INCORPORATING NEWS ANALYTICS INTO INVESTMENT AND TRADING STRATEGIES

Richard Brown

Global Business Manager, Machine Readable News

Sentiment Symposium

April 13, 2010

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WHAT DRIVES CLIENT DEMAND?

• Differentiated content – Generate alpha (offense)

– Manage event risk (defense)

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But how?

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EXPLOITING NEWS CONTENT

• News flow is a good indicator of volume and volatility.

• Pricing movements accompanied by news tend to be momentum in nature; those with a lack of news tend to reverse to average trends.

• The market tends to overreact when there is a lot of news on something and under-react when there is a small quantity of news.

• For direction and magnitude, find cause:effect relationships

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THOMSON REUTERS NEWS ANALYTICS

• Scores text across three dimensions– Sentiment (Author tone – positive, neutral, negative)

– Relevance (Is it substantively about the company?)

– Novelty (How unique is the article?)

• Combinations of these factors enhance traditional approaches to understanding the market impact from news– News = volume and volatility

– Momentum and mean reversion

– Over/under reactions

– Signals for returns: Direction and magnitude

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THOMSON REUTERS NEWS ANALYTICS USES

• Circuit breaker / halt trading alert (Wolf detection)

• News flow algorithms (more participatory algos)

• Alpha generating signal

• Risk Management – Quantify “event risk” and manage portfolio volatility

• Compliance monitoring – detect potential market abuse

• Post trade analysis – why did the algo/strategy not work?

• Stock screening tool (good/bad news stocks)

• Fundamental research – measure company sentiment, peer analysis, aggregate for market/sector outlook

• Trader support – confirming/contrarian trading signals, volatility signals

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HOW TO MAKE MONEY WITH THOMSON REUTERS NEWS ANALYTICS

Buy on good news

Sell on bad news

Outperform S&P500 by 5000 basis points over a 60 day period!

S&P1500 stocks in 2008; Daily items >50; Pos vs Neg >50%

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THOMSON REUTERS NEWS ANALYTICS EQUITIES SAMPLE OUTPUT

Relevance: 0 - 1.0

Prevailing Sentiment: 1, 0, -1

Positive, Neutral, Negative: Probabilities which sum to 1.00, providing more granular sentiment

Novelty represented by Linked Counts: 12h, 24h; 3d, 5d, 7d

Item Type: Alert, Article, Updates, Corrections

Headline: Alert or Headline text

Topic Codes: What the story is about; RCH=Research; RES=Results; RESF=Results Forecast; MRG=Merger & Acquisitions . . .

Other metadata: Index IDs, linked references, story chains, item counts

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• Daily News & Price data in the same view (Jan-June 2007)• Daily Net Positive Sentiment [orange] : Daily sum of each item's Relevance*(Positive - Negative Sentiment)• Average Daily Price [blue]• Y-axis normalised to go from 0-100% of the respective values

• Event above shows direct correlation between dip in News Sentiment and Price on a single day• Series of Events above show close correlation between upturns in News Sentiment and Price over a sustained period of a few days (multiple short term signals lead to longer term movement)

IMPACT OF DAILY NEWS SENTIMENT ON PRICE

Dip in net positive

sentiment and price

Rise & fall in net positive sentiment

lead to similar movements in price

Upturns in Net Positive Sentiment correlate to upward price momentum

over period of a few days

• What happened here to drive the price down at the end of February?

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EXAMINING DAILY NET POSITIVE SENTIMENT VS PRICE FOR SONY

Conclusions drawn:

• Daily or intra-day sentiment can be a powerful indicator for stock price movements

– Real-time for very rapid decision-making – market making, high frequency

– Daily sentiment impact into following day/week’s price movement

– Multi-day signals for longer-term movements

– Weight and filter by relevance and novelty

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IMPACT OF CUMULATIVE NEWS SENTIMENT ON PRICE

Overall positive correlation between

Price and Cumulative Sentiment

• Cumulative Sentiment can be powerful measure to predict medium to long-term movements

• Variations:

•X day moving averages

•Relevance filtering and weighting

•De-duplication

•Multiple content sources

• Same downturn as seen previously, but visually a contrarian signal. Why???

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BENCHMARK PRICE TREND

• Drop in IBM’s share price between 2/21/07 and 3/5/07 • Corresponding drop in IBM benchmark - Special Technology Sector Spider XLK index• Broader market factors were influencing the price during this time

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1. Can News explain this downturn in Price?

2. Highlight this significant cluster of negative news stories which are only slightly relevant to IBM

PRICE TREND AND INDIVIDUAL NEWS

3. News is related to general worries on the China economy in February 2007 Human decision support:

• Analyze price movements

• Drill into news stories by type, source, sentiment, relevance, topic, other criteria

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General Observation: spikes in Quantity of News (tall bars in the top view) are co-incident with spikes in trading volume (third pane), especially when negative (second pane).

NEWS VOLUME AND TRADING VOLUME

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S&P500

ENERGYNet number of positive items

August 2007

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KEYS TO DOING IT RIGHT

• Don’t underestimate the complexity– Roll up sleeves to understand the data and the output

– Not all content is created equal

– Requires comprehensive aliasing capabilities

– Measuring entity level sentiment is critical

– Detailed sentiment is important

– More metadata is better

– Fault tolerant, fully resilient environment is a must

– Speed is important

• Choose a partner you can trust

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Questions?