readable Filings (MRF) product by identifying companies in thematic investing.  This blog uses 'Drones' as an example topic.

SMA Receives Third U.S. Patent

November 24, 2020

Machine Readable Filings (MRF): 8-K Sentiment Alpha

October 26, 2020

This blog is an analysis of the 8-K filings from SMA's Machine Readable Filings (MRF) dataset.  We look at the predictive power of the sentiment values of the 8-K filings towards the companies' future equity returns.

Crypto Currency Market Index

October 13, 2020

In this blog, we look at a Crypto Currency broad market indicator built with SMA sentiment data that is predictive of future Bitcoin prices.  We call this indicator the Crypto Market Score (CMS).

Machine Readable Filings Extracts the Significance of ESG in Future Earnings

August 4, 2020

This blog is an analysis of the ESG Topic Model on the Machine Readable Filings (MRF) dataset. SMA partnered with S&P Global Market Intelligence to provide textual data in U.S. SEC EDGAR filings broken down by heading with text underneath (i.e. Parts, Items). Utilizing MRF and SMA's Topic Modeling technology, we analyze the breadth of who's mentioning ESG in their filings and the depth of the mentions.

Filtering Relevant Tweets Using Topic Models

July 20, 2020

In this blog, we look at how SMA captures the most relevant and indicative information for each of the securities we track on Twitter - Topic Modeling, and Account Filtering.

The TIE partners with CoinMetro to provide SMA Sentiment to Crypto Exchange users

July 2, 2020

Machine Readable Filings (MRF): Total Document, MD&A, and Risk Factors Alpha

June 29, 2020

This blog is an analysis of the Machine Readable Filings (MRF) dataset to predict future U.S. Equity returns.  SMA partnered with S&P Global Market Intelligence to provide textual data in U.S. SEC EDGAR filings broken down by heading with text underneath (i.e. Parts, Items). In this blog, we look at the predictive power of the data set on the Document, as well as the Item levels.

Machine Readable Filings (MRF): Total Document, MD&A, and Risk Factors Alpha

June 29, 2020

This paper is an analysis of the Machine Readable Filings (MRF) dataset to predict future U.S. Equity returns.  SMA partnered with S&P Global Market Intelligence to provide textual data in U.S. SEC EDGAR filings broken down by heading with text underneath (i.e. Parts, Items). We look at the predictive power of the data set on the Document, as well as the Item levels.

S&P Global Launches Data Marketplace

May 29, 2020

Predictive Sentiment on Machine Readable Filings (MRF)

May 27, 2020

This blog explores the predictive nature of metrics on regulatory filings using SMA patented NLP and machine learning from the recently release Machine Readable Filings (MRF) Product.

Bitcoin Sentiment from SMA on Twitter Reaches Its Highest Level in 3 Years

May 20, 2020

S&P Global - Social Market Analytics Machine Readable Filings (MRF)

April 9, 2020

S&P Global and Social Market Analytics launched Machine Readable Filings (MRF), a sophisticated new data offering which applies Parsing and Natural Language Processing to generate machine readable text extracted from SEC Regulatory Filings.

S&P Global Market Intelligence Expands Textual Data Suite with Machine Readable Filings via Xpressfeed™

April 9, 2020

Machine Readable Filings (MRF) Word Count Alpha

March 30, 2020

This paper discusses the analysis of U.S. Equity Returns using Machine Readable Filings (MRF) word counts.  It focuses on change in word counts in 10-Ks and 10-Qs as it is builds on existing academic research Lazy Prices.

Open FACTSET: Social Market Analytics, Inc. (SMA) S-Factor Sentiment

March 20, 2020

Sentiment Performance During COVID-19 Volatility

March 16, 2020

In this blog we look at SMA Sentiment Score's performance over the past few weeks, amid the recent market volatility due to COVID-19.

SMA S-Score Strength on the Wings

January 16, 2020

This blog goes over the predictive power of SMA's S-Score, a statistical Z-Score calculation on the current sentiment. The analysis shows that the more significant the S-Score, the more extreme the subsequent returns.

Analysis of Social Market Analytics Using MyDataOutlet Analytics Platform

December 10, 2019

This blog post highlights research done on an excellent research platform My Data Outlet (MDO). MDO specializes in integrating financial data into R. They offer an API to access financial data, allowing for a single access point for extracting data. The research provides a great illustration of the predictive power of SMA's metrics.

Social Market Analytics (SMA) Partners with Lightspeed, a division of Lime Brokerage

December 3, 2019

Top Futures Traders Use Tweetdeck For Breaking News Trading Strategy

November 25, 2019

Crypto Portfolio Will Analyze Twitter to Gauge Trader Sentiment

October 15, 2019

Using derived analytics from Twitter data to forecast more effectively in volatile markets

September 16, 2019

Benefits of SMA Machine Learning Algorithms

September 4, 2019

This blog answers the question – “Do SMA's Machine Learning algorithms really add value to the NLP process?”. Answer -> Yes.  

