Download Trading Off The News

Trading Off the News:
Applications of News Algorithms
July 1, 2008
CARISMA 2008
Alan Slomowitz
Director Product Development
Algorithmic and Trading Solutions
Dow Jones Content Technology Solutions
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Trading Off The News - HP to Acquire EDS
15:02 *WSJ: Hewlett-Packard In Advanced Talks to Acquire EDS
15:02 *WSJ: Hewlett-Packard-EDS Deal Could Come In Matter Of Days
15:03 *WSJ: Premium Expected To Be In 30% Range –Sources
15:03 *WSJ: EDS Overall Price Roughly $13 Billion -Sources >HPQ EDS
Source: DJ Newswires
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News and the Quantitative Investor:
The New Frontier
 Successful trading is about finding the crucial edge
 First to take advantage of trading opportunities
 Quantitative investors require:
 Analytical hypotheses
 Technology
 Data
 Data = News
 Exploit this new information source
 Difficult-to-quantify qualitative content
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Taking Advantage of the News
 Intuitively, investment professionals realize you
can use news to create profitable trading models
 Proprietary traders, Stat Arb desks and hedge
funds now use news to create Alpha-based
trading strategies
 News based algorithms that can profit from market anomalies lasting from mere
milliseconds to days or even longer
 Economic indicator based algorithms
 Corporate news based algorithms
 News-based algorithms are valuable additions to
Alpha generation:
 News is difficult to integrate into investment models
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Difficulty means higher value – not so easy to commoditize
Requires different tools – both data and text analysis tools
Different ways of analyzing market trends
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Making News Work for You:
Tagged, Machine-Readable News Feed
 Economic Indicator-Based Algorithms
 Arms Race – Must have a global, reliable and innovative news
provider
 Latency matters
 FX and Futures markets
 Multiple markets and countries
 Corporate News-Based Algorithms
 Scheduled events: Earnings, Guidance
 Unscheduled events: Mergers, Ratings changes, Executive
changes
 Text mining events: surprise and sentiment
 Analyzing the language of the news
 Quantifying that analysis
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Solving the Corporate News Puzzle
 Expected Corporate News Events
 Plan for releases incorporating expected, historical and actual data
 How long does it take for market to assimilate this news
 Unexpected News Events
 Cannot build an alpha algorithm for every unexpected event
 Anticipate a controlled set of pre-defined news events
 Ratings changes, executive changes, dividends
 Capability to stop algorithms that are in flight when such news events
occur
 e.g., HP announces purchase of EDS
 Adjust trading strategy for significant events
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Solving the Corporate News Puzzle (cont.)
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Complex Event Processing
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Multiple signals combined
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If EPS > X and Price moves > 3% in 5 minutes and market is up less
than 1% Then BUY XXXX shares
 Academic Research
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What the Academics are Saying
 Paul Tetlock, Quantifying Language to Measure Firms’
Fundamentals (Sept 2006/May 2007)
 Linguistic media content captures otherwise hard-to-quantify aspects
of firms’ fundamentals, which investors quickly factor into stock prices
 Simple counting of negative words can uncover negative sentiment in
earnings releases
 Antweiler and Frank, Do U.S. Stock Markets Typically
Overreact to Corporate News Stories? (October, 2005)
 Initial returns jump is typically accompanied by a temporary jump in
trading volume
 Reversal is typically accompanied by gradually declining trading
volume
 During business cycle expansions, the process is largely complete
after two or three weeks
 During recessions, the reversal is much more prolonged and we are
not able to identify a clear point at which the process ends
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What the Academics are Saying (cont.)
 Paul Tetlock, Giving Content to Investor Sentiment: The
Role of Media in the Stock Market, Journal of Finance
(June 2007)
 Academic Bibliography available
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Trading off Positive/Negative Word Counts
Long/Short Portfolio
• Firms with positive news –
Long
• Firms with negative news –
Short
• Hold for one trading day
• Rebalance at end of next
trading day
More Than Words – Quantifying Language to Measure Firms’ Fundamentals
May 2007 – Tetlock, Saar-Tsechansky, Macskassy
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Abnormal Event Returns 10 Days Prior and
10 Days Post News Releases
S&P 500 Firms
All news stories with a fraction of
negative words in the year’s top
(bottom) quartile as negative
(positive) stories
Compute difference between
reaction to positive and negative
news stories
More Than Words – Quantifying Language to Measure Firms’ Fundamentals
May 2007 – Tetlock, Saar-Tsechansky, Macskassy
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Cumulative Standardized Unexpected Earnings (SUE)
Cumulative SUE 10 quarters prior
to news and 10 quarters after news
Negative stories 30 days prior to
earnings announcements
More Than Words – Quantifying Language to Measure Firms’ Fundamentals
May 2007 – Tetlock, Saar-Tsechansky, Macskassy
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40 Minutes of Alpha
S&P 500 Companies
Beat the estimates and
you are king …
Miss your estimates and
you get hammered …
For 40 Minutes!
Research in Progress
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News Impacts: Some Examples
 Rapidly changing market conditions and news events alter
market prices and expectations
 Belief is that prices should fully reflect expectations
 News events do have significant effects on market prices and
returns
 Merger announcements
 Earnings guidance
 Interest-rate cuts
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Bank of America to Buy Countrywide
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GE Earnings Guidance
Source: DJ Newswires & MarketWatch
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Bank of England Cuts Rates
* DJ Bank of England Cuts Bank Rate To 5.25% From 5.5%
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Good News/Bad News – Profit from Both
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The Ultimate Challenge: Deriving tradable meaning from
the news
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Start with publicly available content like DJ News, press releases,
EDGAR filings
Determine analytical methodology
Back-test and determine viability
Integrate multiple models, sources
Apply to real-world
Requirements
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Large archive
Text mining tools
Sentiment models
Skilled analysts
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Potential Alphas
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Profiting from expected events
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News and momentum:
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Evidence that news gives rise to long- and short-term momentum in
prices
Overreaction and underreaction:
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Economic data changes
On news releases, stocks overshoot with prices misaligned with
fundamentals
Sentiment - Count of negative news:

