CBOE – Social Market Analytics SMLCW Index significantly outperforms.

Social Market Analytics aggregates the intentions of professional investors as expressed on Twitter.  SMA factors are highly predictive over various time frames.  In June of 2017 Social Market Analytics launched a weekly re-balanced large cap sentiment based index.  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 index has been published daily since that date and is available on all major feeds.

Last year the SP500 Index had a return of -8.4%.  The CBOE SMLC Index had a return of +.87%.  Below is a comparative return chart over the last year compared to the SP500.

For more information or to license this index please contact us at ContactUs@SocialMarketAnalytics.com

smlcw performance

 

 

 

Power of Predictive Alpha in a Bear Market

This year has been tough for most investment strategies.  Firms using traditional sources of data are generating the same underwhelming returns.  Two years ago, Social Market Analytics, Inc.  (SMA)  (Twitter)   launched the SMLCW index in partnership with the CBOE.  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.  It’s A long only index of super-cap stocks with unusually positive Twitter conversations.

SMA publishes a family of metrics providing a full representation of the Twitter conversation across equities (US and LSE), commodities, currencies, ETF’s & Cryptos.

S-Score is a normalized representation of the current Twitter conversation of professional investors as identified by Social Market Analytics patented algorithms.  SMA has access to the full Twitter feed through our licensed partnership with Twitter and listens in real-time for any mention of topics and securities of interest.  These Tweets are scanned in real-time for sentiment and influence of the poster and compared to prior conversations over the look back period.  Securities with higher S-Scores subsequently outperform and securities with negative S-Scores under-perform.

SMA S-Scores are predictive over multiple prediction periods.  With seven years of out-of-sample data we can extend our comparison baselines and predict over longer periods.

Year-To-Date the SMLCW index is up over 7.5% while the SP500 is flat.  Subtracting a couple percent for commissions/slippage and the index is still significantly positive. This is not a back-test, this index has been live and on your quote screens for nearly two years.  YTD actual performance chart from the CBOE site is below.

SMLCW - YTD

As mentioned, this is a long only index.  During the recent market drawdown this long index has been performing.  SMA negative S-Score stocks have been moving lower at a significant rate – generating positive alpha.  Below is a chart of the SMLCW index compared to the SP500.  for any questions or to learn more please contact us at:  ContactUs@SocialMarketAnalytics.com.

Thanks,

Joe

 

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

Social Market Analytics, Inc. (SMA) partnered with the Cboe in January 2017 to release the SMLCW Index ‘Cboe – SMA Large Cap Weekly Index’. 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.

SMA has two U.S. Patents around its machine learning and NLP processes that produce predictive analytics at the security level across U.S. and UK stocks, ETFs, FX, Futures, and Crypto Currencies

The SMLCW portfolio is an equally-weighted Long Only portfolio of 25 stocks drawn from the CBOE Large-Cap Universe with the highest average 5-period S-Scores. Stocks in this universe (a) are in the top 15% capitalization tranche of stocks that are the underlying for options listed on the CBOE (approximately 3000 stocks) and (b) have a market capitalization greater than or equal to $10 billion.

SMLCW YTD

The CBOE Large-Cap Universe is reconstituted quarterly on the third Friday of the month. The SMLCW portfolio is reconstituted every Friday at 8:30 am CT, based on average 5-period SMA S-Scores at 8:10 am CT. A period is a date on which there is sufficient social media data to derive SMA S-Scores. Stocks are deemed sold and purchased at market-on-open prices. The portfolio is held until 8:30 am CT on the next Friday. If Friday is a business holiday, the portfolio is rebalanced on the preceding Thursday.

To learn more, visit SMA at www.socialmarketanalytics.com or the Cboe website at http://www.cboe.com/products/social-media-indexes

 

 

 

 

 

 

 

 

 

Predicting LSE Security Price Movements with Twitter Sentiment

Social Market Analytics, Inc. (SMA) aggregates the intentions of professional investors as expressed on Twitter & StockTwits and publishes a series of metrics that describes the current conversation relative to historical benchmarks.  Our data is a leading indicator of price movement both positive and negative.