SMA on NPR Marketplace

August 30, 2019

SMA's Joe Gits with Kai Ryssdal on NPR Marketplace, talking about market reactions to the presidents's tweets.

Performance of SMA Data in a Volatile Market

August 26, 2019

This piece shows the performance of SMA’s sentiment data in the volatile market of 2019, illustrated by returns and Sharpe/Sortino ratios.

Can Tweets And Facebook Posts Predict Stock Behavior?

June 25, 2019

SMA Partners with Coin Metrics to provide Real-Time Sentiment Data Feeds

June 17, 2019

Coin Metrics and SMA announced today a partnership to incorporate SMA’s Crypto Currency Data Feed into the Coin Metrics Market Data Platform.

SMA Partners with Coin Metrics to provide Real-Time Sentiment Data Feeds

June 17, 2019

Coin Metrics is incorporating SMA's cryptocurrency data feed into its market data platform.

CME Group hosts SMA for a 'Lunch and Learn'

May 31, 2019

The CME Group had SMA into speak to the Data and Marketing Teams about AI, Machine Learning, and NLP across Finance and Futures and Options

SEC, Finra warn investors not to base stock decisions on social sentiment

May 9, 2019

Social Market Analytics has two U.S patents developed "to prevent just this kind of abuse."

SMA Partners with RCM-X for Sentiment-Driven Advanced Algorithmic Trading

May 2, 2019

RCM-X is partnering with SMA to incorporate SMA's Cryptocurrency Data Feed into the logic of RCM-X's advanced order types and technologies.

Social Market Analytics Identifies Most Accurate Twitter Accounts

May 1, 2019

SMA aggregates the intentions of professional investors as expressed on Twitter. We identify these professional investors using our proprietary twelve factor ranking system.  One factor is the forward accuracy of Twitter accounts.  If a Twitter account is tweeting bullishly based on our patented NLP process and the security subsequently moves higher over specified periods that account is deemed to be accurate over that period. We found significant variability in account accuracy for supposed professional investors.

IHS Markit Analysis of Social Market Analytics LSE Equity Data

March 11, 2019

IHS Markit recently added SMA's LSE 1000 Equity S-Factor Feed to their data offerings.  In conjunction with the launch IHS Markit authored a research paper exploring the predictive nature of the SMA S-Factor data on LSE equity securities.

IHS Markit - Social Media Indicators in the UK (LSE)

March 11, 2019

IHS Markit recently added SMA’s LSE 1000 Equity S-Factor Feed to their data offerings.  In conjunction with the launch IHS Markit authored a research paper exploring the predictive nature of the SMA S-Factor data on LSE equity securities.

Fidelity Hosts Webinar on SMA on Fidelity Active Trader Pro

March 1, 2019

SMA is Pleased to participate as a Silver Sponsor at BattleFin Miami

January 29, 2019

Benefits of SMA Account Filtering During 2018 Down Market

January 22, 2019

SMA aggregates the intentions of professional investors as expressed on Twitter.  We apply our patented filtering and natural language processing(NLP) to Tweets to proactively select Twitter accounts to use in our predictive metrics. From the perspective of 2018 market performance, this blog answers two questions we get regularly: How would your data perform in a bear market?  And what is the benefit of your NLP and account ratings systems?

CBOE – Social Market Analytics SMLCW Index significantly outperforms

January 8, 2019

In June of 2017 SMA launched a weekly re-balanced large cap sentiment based index (SMLCW). This index is comprised of twenty-five stocks with the highest average Twitter sentiment over the prior week selected and re-balanced Friday afternoons from the CBOE Large Cap 450 Index. This blog takes a look at SMLCW's significant performance in 2018, a 0.87% gain compared to a 8.4% loss on the S&P 500 Index.

Predictive Real-Time Alerting on Commodities

December 11, 2018

Social Market Analytics (SMA) tracks real-time sentiment on equities, commodities, currencies, ETF’s and crypto currencies.  SMA has the most powerful and customizable Alerting API combining Twitter sentiment and pricing metrics.  Users receive custom real-time sentiment alerts on instruments in their watch list.

Power of Predictive Alpha in a Bear Market

November 28, 2018

SMA launched the SMLCW index in partnership with the CBOE two years ago.  This index is re-balanced weekly and comprised of the twenty-five securities selected from the CBOE large cap universe with the highest average S-Score over the prior week. This blog takes a look at its performance in 2018, a tough year for most investment strategies.

Social Market Analytics (SMA) Trading Strategy on Natural Gas Futures

November 21, 2018

SMA's NLP is unique because of our proprietary processes that tag sentiment weights based on the language used in finance per asset class. Recently, we did as study on using SMA signals to create a Long Short trading strategy using Natural Gas futures. The results show a significant outperformance from Natural Gas prices.

