SlideShare a Scribd company logo
- ‹#› -
Beyond Semantic Analysis: Utilizing Social Finance
Data Sets to Improve Quantitative Investment Models
Leigh Drogen
Estimize Founder and CEO
New Social Finance Data Sets
2
New Social Finance Data Sets
3
Wait a minute….
Why is Bloomberg on that slide?
New Social Finance Data Sets
4
Did you know that Bloomberg sells
access to the entire corpus of its
users’ anonymized chat history?
New Social Finance Data Sets
5
Please collect your blown minds from
the floor now so that we can move on.
Moving Beyond Sentiment and Semantic Analysis
6
Moving Beyond Sentiment and Semantic Analysis
7
•Proxy for investor attention
•Identifying market influencers
•Larger and more diverse sample sets
•Removing the sell side bias
Academic Studies
8
• Wisdom of Crowds: The Value of Stock Opinions Transmitted
Through Social Media - Hailiang Chen, Prabuddah De, Jeffrey
Hu, and Byoung Hwang
• Crowdsourcing Forecasts: Competition for Sell Side Analysts?
- Rick Johnston
• Generating Abnormal Returns Using Crowdsourced Estimates
from Estimize - Leigh Drogen and Vinesh Jha
• The Value of Crowdsourcing: Evidence From Earnings
Forecasts - Barbara Bliss
Estimize Pre Earnings Drift
9
Estimize Pre Earnings Drift
10
11
Estimize Post Earnings Drift
Estimize Post Earnings Drift
12
Estimize Post Earnings Drift
13
Estimize Post Earnings Drift
14
Estimize Notable Estimates
15
• Differ from the average estimate by a minimum percentage, or by a
minimum standard deviation, reflecting fact that some stocks naturally
have less uncertainty built into their estimates.
• If stock’s earnings have previously deviated significantly from
expectations, Notable Estimate must be even more differentiated - as
these companies are likely to report farther away from the crowd’s
expectations.
• Estimate must be made at least five days in advance of expected
earnings in order to be considered Notable.
• Contributor must have a strong track record of providing accurate
earnings estimates to Estimize within the sector.
Stock Groupings
16
• GICS industry and sector groupings are generated based on how
companies produce revenue.
• While sell side analysts organize along these lines, the vast majority of
market participants do not.
• Social finance platforms like Estimize, SeekingAlpha, StockTwits or
Twitter allow users to contribute across whatever stocks they wish.
• By looking at the overlap in these stocks we are able to create higher
correlated groupings.
• These groupings can be used as an alternative risk factor when
constructing portfolios.
Investor Attention Proxy
17
• Social finance platforms give an opportunity to measure what investors
are looking at and talking about, enabling us to measure several
heuristics including information availability.
• The immediate price and volume reaction to a firm’s earning surprise is
much stronger, and the post-earnings announcement drift is much
weaker for firms with crowd following.
• Higher levels of trading volume surrounding earnings announcements
for firms that have an active investor following.
• Rise and decline in investor attention on other platforms (OpenFolio,
Slingshot Insights, StockTwits) may provide similar insights.
- ‹#› -
Thank you!
L@estimize.com

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Beyond Semantic Analysis Utilizing Social Finance Data Sets to Improve Quantitative Investment Models by Leigh Drogen, founder and CEO of Estimize

  • 1. - ‹#› - Beyond Semantic Analysis: Utilizing Social Finance Data Sets to Improve Quantitative Investment Models Leigh Drogen Estimize Founder and CEO
  • 2. New Social Finance Data Sets 2
  • 3. New Social Finance Data Sets 3 Wait a minute…. Why is Bloomberg on that slide?
  • 4. New Social Finance Data Sets 4 Did you know that Bloomberg sells access to the entire corpus of its users’ anonymized chat history?
  • 5. New Social Finance Data Sets 5 Please collect your blown minds from the floor now so that we can move on.
  • 6. Moving Beyond Sentiment and Semantic Analysis 6
  • 7. Moving Beyond Sentiment and Semantic Analysis 7 •Proxy for investor attention •Identifying market influencers •Larger and more diverse sample sets •Removing the sell side bias
  • 8. Academic Studies 8 • Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media - Hailiang Chen, Prabuddah De, Jeffrey Hu, and Byoung Hwang • Crowdsourcing Forecasts: Competition for Sell Side Analysts? - Rick Johnston • Generating Abnormal Returns Using Crowdsourced Estimates from Estimize - Leigh Drogen and Vinesh Jha • The Value of Crowdsourcing: Evidence From Earnings Forecasts - Barbara Bliss
  • 15. Estimize Notable Estimates 15 • Differ from the average estimate by a minimum percentage, or by a minimum standard deviation, reflecting fact that some stocks naturally have less uncertainty built into their estimates. • If stock’s earnings have previously deviated significantly from expectations, Notable Estimate must be even more differentiated - as these companies are likely to report farther away from the crowd’s expectations. • Estimate must be made at least five days in advance of expected earnings in order to be considered Notable. • Contributor must have a strong track record of providing accurate earnings estimates to Estimize within the sector.
  • 16. Stock Groupings 16 • GICS industry and sector groupings are generated based on how companies produce revenue. • While sell side analysts organize along these lines, the vast majority of market participants do not. • Social finance platforms like Estimize, SeekingAlpha, StockTwits or Twitter allow users to contribute across whatever stocks they wish. • By looking at the overlap in these stocks we are able to create higher correlated groupings. • These groupings can be used as an alternative risk factor when constructing portfolios.
  • 17. Investor Attention Proxy 17 • Social finance platforms give an opportunity to measure what investors are looking at and talking about, enabling us to measure several heuristics including information availability. • The immediate price and volume reaction to a firm’s earning surprise is much stronger, and the post-earnings announcement drift is much weaker for firms with crowd following. • Higher levels of trading volume surrounding earnings announcements for firms that have an active investor following. • Rise and decline in investor attention on other platforms (OpenFolio, Slingshot Insights, StockTwits) may provide similar insights.
  • 18. - ‹#› - Thank you! L@estimize.com