Practical challenges in dealing with news and social media analytics

1. CHALLENGES IN
DEALING WITH NEWS
AND SOCIAL MEDIA
ANALYTICS
Fred GEORJON
CEO & co-founder
frederic.georjon@infotrie.com
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www.finsents.com
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2. TOO MUCH DATA
How much can you read
in 30mn, 1h?
Can you speak Chinese,
Korean, Japanese, French,
German, Spanish?

3. MAIN METHODS
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Words count
Neg/Pos based on
dictionaries
Imprecise
Scalable
Statistical
Machine Learning &
classifications
Algorithms
Can be slow
Out/In sample
problem
Grammar
based
Pure NLP
Precise
Non scalable

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METRICS
News Items
• Topic/Entity
• Relevance
• Volume
• Buzz
• Novelty
• Sentiment
• …
(1) Das and Chen (2007)
(2) Leinweber and Sisk (2010)
Classification Accuracy
• Confusion matrix
• False positives
• Ambiguity filters, sentiment error (1)
• Disagreement
• Correlation
• Aggregation performance (2)
• …

5. SENTIMENT INDICATORS: PRICE VS NEWS
• Classical price base sentiment indicators include:
• Vix
• Put/Call ratios
• ISE Sentiment Index
• Investors Intelligence index,
• Daily Sentiment Indexes (DSI & DSIE)
• Investor Sentiment (1)
• …
• News (or social media) based sentiment indicators:
• Complement price based approaches …
• … but do not negate them
• Offer alternatives: e.g. to lack of depth for equity option market in SE Asia
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(1) Baker and Wurgler 2006

6. SENTIMENT VS FACTS
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• Sentiment is one metric
• Multiple other factual dimensions can be analysed.
• E.g. buzz, volume, searches (Google trends)
• How can I track all events leading to change in volatility?
• E.g. a change of central banker introduces volatility

7. ANALYSING PREMIUM NEWS ONLY
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• Timeliness is key
• Premium sources (1)
• Key newswire (Bloomberg, Reuters, Dow Jones …)
• Stock exchange statements
• Press releases from company websites and articles in national
business-focused newspaper
(1) Moniz, Brar, Davies, Strudwick (2011) The Handbook of News analytics in finance

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AGGREGATES
Companies
Accounting
Related
Strategic
related
Other
Places
Country
Region
Town
Macro-economic
Central Bank
IR changes
Key statistics:
Employment,
GDP …
Non Eco
Politics
War, civil
unrest,
Terrorism
Earthquake,
Tsunami..
People
Politician
Executives
VIPs

9. CORRELATION WITH MARKET
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• Critical to track correlation
• With any asset class
• Equity, Forex, Commodity, Futures, Options, Rates, Bonds, Credit
• Or statistic
• GDP
• Unemployment
• …

10. FIELDS OF APPLICATION
• Practical fields of application include:
• Event driven trading
• Pricing: e.g. predicted volatility
• Risk
• Technical indicator
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11. ACCOUNTING RELATED NEWS
Earnings Trading updates Guidance Financial issues Credit rating
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news
Announcement of
earnings
Announcements of
sales / trading
statement
Guidance / update
news
Buybacks S&P credit rating
changes
Restatements of
operating results
Conference
presentation calls
Dividend
announcements
Annual general
meetings
Sales / trading
statement calls
Debt financing
related
Special / extraor.
meetings
Shareholders /
analyst calls
Fixed income
offerings
Follow-on equity
offerings

12. STRATEGIC NEWS
M&A related Restructuring Product related Corporate
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governance
Other news
M&A rumours and
discussions
Business
reorganizations
Client announcements Executive changes –
CEO
Index changes
M&A transaction
announcements
Changes in company
bylaws / rules
Product-related
announcements
Executive changes –
CFO
Address changes
Seeking Acquisitions /
Investments
Discontinued
operations /
downsizings
Strategic alliance Executive / board
changes - other
Ticker changes
Seeking financing /
partners
Lawsuits & legal issues
Seeking to sell / divest Bankruptcy related
Spin-offs Labour-related
announcements
Business expansions

13. SECOND HANDED CONTENT?
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• Lesser known newspapers
• Finance and economic weekly magazines
• Rumours
• Blogs, Twitters, Weibo
• International press
• Social Trading
• Stocktwits, eToro, …
• Trading games
• Domain specific
• Sustainability, Ecological, Social , Governance…
• Industry specific

14. SECOND HANDED CONTENT? (CONT.)
• You might want to consider the signals as
• Fully discounted information
• Reversal signal
• Weak/contradictory information: E.g. GlaxoSmithKline
problems mentioned in Mandarin press weeks before it hits
the international ones
• A warning only, which after verification by an analyst could
lead to a monthly rebalancing of your portfolio
• Create “smart” signals out of “dumb” signals using Machine
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Learning

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AND ?
• The same type of technology can be applied
• to voice: e.g. broker-dealer conversation – at least from a
compliance angle
• to email
• to any private sources
• To chatting/ Instant Messaging systems
• Not mentioning ethical challenges & new emerging trends
where algos write articles… to later read them

16. THANK YOU!
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www.finsents.com
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