The Third Barclays Quantitative Investment Strategies Conference

November 13, 2018

SMA is happy to participate in the "Using artificial intelligence, machine learning & big data for QIS investing panel discussion" in London

Social Market Analytics (SMA) on CME Group Active Trader

November 8, 2018

The CME Group has partnered with Social Market Analytics, Inc. (SMA) on the CME Active Trader platform to provide predictive sentiment data analytics across six asset classes and thirty-six commodities. The CME Group is leveraging SMA’s Patented processing technology in machine learning and natural language processing (NLP) to provide users with new alternative sentiment data to a trader’s tool kit.

Cboe – SMA Large Cap Weekly Index continues to outperform in Volatile Market

October 31, 2018

The SMLCW Index is a Long Only Index that has outperformed since it was released and has continues to outperform in the recent market volatility and sell-off. In the chart below the S&P500 is flat for the year and SMLCW is up nearly 5% YTD.

Social Market Analytics Receives Second Patent

October 18, 2018

With the SMA team continuously expanding and improving the technology, SMA recently received a second patent as an extension of the original patent. The first patent was on the three-component system for extraction, evaluation and publication of metrics on social media feeds. SMA now has two granted U.S. Patents.

SMA Speaks at the FCS - Financial Communications Society

October 12, 2018

SMA Receives Second U.S. Patent

October 12, 2018

Predicting LSE Security Price Movements with Twitter Sentiment

October 10, 2018

SMA covers the Top 1000 securities on LSE ranked by market cap. This blog is about the predictive nature of our LSE security universe.  We calculate our custom metrics on the top 1000 market cap securities listed on the LSE.  Our LSE data starts on 1/1/2016. The quintile analysis confirm the predictive nature of dataset in LSE data. The spread between the top and bottom quintiles is 10% annualized and sharpe and sortino numbers show a high return to risk ratio.

Bitcoin Sentiment Based Trading Strategy

September 26, 2018

Social Market Analytics (SMA) publishes real time Twitter based sentiment for nearly 350 crypto currencies including Bitcoin.  In this post we will review a sentiment-based Z-Score strategy to generate profitable trades for Bitcoin.

Extreme Positive Gold Sentiment on CME Active Trader Website

September 24, 2018

Social Market Analytics (SMA) data is live on the CME Active Trader Website.  Real-time sentiment and indicative Twitter volume is can be tracked used by traders to generate new ideas.

Social Market Analytics Sentiment Data for Forex Trading

September 20, 2018

This blog explores a trading system using the SMA Twitter based sentiment data to trade a basket of Forex with two strategies: Sentiment RSI, and S-Score Based Currency Selection Model.

Social Market Analytics Sentiment now on CME Active Traders Site

August 22, 2018

SMA is excited to announce a partnership with the Chicago Mercantile Exchange to provide real-time Twitter based sentiment for their active trader website, giving commodity traders instant real-time access to Twitter based sentiment metrics.

IHS Markit - Social Media Indicator Review (Equity)

June 15, 2018

This paper revisits the social media indicators IHS Markit & SMA introduced back in 2014. It reviews factor performance since the model’s inception, with focus on a key predictive factor, S-Score™. S-Score™ interactions with short-term price momentum and short interest factors are also analyzed. Furthermore, it also considers the application of sentiment aggregated at the market level.

Barclays Risk Premia Forums in Singapore and Hong Kong

May 7, 2018

SMA CEO Joe Gits speaks at the Barclays Risk Premia Forums in Singapore on May 7th and Hong Kong on May 9th

These Benzinga Global Fintech Awards Finalists Are Revolutionizing AI And Machine Learning

May 4, 2018

The Benzinga Global Fintech Awards are a yearly showcase of the greatest advances in fintech from leaders and visionaries in the worlds of finance and technology. This year, executives, developers and innovators from the likes of Facebook, Amazon, IBM, JPMorgan, TD Ameritrade, TradeStation, Fidelity, Zelle and so many more attending the Oscars of Fintech.

UIUC Bitcoin Trading System Practicum Presentation

May 3, 2018

The SMA Practicum Group at University of Illinois worked with RCM Capital in the spring of 2018 to develop a Bitcoin trading strategy combining price momentum with sentiment.

University of Illinois MSFE Practicum - Cryptocurrency Momentum-Sentiment Trading Strategy

May 3, 2018

SMA takes a look at sentiment's impact on the cryptocurrency market in a practicum with the MSFE students from the University of Illinois in the spring of 2018. The SMA Practicum Group worked with RCM Capital to develop a Bitcoin trading strategy combining price momentum with sentiment.