A simple count of negative words in news has proven to provide
strategies with positive Alpha
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Profiting From News Has Its Challenges
 What news events to capture
 Economic data, Earnings, Guidance – the easy stuff
 Mergers & acquisitions, executive changes, bankruptcies – that’s tough
 Sentiment - ??
 Many news feeds are not tagged or machine-readable
 Need to parse, automate, and digest news
 Web-based content is another major challenge
 Need to determine:
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Which news is relevant? So many sources!
How to react to unexpected events?
Trusted sources
Is news already factored into price?
Which direction will news push the price?
© Copyright 2008 Dow Jones and Company
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Final Thoughts
 Electronic and Quantitative Trading market is rapidly evolving
 News is an increasingly important driver of automated trading
strategies
 Growing number of tradable news events
 News data algorithms
 Economic data; earnings and guidance
 Elementized News events
 Ratings changes, mergers & acquisitions, executive changes
 Trading on planned events is profitable
 If you can react quickly enough
 Not paying attention to news can cost you
 Lost Alpha opportunities
 Outright losses
© Copyright 2008 Dow Jones and Company
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Dow Jones Solutions
For Algorithmic & Quantitative Trading
Transforming News For Quantitative Trading And Research

Suite of advanced information and technology tools for a performance edge
 Unique news data, tagged and elementized
 Computer-readable
 Flexible, ultra-low-latency delivery options and seamless integration
 News sentiment tools
 20-plus-year news archives for back-testing ideas
 Tools for creating, deploying and adapting complex, news-based trading strategies

Products
 Dow Jones Elementized News Feed
 Economic Data – Major economic indicators
 Corporate Data – Earnings, Guidance, Mergers, Executive Changes, Ratings,
Bankruptcies, more
 Dow Jones News & Archives for Algorithmic Applications
 20-plus-year archive of news for analysis
 Viewer and toolkit available
 Dow Jones News Analytics
 News transformed into actionable data
 Derive analytics based on sentiment, volume, more
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Trading Off The News
Questions?
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Trading Off The News:
Applications Of News Algorithms
Alan Slomowitz: [email protected]
(201) 938-2195
© Copyright 2008 Dow Jones and Company
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