Social Market Analytics, Inc. and the Lightspeed Trader Platform

By: Koburn Weisman

Traditional sources of information for active traders include analyst estimates, news stories, measures of market volatility and various trading tools. Recently, “social sentiment” investing tools have become a common resource as well, designed to aggregate and analyze social media data to produce predictive market analytics. While other types of investment analysis should be included in investment decisions, social media data can assist in providing investors with indications of future market and economic performance along with, in some cases, positive or negative ratings of stocks and potential trading and investment strategies.

Social Market Analytics, Inc.:
Founded in 2011, Social Market Analytics, Inc. (SMA) goal is to harness the massive amount of unstructured financial data across both Alternative and Traditional sources into machine readable feeds and market intelligence. Over the last decade, SMA has become the leader in providing APIs for quantitative systemic trading firms and market makers. SMA’s patented processes provide the financial and marketing communities with new data sources to evaluate financial data sets, enhance returns, and reduce risk, allowing SMA to operate as a predictive analytics FinTech firm. SMA has partnered with Lightspeed Financial Services Group (Lightspeed) to provide data as a visual, updated every minute.

SMA Factor Performance:

The graph above shows Open-to-Close returns for US Equities that have an S-Score (Sentiment) greater than +2.000 or less than -2.000 at 9:10 AM ET, highlighting the predictive nature of SMA’s data.

The green line represents the performance of all stocks with a S-Score greater than +2.000 at 9:10 AM ET (20 minutes before the market open). Data suggests that this group of stocks would outperform the market due to the significantly high sentiment surrounding these stocks.

The orange line shows the performance of all stocks with a S-Score less than -2.000 at 9:10 AM ET. Data predicts an underperformance from this group of stocks because of their significantly negative mentions on Twitter.

The position is entered on the Open and is then liquidated on the Close. This strategy does not take into account trade costs, bid/offer spreads, or trade slippage.

How Traders Use SMA on Lightspeed:

Trade Ideas: 
SMA covers the broad U.S. Equity market across small, medium, and large cap stocks, filtering through roughly 1 billion Tweets a day to capture all conversations relating to US Equities. SMA’s technologies provide a live Top/Bottom 10 Watchlist, live Market Sentiment and Tweet Volume on individual securities, and once a day snapshot on Sentiment from the most accurate Twitter accounts. Oftentimes news breaks on Twitter ahead of traditional media outlets, allowing traders to track sentiment spikes as news breaks. As SMA captures ongoing Twitter sentiment for U.S. equities, Lightspeed lets you know by the minute.

Position Monitoring: 
SMA helps traders monitor open positions by updating Sentiment every 60 seconds. SMA’s Odometer on Lightspeed lets traders monitor Sentiment in near real time and understand why Sentiment on a stock reports as positive, negative, or neutral.

Trade Execution: 
Trade Cost Analysis (TCA) plays a large part in understanding how execution effects returns (alpha), especially for large institutional firms. TWAP (time weighted) and VWAP (volume weighted) algorithmic execution models, especially, have become very popular over the past decade. Depending on the sentiment of a stock and the change in sentiment, a trader might be inclined to TWAP or VWAP their execution. For instance, if a trader wants to buy AAPL and the stock’s sentiment is positive, the trader may choose to buy at the market. However, if AAPL’s sentiment is negative, the trader might choose to buy over a period of time during the session while monitoring Sentiment*. SMA’s Sentiment Trend Chart can help track these sentiments in real time. 

Accurate Accounts:
Accurate Accounts are the SMA version of the Starmine product by Refinitiv that ranks Equity Analysts. SMA rates Twitter accounts talking about stocks with a 12-factor algorithm. One of those factors is the accuracy of accounts when they talk positively or negatively about a stock over different holding periods. SMA measures this over 1 day, 2 days, 1 week, and 1 month holding periods. Every day SMA extracts the 100 most accurate accounts for each holding period and display what percentage of those accounts are speaking positively or negatively about securities. This widget is updated every day.

About SMA: SMA has developed Intellectual Property in four areas FinTech Areas:

  1. Sentiment NLP – Financial Sentiment is difficult. SMA captures both words and phrases and fine scores each phrase from -1.000 to +1.000. SMA then aggregates conversation at the individual stock level to arrive at our S-Score (a Z-Score from -4.25 to +4.25). SMA captures all conversation from fundamental, technical, trading, product, c-suite, etc. The SMA Dictionary is Machine Learning in a Supervised and Unsupervised environment with regression analysis each quarter to ensure improvements continue.
  2. Topic Modeling –- $-tags and #-tags are the starting building blocks for stock level Topic Modeling. SMA goes much deeper. Our Machine Learning process makes suggestions for inclusions and exclusions to each topic model. For example, for Tesla’s topic model we want include conversation around Solar City and not conversation about Nicola Tesla. We capture Tim Apple as a euphemism to Tim Cook. We eliminate bad bots and actors. Modeling is able to distinguish between tickers like $ETH for Ethan Allan the furniture maker and $ETH Ethereum the Crypto Currency. SMA’s goal is to capture all Tweets relevant to the stock. 
  3. Source Accuracy – SMA discovered that it is not just what is being said on Social Media, but who is saying it. SMA ranks everyone talking about stocks on Twitter with a 12-step algorithm to rate each Twitter account. A minimum threshold must be passed by the Twitter account to be included in our SMA’s ‘Alpha’ universe.
  4. Textual Parsing – SMA has built its own source agnostic Textual Parsing engine, which allows any raw textual document to be parsed and broken down by section with sentiment data at the section level.

For more information on SMA’s integration with Lightspeed Trader, watch Lightspeed’s Social Media Predictive Data webinar outlining SMA’s real-time metrics available for active traders on the Lightspeed Trader platform.

*Disclaimer: SMA is just one of many information points and although helpful, other factors should be considered when trading.

Active Trading with Lightspeed
Lightspeed provides professional traders with all the tools required to help them find success in stock trading, and we have been developing and honing our active trader platform to offer an optimal user experience. With the intuitive interface layouts and institutional quality stock and options scanners, we aim to help traders reach their goals, no matter what their strategy is. We also offer our clients some of the lowest trading fees in the industry.

For more information on a professional trading platform with Lightspeed, please call us at 1-888-577-3123, request a demo or to open an account.

About Social Market Analytics, Inc.
Founded in 2011, Social Market Analytics, Inc. (SMA) goal is 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. 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. SMA data is delivered at the Security (Ticker) level across all Asset Classes.

For more information, visit

Lightspeed Financial Services Group LLC is not affiliated with these third-party market commentators/educators or service providers. Data, information, and material (“content”) are provided for informational and educational purposes only. This content neither is, nor should be construed as an offer, solicitation, or recommendation to buy or sell any securities or contracts. Any investment decisions made by the user through the use of such content is solely based on the users independent analysis taking into consideration your financial circumstances, investment objectives, and risk tolerance. Lightspeed Financial Services Group LLC does not endorse, offer nor recommend any of the services or commentary provided by any of the market commentators/educators or service providers and any information used to execute any trading strategies are solely based on the independent analysis of the user.

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