Is Vanguard’s Success a Problem? Some Customers Think So

March 29, 2018

Louise Robbins bought shares in an exchange-traded fund last Friday afternoon as markets fell, knowing that she had enough money in her Vanguard Group settlement fund to pay for the trade.

Trading Text and Sentiment Analysis

February 27, 2018

SMA creates actionable intelligence from social media data by filtering out the noise to deliver clean data on sentiment for financial markets. More specifically, it produces a family of metrics, called S-Factors™, designed to capture the signature of financial markets sentiment.

Introducing The SMA 50 Long Index

February 20, 2018

SMA has been creating security level sentiment metrics for six years. This blog will discuss the application of sentiment to a long only 50 stock, re balanced annually, index.

Social Market Analytics – Year in Review

January 8, 2018

This blog shows SMA's sentiment data performance in 2017, illustrated with tables of Open to Close performance of securities with the aid of sentiment scores.

Predicting Trading Volume Distributions Using Social Media Signals (Equity)

January 8, 2018

Trading volume predictors are part of a continuous iterative research process at most firms. Trading volume depends on multiple factors such as the market activity, political events, global unrest and human behavior. This paper explores the use of social media signals to predict trading volume by using linear regression testing and correlation analysis.

SMA Crypto Currency Data Feed Goes Live

January 2, 2018

SMA's Crypto Currency Data Feed has gone live covering +270 Digital Assets, Exchanges, and Futures.  The CC Data Set has the same monotonic profile of all SMA Asset Classes and is being used in trading by Market Makers and for Portfolio Management

SMA Now Has Six Years of Out-Of-Sample History!

December 5, 2017

SMA is celebrating six years of out-of-sample data in US Equities. This data is unique in that it is a true representation of the Twitter conversation at each historical point-in-time.

University of Illinois MSFE Practicum - SMA50 Index

December 4, 2017

The SMA Practicum Group at University of Illinois, during the fall semester of 2017, created a new sentiment enhanced index, the SMA50 Index. The index measures the aggregate performance of stocks with high levels of crowd sourced commentary and high market liquidity. This piece explains the construction of the index, as well as analyzes its performance.

SMA's LSE FTSE1000 Feed Goes Live

December 1, 2017

SMA has expanded into EMEA with it first offering.  SMA is live an in production with clients covering the FTSE1000.  Similar to U.S. Equities, SMA offers the FTSE data in across four feeds: S-Factor™, Activity, Tweet Level, and Lexical.

Bitcoin Conversation Volume Beats Talk of Facebook, Apple, Netflix, Google

November 18, 2017

“Twitter is clearly taking the lead as the home for discussions related to new monetary technologies,” Social Market Analytics‘ Joe Gits declares to Jared Podnos. And it does seem to be the case.

Deutsche Bank Extension Paper

August 1, 2017

This is an extension to the Research Paper titled “Signal Processing: Social Media Sentiment” published by the Deutsche Bank Quantitative Research Group. This extension expands on the technical indicators and range strategy concepts of the original paper and finds that it is advantageous to incorporate technical indicators that capture sentiment momentum and sentiment volume.

Deutsche Bank Research Report On SMA S-Factor Data

July 17, 2017

Deutsche Bank Quantitative Research Team released a full research report exclusively on SMA's sentiment data.  This report independently verifies the predictive nature of the SMA's S-Factors™.

Deutsche Bank Markets Research - Signal Processing

July 6, 2017

This research explores how natural language processing techniques can be used to process qualitative data to form equity return forecasts. Specifically, it analyzes SMA Indicators provided by IHS Markit which estimate stock-level sentiment from twitter data for US equities.

Allegations of ‘fake news’ stretch beyond politics

July 4, 2017

Social Market Analytics, for instance, culls millions of tweets a day to give “quantitative” traders a sense of what direction a stock may be moving, said Joe Gits, the company’s chief executive. The firm is on the lookout for false leads and avoids tracking small companies with little following, known as penny stocks, he said.

43 of the top big data companies to work for, by J.P. Morgan

June 1, 2017

JPMorgan names Social Market Analytics, Inc. (SMA) as one of the Top 43 Big Data Companies.  "These new "alpha generating" data sources have become a significant source of competitive advantage for investors. J.P. Morgan predicts that analysts and portfolio managers who don't have access to these data sources will be left behind."

Application of Social Media Signals to Enhance Index Performance

May 10, 2017

Traditional passive indices such as the S&P 500 use a metric such as float adjusted market cap to calculate the weights of each company in the index. This research paper talks about applying an additional sentiment layer on top of the float market cap to further adjust the weight of the stocks to enhance performance.

Joe Gits Talks Twitter At CBOE’s Risk Management Conference

April 21, 2017

Joe Gits, CEO of SMA, spoke at the 34th annual CBOE Risk Management Conference. Gits spoke about SMA’s patented technology, the Social Sentiment Engine, and Twitter’s relevance in financial markets.