There is unique predictive information in unstructured content.  Social Market Analytics use AI and Machine Learning techniques developed over the last eight years to convert this unstructured content into data suitable for quantitative analysis. This opens a whole new area of big data analysis.

Social Market Analytics (SMA) calculates predictive sentiment on the entire US equity universe, Currencies, Commodities, Crypto currencies, ETF’s and custom sources.   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. Below is a cumulative quintile distribution of returns based on our S-Score metrics.  Our S-Score is effectively a Z-Score comparing 24-hour sentiment based on the Tweets of professional investors compared to a 20-day baseline.   Prediction periods vary per asset class and baseline. Longer baseline comparisons lead to longer prediction periods.

Stocks with abnormally positive conversations typically outperform their peers and stocks with abnormally negative conversations typically underperform their peers.  As expected conversations with normal positive or negative tones perform like the overall market.

Below is a typical quintile chart for the LSE 1000 universe tracked from post Brexit to 8/31/2018. The spread between the top and bottom quintiles is 10% annualized.   Sharpe and Sortino ratios are in the table below that.  To learn more or request a historical data set contact SMA with any questions ContactUS@SocialMarketAnalytics.com

LSEQuintiles 1

LSE Quintiles2

Social Market Analytics Sentiment Data for Forex Trading

Social Market Analytics (SMA)  provides real-time sentiment data for equities (North America & LSE), commodities, foreign exchange, Crypto Currencies and ETF’s.

In this blog I am going to explore a trading system using the SMA Twitter based sentiment data to trade a basket of: EURUSD, EURGBP, GBPJPY, GBPUSD ,USDCAD ,USDCHF ,USDJPY.

We will explore two straight forward trading systems:

  • Forex Sentiment RSI: Daily Long/Short Strategy
  • SMA S-Score Based Currency Selection Model

RSI Calculation Methodology 

CurrencyBlog 1

This strategy is a single-factor model solely based on adjusting daily weights according to 3-Day Sentiment RSI on the 7 of the highest daily volume Forex pairs. It is long-short with the assumption that tails act with similar magnitude.

  • Long/Short
    1. RSI >= 50, Long
    2. RSI < 50, Short
  • 50% Long & 50% Short Asset Allocation
    1. Long weights are calculated using only longs
    2. Short weights are calculated using only shorts
  • Daily weight adjusted following:
    1. separately for the long side and the short side

 

currencyBlog2

The strategy significantly improves returns compared to an equal weighted baseline.  Sharpe and Sortino ratios are statistically significant:

  • Sharpe Ratio:
    • 2.77 Jan 03, 2017 to July 19, 2018
    • 3.40 YTD
  • Sortino Ratio:
    • 5.40 Jan 03, 2017 to July 19, 2018
    • 7.46 YTD

The volatility of each leg of the strategy is either kept stable or decreased in comparison with the baseline.

SMA S-Score Based Currency Selection Model

This daily trading strategy is based on the S-Score at 09:10:00 EST and executing a 24-hour hold based on these values at 09:15:00 EST. We find consistency across execution times.  The goal is to assess sentiment and take make a directional trade in agreeance, given that the sentiment falls at least 1 standard deviation from the 20-day mean.

Equal weighted based on standard deviation criteria:

– Long: S-Score > 1

– Short: S-Score < -1

– Baseline: Equal Weighted Portfolio of the 7 Currency pair

Long and short legs are capped at 50% of the daily portfolio, even on the occurrence of an outlier day where all pairs are long, or all pairs are short.

currencyBlog3

 

The strategy drastically improves returns compared an equal weighted baseline.  Up to 40% cumulative over a 19-month period with a consistent annual rate of return.

  • Sharpe Ratio:
    • 2.56 Jan 03, 2017 to July 19, 2018
    • 3.56 YTD
  • Sortino Ratio:
    • 4.93 Jan 03, 2017 to July 19, 2018
    • 7.72 YTD

These are straight forward strategies that illustrate the predictive nature of our dataset.  Twitter and StockTwits based factors.  To learn more about how Social Market Analytics sentiment data can help your trading please contact us at contactus@Socialmarketanalytics.com or Doug Hopkins @ (312) 788-2621.