White Papers / New Research

SMA differentiates through transparency. We provide our historical data, along with results related to backtests and alpha derivation, to clients and interested firms. We invite you to review SMA and third party analysis of SMA S-Factors in the documents below.

Check the box(es) to the left of desired research heading(s). Then click the green request button to download the selected piece(s).

Application Of Sentiment Analytics To Fama-French Model

January 10, 2017

In this paper we expand on the Liew (2016) paper exploring the predictive power of StockTwits based sentiment data. We postulate 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 Liew paper.

A Returns Analysis on StockTwits Sentiment Metrics

August 25, 2016

This paper discusses the analysis of a Returns Study done on US Equities using social media sentiment factors from Social Market Analytics (SMA) 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.

Application of Social Sentiment Factors In ETF Design

July 26, 2016

The SMA Practicum Group at UIC, Urbana-Champaign, 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.

The Application of Sentiment Velocity and Acceleration Metrics in Portfolio Management

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?  We attempt to answer this question by creating a trading strategy using longer-term signals derived from S-FactorsTM data published by Social Market Analytics.  We introduce new sentiment velocity and acceleration metrics that identify the exhaustion of sentiment trends, which then function as trade entry and exit signals


SMA Research Note: Analysis of EURUSD Twitter Sentiment in December 2015

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 researh note explores two frequencies- 15 minutes and daily- both of which point to same trend.

Sentiment Enhanced ETFs

December 28, 2015

The SMA Practicum Group at UIC, Urbana-Champaign, during the Fall semester of 2015, looked at ways of enhancing ETFs.  This reserach not 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.


SMA Research Note: 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.

SMA Research Note: Twitter Sentiment and Volatility Index Directional Forecasting

August 4, 2015

 SMA and UIUC practicum group investigate the benefits of using sentiment measures in classifier models designed to predict next day directional movement for volatility indexes.

SMA Research Note: An Analysis of Equity Returns using an Open to Close Methodology

July 20, 2015

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

SMA Research Note: An Analysis of FOREX Returns using an Open to Close Methodology

July 20, 2015

SMA develops an intraday trading strategy on a basket of currency pairs using the S-Score and SV-Score factors. We study how the cummulative returns have changes for the trading stragey developed versus a benchmark by using risk adjusted returns measures. 

The Altera “Windfall” $2.4 million options trade of 03/27/15

June 15, 2015

There is a rapidly growing consensus in capital markets that rigorously analyzed information derived originally from social media can be a very valuable input in identifying trading opportunities.
Nowhere was this more evident than in what happened to Altera shares on Friday, March 27th.

SMA Research Note: Using S-Factors to Predict Trading Volume

December 19, 2014

SMA discusses how our social media driven factors can be used to forecast or enhance predictions of security trading volume.  

SMA Research Note: Edge Ratio Analysis

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. We utilize John Sweeney's Edge Ratio as a metric to validate signals derived from SMA S-Factors. 

SMA Research Note: Deltix Crossover Strategy

October 24, 2014

 Third party illustration of SMA metrics in an automated trading strategy. This piece 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.

SMA Research Note: Return and Transaction Cost Analysis of an Intraday Trading Strategy

December 1, 2014

SMA investigates an intraday momentum trading strategy based on S-Score. After running a back test, we establish the return characteristics, isolate the alpha component and explore the effect of transaction costs.