Did you have a 40 Minute Head Start on Ocwen Financial Price Drop?

April 21, 2017

On April 20th 2017, discussion started on Twitter that Ocwen Financial was going to be investigated in relation to sub prime mortgage concerns. SMA's sentiment data provided a strong sell signal 40 minutes before the price drop.

Decile Spreads for Twitter & StockTwits

March 10, 2017

This blog explores decile groupings based on SMA's S-Score™, and their corresponding cumulative subsequent returns.

A Little Birdie Told Me: Playing the Market on Trump Tweets

February 16, 2017

Joe Gits, the chief executive of SMA, commented on the market reactions to the president's tweets.

Why Chicago trading firms have a Twitter crush

February 2, 2017

SMA culls Twitter feeds, including posts by people in the StockTwits trading community, for positive or negative remarks on specific stocks and delivers that as a metric to its customers.

Six Months of SMLC

February 1, 2017

This paper looks at the performance of SMLC (SMA Large Cap Index) SMA launched partnered with CBOE back in September 2016.

When Trump tweets and stocks fall, puppies win

January 31, 2017

T3 is far from the first company to capitalize on Trump's targeted tweet-storms, made evident by the almost instantaneous market response to his online remarks, analysts told the Los Angeles Times in mid-January. "It's in the algorithms," said Joe Gits, chief executive of Social Market Analytics. "They've done it."

2016 In Review

January 23, 2017

This piece shows the performance of SMA's sentiment data in 2016, illustrated by returns and Sharpe/Sortino ratios.

Wall Street firms use algorithms that capture Trump’s tweets to profit from automated trades

January 19, 2017

Trump’s market moves are “getting press now because of our next president’s propensity to tweet” and Trump’s upcoming ability to actually change the business climate, Gits said. “But it really started a couple of years ago.”

When Trump tweets, Wall Street trades — instantly

January 16, 2017

The jaw-dropping speed at which certain stocks have moved in response to Donald Trump’s tweets about corporate America makes it seem as if Wall Street already was waiting for the president-elect’s words. It was.

CBOE Launches Second Social Media Benchmark Index

January 13, 2017

Chicago Board Options Exchange has launched the CBOE-SMA Large-Cap Weekly Index (SMLCWSM Index), the second in a series of sentiment-based strategy benchmark indices designed to capitalize on short-term market momentum based on SMA metrics.

Rutgers University - Application of Sentiment Analytics to Fama-French Model (Equity)

January 10, 2017

This paper expands on the JHU research paper (Liew & Budavari, 2016) exploring the predictive power of StockTwits based sentiment data. It is postulated that using a fine grain text analytics approach on social media posts is a better representative of the sentiment factor. This new model shows improvement in both Fama French 5 Factor Model and the model in JHU paper.

Weekly, Monthly, Quarterly Re-balance

January 9, 2017

This piece explores the use of SMA data for weekly, monthly and quarterly holding periods in portfolio managements.

When Donald Trump Hate-Tweeted Lockheed Martin, Hedge Funds Were Ready

December 14, 2016

Even before Donald Trump went on Twitter and posted his market-cratering tweet lambasting Lockheed Martin‘s F-35 fighter jets, the company’s stock was already falling.

SMA Signals for Monthly & Quarterly Holding Periods

October 24, 2016

Now with five years of out-of-sample history, SMA created statistically significant signals with monthly and quarterly holding periods. This blog shows the use of sentiment data for monthly and quarterly holding periods, and also explores a trading system by looking at exhaustion in social media.

SMLC Performance Since Launch

September 19, 2016

Since SMLC (SMA Large Cap Index) launched six weeks ago, there has been a significant increase in volatility. This piece shows how SMLC has performed during this period of increased volatility.

CBOE & SMA Weekly Sentiment Index

September 12, 2016

SMA and CBOE researchers have been working on multiple indexes, the next index (SMLCW) is a weekly rebalance portfolio based on the average sentiment of stocks during the week as measure on Friday mornings prior to the Open.

Twitter’s New Followers

August 29, 2016

Can you trade off of Twitter? The Chicago Board Options Exchange and its partner SMA believe so.

A Returns Analysis on StockTwits Sentiment Metrics (Equity)

August 25, 2016

This paper discusses the analysis of a Returns Study done on US Equities using SMA's sentiment factors in a single factor trading model environment. In a comparison to a market reference on a long only strategy, the results indicate an outperformance in returns for positive sentiment stocks and an underperformance for negative sentiment stocks. The long short strategy outperforms the market reference consistently over multiple testing periods.

CBOE SMA Large Cap Index

August 19, 2016

On July 29, CBOE and SMA launched the CBOE SMA Large Cap Index (SMLC) which tracks the return of a hypothetical portfolio strategy based on SMA S-Scores™. It has outperformed the S&P500 over the past three weeks.

Tweet trades: CBOE launches benchmark index based on social media sentiment

August 15, 2016

Produced in partnership with Chicago-based SMA, the CBOE-SMA Large Cap Index (or SMLC Index) formally announced Monday is being touted as the first of what is expected to be a series of sentiment-based strategy benchmark indexes that will aim to measure short-term market momentum.

University of Illinois MSFE Practicum - Application of Social Sentiment Factors In ETF Design

June 26, 2016

The SMA Practicum Group at University of Illinois, during the Spring semester of 2016, created a new sentiment enhanced fund. The research modifies the existing S&P 500 sector tracking ETFs (SPY, XLV, and XLY) by enhancing the highest market capitalization subset of the ETFs based on social media sentiment while still passively investing in the remaining stocks of the ETFs.

SMA Predicts Brexit Two Weeks Before The Vote

June 24, 2016

SMA was able to predict Brexit by analyzing the Twitter volume of the top hashtags on this topic.  

That’s Two Takeovers in a Week!

June 22, 2016

SMA's sentiment data provided another actionable signal when Twitter broke SolarCity being acquired by Tesla Motors. The investors with SMA data in their trading models were ahead of the curve, when the rest of the market was just learning of the news.

CBOE to Develop Series of Social Media-Based Strategy Benchmark Indexes

June 14, 2016

Chicago Board Options Exchange announced today that it has entered into an exclusive licensing agreement with SMA to develop a series of sentiment-based strategy benchmark indexes based on SMA’s social media metrics.

Twitter Leads News For MSFT, LNKD Acquisition

June 13, 2016

Microsoft buying LinkedIn broke on Twitter first. SMA detected this 7 minutes ahead of any news article came out.

SMA Predicted #Brexit Two Weeks Before the Vote

June 8, 2016

People seem surprised that Britain voted to exit the EU. SMA with its partner the CBOE are not nearly as surprised. Russell Rhoades from the CBOE has been blogging and Tweeting with SMA data for two weeks that it looks like the Brexit is going to happen.

StockTwits based S-Factor Return Charts

May 13, 2016

StockTwits is a community for active traders to share ideas enabling you to tap into the pulse of the market. This blog will focus on the deterministic nature of the StockTwits data set when aggregated into SMA S-Factors™.

The Application of Sentiment Velocity and Acceleration Metrics (Equity)

April 28, 2016

This research note addresses the question: Can social media sentiment be used to predict price movements over multi-day (as opposed to intraday) holding periods?  This paper attempts to answer this question by creating a trading strategy using longer-term signals derived from S-Factors™ data published by SMA.

Twitter Sentiment and Longer Holding Periods

April 20, 2016

SMA introduces two longer term signals into the metrics: Velocity and Acceleration, which capture the rapid changes in sentiment.

Analysis of EURUSD Twitter Sentiment

February 4, 2016

SMA studies the correlation between the Twitter derived sentiment on EURUSD forex pair and the correlation with the EURUSD exchange rate in December 2015. The research note explores two frequencies- 15 minutes and daily- both of which point to same trend.

Bernie Sanders Landslide Twitter Victory

February 2, 2016

SMA's chief executive, Joe Gits, talks about how Twitter sentiment can be used to interpret political election results.

Applying Big Data Sentiment Analysis to Donald Trump

January 27, 2016

SMA takes a look at the political landscape by analyzing the sentiment on the current conversation about candidates and issues.

Follow the Twitter Feed To Fat Returns

January 24, 2016

Social media platforms have gained prominence when it comes to investing partly because traditional information sources, such as newspapers and newswires, are no longer always first with the news.

Johns Hopkins University - The 'Sixth' Fama-French Factor (Equity)

January 9, 2016

In this JHU research paper, it explores the characteristics of securities derived from social media and discovered significant power in explaining the time-series variation in daily returns.

Crude Oil and StockTwits Sentiment

January 8, 2016

Using their patented sentiment calculation technology and the conversations on the StockTwits, SMA identified an interesting connection between sentiment and subsequent changes in the front month Crude contracts over the last year .

2015 In Review

January 4, 2016

This piece shows the performance of SMA’s sentiment data in 2015, illustrated by returns and Sharpe/Sortino ratios.

University of Illinois MSFE Practicum - Sentiment Enhanced ETFs

December 28, 2015

The SMA Practicum Group at University of Illinois, during the Fall semester of 2015, looked at ways of enhancing ETFs. This research investigates the performance of enhanced ETF portfolios by modifying the constituent weights of cap-weighted SPDR ETFs utilizing market sentiment metrics provided by SMA. Three ETFs, SPY, XLV, and XLY, are analyzed to see how the different sectors would perform with respect to market sentiment.

Long/Short Research on Russell 1000 Stocks

December 8, 2015

This blog takes a look at the performance of a sentiment strategy on the Russell 1000, using SMA's S-Scores™ and S-Volumes™.

Social Media and Smart Beta

October 27, 2015

SMA researches modifying weights of the SPDR SPY ETF based on sentiment values and examines the impact on return.

An Analysis of Equity Returns Using a Close to Close Methodology

October 14, 2015

SMA analyzes the predictive power on a close to close return basis based on the S-Score™ at 2:40 pm central time - giving a lead time of 20 minutes to make changes to the portfolio/alpha model - and buy at the close price of the day. This research, in addition to the pre-market open study, illustrates that sentiment is predictive and is not overly sensitive to timing.

Social Market Analytics Visualization Tools

October 6, 2015

SMA introduces two ways to access sentiment data without programming: Excel Add-in and Sentiment Dashboard.

Sentiment Leading Recent Market Volatility

September 3, 2015

This blog explores the relationship between market movement and SMA's sentiment data by looking at the percentage of positive Tweets versus the percentage of negative Tweets over the last couple of weeks.

Twitter Can Help You Cash In on Corporate Earnings

August 28, 2015

The collective 'wisdom of the crowds' on Twitter can beat Wall Street in predicting corporate earnings and helping you make smart stock trades, a new report says.

Social Media Generated Trading Ideas

August 11, 2015

This blog lists some recent trading opportunities social media data presented. In each case activity and sentiment increased prior to the actual event.

University of Illinois MSFE Practicum - Twitter Sentiment and Volatility Index Directional Forecasting

August 4, 2015

The SMA Practicum Group at University of Illinois investigates the benefits of using sentiment measures in classifier models designed to predict next day directional movement for volatility indexes.

Twitter Sentiment and Volatility Index Directional Forecasting

August 4, 2015

SMA has just completed a comprehensive analysis that shows the performance of classifier models, designed to predict next day directional movement for volatility indexes, improves by adding market sentiment measures derived from social media sources.

An Analysis of Equity Returns Using an Open to Close Methodology

July 20, 2015

SMA conducts an analysis on the cumulative returns over 3 and a half years using an intraday trading strategy based on S-Score™, and compares the historical returns with the YTD returns to see how the underlying analytics have evolved over time.

Predictive Power of SMA S-Factors

July 7, 2015

This blog reviews SMA's metrics' performance, illustrated by charts that look at the full history and YTD performance of the S-Factors™ across the entire universe.

Social Topic Conversations: What You Want, When You Want It, How You Want It

June 8, 2015

SMA's CFO Kim Gits talks about how SMA builds S-Factors™ metrics from the unfiltered Twitter fire hose.

How Twitter Moves Markets And Traders

June 2, 2015

Today's financial technology dialog is often about a word you don't usually associate with it - democracy - bringing software, data, reporting, testing and trading to the masses. And it's not just one size for everyone - its customizable too. At the FinTech Exchange 2015 Chicago event, 13 firm executives spoke during its lightning round.

This Is How Hedge Funds See Market Moves Before The Rest Of Us

May 21, 2015

Joe Gits, CEO of SMA, explains to Crain's how Twitter data is extracted and parsed to get meaningful sentiment information.

Social Media and Investing for a New Generation

May 5, 2015

Kim Gits, CFO of SMA, talks about Millennial investors and how they will change the future of social media use in capital markets.

Nasdaq Takes Blame For Twitter’s Earnings Leak

April 28, 2015

Twitter got a taste of its own broadcasting power today when a web crawler found and shared its earnings on the social media service nearly an hour before its intended release.

THE ALTERA “WINDFALL” $2.4 MILLION OPTIONS TRADE OF 03/27/15

April 21, 2015

On Mar. 27, after it broke Twitter that Intel was in talk to buy Altera, SMA's S-Score™ reacted significantly before Altera's price change.

Is Social Media a Proxy for Momentum & Does is Lead or Lag the Market?

March 23, 2015

This piece studies the relationship between social media and the market momentum.

Predictive Power of Social Media data in Sectors

March 3, 2015

This blog explores how predictive social sentiment is for different sectors in the financial market.

Sentiment Scoring using Fine Grain Scoring Versus Bucketing

February 3, 2015

This blog discusses how SMA utilizes three different kinds of Tweet scoring methods.

How big is social media in finance and what are some of the unique challenges?

January 23, 2015

SMA's chief executive, Joe Gits, explains the challenges in applying data from social media to the financial market, as well as the evolution of sentiment score calculation.

What can I do with Social Media Sentiment?

January 16, 2015

This piece explains the different ways social media sentiment can be applied in multiple areas.

Social Market Analytics featured in Red Rocket’s ‘Best Startups for 2014’

December 18, 2014

SMA is announced to be one of the "Best Startups of the Year" by Red Rocket.

Weekly trade highlights from the EDGE report

December 18, 2014

Energy stocks dominated the EDGE reports (which illustrates the most positive and negative industries and the sentiment of all sectors) this week.

An Analysis of Returns and Transaction Costs using an Open-to-Close Methodology

December 1, 2014

This piece covers a transaction cost analysis over SMA's open-to-close demonstration of how social media data provides a valuable addition to a trading strategy.

Weekly trade highlights from the EDGE report

November 26, 2014

This blog looks at the highlights from the EDGE report in the week of Nov. 24.

Weekly trade highlights from The EDGE Report

November 24, 2014

This blog looks at the highlights from the EDGE report as the Q3 earnings season winds down.

Social Market Analytics is now blogging!

October 30, 2014

SMA harnesses the power of social media signals to deliver up-to-the-minute golden nuggets of social sentiment.

Edge Ratio Analysis (Equity)

October 27, 2014

SMA leverages over 2 years of its intraday sentiment factors on U.S. securities to establish evidence of trading signals born from social media, utilizing John Sweeney's Edge Ratio as a metric to validate signals derived from SMA S-Factors™.

Deltix - A Crossover Study (Equity)

October 24, 2014

This paper gives a third party illustration of SMA metrics in an automated trading strategy. It details how Deltix, a provider of analytics software and services, has used social media factors to create a profitable trading system.

S-Factors Definition Use and Significance

October 23, 2014

SMA's original white paper. This piece introduces S-Factors™, a proprietary set of sentiment metrics. It also explores how they can be used to predict price movement in the capital markets.

From Icahn to 'I can' social trading takes off

July 30, 2014

"Twitter is great. I like it almost as much as I like Dell,” Carl Icahn, the activist investor, exclaimed when he made his debut on the social media platform last year. He now counts 190,000 followers who hang on his every tweet.

StockTwits Selects Social Market Analytics to Provide its Active Traders With Enhanced Tools to Beat the Market

July 29, 2014

StockTwits partnered with SMA to deliver near real-time signals from Trader Conversations on its Platform.

Benzinga Pre-Market Info

March 7, 2014

Joe Gits, CEO & Founder at SMA speaks to Benzinga during the pre-market info segment on 03/07/14.

Markit Enhances Factors Suite With Social Media Indicators

March 4, 2014

Markit study confirms social media sentiment measures are effective signals of future stock performance.

Markit Research Signals - #Alpha Extracting Market Sentiment from 140 Characters (Equity)

March 3, 2014

This research paper is an introduction to SMA's alpha-generating social media indicators from our partner at Markit.

First Business: Tweeting For Profit

February 17, 2014

Diane Moca reports on how social media and markets come together with mixed results.

Real Money With Ali Velshi

February 5, 2014

Joe Gits, CEO of SMA, describes the process of harvesting Twitter to provide social media sentiment.

Big Data Technology That Beat The Market By 50 Percent In 2013 Now Available To Day Traders

January 28, 2014

Active individual traders now have access to the same up-to-the-minute “Sentiment” signals available to NYSE Technologies and Markit data clients.

FOX Business: How Twitter Helps Hedge Funds Find Lucrative Stock Tips

November 7, 2013

A Canadian newspaper sent out a little-seen Tweet at 8:12 a.m. ET on Monday breaking the news that BlackBerry’s (BBRY) $4.7 billion buyout had gone up in flames. Within seconds, the clients of real-time information discovery service Dataminr received an alert warning them about the news.

NYSE Technologies And SMA To Distribute Social Media Analysis Data Via SFTI

October 22, 2013

NYSE Technologies and SMA have announced an agreement to distribute sentiment statistics from SMA’s patent-pending social media monitoring engine through NYSE Technologies SFTI Network, and its normalized market data service, SuperFeed.

American Way: Twitter Invades The Stock Market

October 15, 2013

Somebody will likely tweet this story, commenting on it for better or worse. That single tweet, a drop of water, will flow into a gushing firehose of tweets — something like 400 million worldwide each day on every possible subject.

Financial Times: Traders Turn To Twitter For Stock Tips

October 11, 2013

As Twitter’s flotation approaches, Wall Street analysts are building models to calculate what it might be worth – with a figure of up to $15 billion doing the rounds.

Traders turn to Twitter for stock tips

October 11, 2013

Joe Gits, founder of Chicago-based Social Media Analytics, says he expects a turnover of $60m in two years from his system. SMA measures how far sentiment is from the norm for 8,000 US equities, from tweets by 400,000 people identified as financial professionals, active traders or market influencers.

Tabb Forum: Social Engineering: Capturing The Alpha In The Twittersphere

March 27, 2013

Given the mass popularity of social media, many equity market participants are jumping on the bandwagon. But in the case of hedge funds and other trading firms, it is alpha that drives the interest, not entertainment.

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