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Quantified News Based Trading: Is it the next big thing in algorithmic trading? “News is the first order factor that affects prices, volume, volatility of stocks, currencies, commodities, etc” This presentation explores the science behind quantified news based trading and will take you through how it is evolving with time. The presentation also highlights trading profitability results of strategies based on quantified news analytic This topic was presented by Mr. Rajib Ranjan Borah, Founder & Director, QuantInsti, at the "4th Princeton-UChicago Quant Trading Conference" in University of Chicago. This presentation will help you to understand: · What is quantified new trading? · How to quantify news report and articles? · How can you make profit using Quantified news based trading? · How is relevance scored? · What are the challenges involved in Quantified news trading? Watch a recorded video of a presentation on the same topic here: http://youtu.be/UvfhuQddUXw?list=UU8kXgHG13XdgsigIPRmrIyA
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© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantified News based Trading: is it the next big thing in algorithmic
trading ?
Rajib Ranjan Borah
Nov 8, 2013
Princeton – UChicago Quant Trading Conference
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Contents
Sr.No Topic Slide No
1 How is news quantified 5-20
2 Profitability using quantitative news analysis 22-42
3 Machine learning techniques for designing quant news strategies
44-47
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Background - how is news quantified
Profitability using quantitative news analysis
Machine learning techniques for designing quant news strategies
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Historical Perspective
1. Rothschild:
A family network spread across Europe (Frankfurt, London, Paris, Naples, Vienna) → enabled obtaining financial information before peers
Knowledge of Battle of Waterloo result one full day before others → largest private fortune in the world
2. Reuters:
News service used pigeons & telegraph in 1850s to become fastest news disseminator
Continued focus on being the fastest news source → $12.4 billion conglomerate
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
What is Quantitative News Trading?
News is the first order factor that affects prices, volume, volatility of stocks, currencies, commodities, etc
Computer programs that scan news articles & quantify them
-> can respond to price moving factors faster than humans
-> can monitor a vaster amount of news reports than humans
This field is known as ‘Quantitative News Trading’
Apart from trading, quantification of news is also utilized in
• Media evaluation
• Market research
• Brand & reputation management
• Political analysis
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
What is Quantitative News Trading?
• Sample output of a News Analytics feed: News represented by numbers
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
What is Quantitative News Trading?
News is the first order factor that affects prices, volume, volatility of stocks, currencies, commodities, etc
Computer programs that scan news articles & quantify them
-> can respond to price moving factors faster than humans
-> can monitor a vaster amount of news reports than humans
This field is known as ‘Quantitative News Trading’
‘‘During the 200 milliseconds a human is reading the latest news headline, a trading program will have downloaded the entire article, analyzed its meaning, & traded based on the content”
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
What is Quantitative News Trading?
News is the first order factor that affects prices, volume, volatility of stocks, currencies, commodities, etc
Computer programs that scan news articles & quantify them
-> can respond to price moving factors faster than humans
-> can monitor a vaster amount of news reports than humans
This field is known as ‘Quantitative News Trading’
‘‘During the 200 milliseconds a human is reading the latest news headline, a trading program will have downloaded the entire article, analyzed its meaning, & traded based on the content”
How do you quantify news reports and articles ?
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 1. Sentiment
News articles are assigned a score called ‘sentiment’
Sentiment says whether the article has a positive / negative or neutral tone
(Sale of Apple iPhones drop = -ve sentiment)
Sentiment at document level is different from sentiment at entity level
(Samsung beats Apple in smart phone sales = -ve sentiment for entity named Apple, +ve sentiment for Samsung)
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 1. Sentiment
How is ‘sentiment’ scored ?
• Naive parser: based on word count of –ve / +ve keywords
• Discriminated parser: weighted word count
• Grammatical parser: which verbs work on which objects. check linguistic semantics
• Machine Learning: From the data and the answers, try to find the factors– Generate bag-of-words: distance of subject from these sentiment
words
– Overfitting (and large vector sets), hitch-hiking and ignorance of linguistic structure
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 1. Sentiment
Scoring sentiments: grammatical parsing
• A database of words & phrases against which the article is searched
• Which verbs act on which objects
• Phrases which use adjectives & adverbs emphasize sentiments, therefore greater weightage
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 2. Relevance
How is relevance scored ?
• How many companies are mentioned in the news article
• Is the company mentioned in the headline as the subject/object
(‘Headline:UBS downgrades HSBC’ is not relevant to UBS)
• In which sentence number is the company first mentioned
• Length of the article & how many times is the firm mentioned
• Number of sentiment words & total words in article
• Two firms mentioned in a news article can both have a relevance of 1.0 (HP & Compaq announce merger)
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 2. Relevance
Issues with calculating relevance
• Requires synonym database:– IBM
– International Business Machines
– I.B.M.
– Big Blue
– BAML
– Bank of America
– Merrill Lynch
– Bank of America Merrill Lynch
– Merrill
– BoA
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 3. Novelty
How is novelty measured ?
• The keywords in the current news article are compared to historical articles about that company for similarity of digital fingerprints
• A linked articles count is generated
• Novelty is reported for – Within same news feed novelty (i.e. all Bloomberg news articles only)
– Across all news feeds novelty (i.e. across Reuters, Dow Jones, Bloomberg articles)
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 4. Market Impact
• Different types of news articles have different impacts on the price of the asset
• Another aspect of relevance is the likely market impact of the news article
• Market Impact is therefore a function of the type of news
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - News Types
Types of news:
• Accounting news– Earnings
– Trading updates (broker action, market commentary)
– Guidance
– Financial issues (buybacks, dividends, equity offerings, etc)
– Regulatory filings
• Strategic news– M&A
– Restructuring
– Product, customer, competition related
– Corporate Governance
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 5. Volume
The number of news articles on the same topic can be a useful input to validate the impact
• Volume of news in Social Media also checked sometimes
• News Analytics strategies also check market based qualitative parameters along with news -> these help check if reaction to news is not already factored in– Trading Volume in last 24 hours (and historical average volume)
– Price change in last 24 hours
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - 6. Social Media
Long term trading strategies try to gauge market sentiment from the plethora of information in the social media front
• Search engine volume counts (e.g. Google Trends) - global search for news keywords.
Can be used to confirm market impact of news
• Facebook, Twitter - user sentiment evaluated at macro level.
Many tools use certified twitter/facebook feeds only
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - Key Factors
While the following are the four key inputs:
• Sentiment
• Relevance
• Novelty
• Market Impact
Some news analytics based strategies use other factors as well…
• Volume
• Social Media
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News – Market Psyche
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Background - how is news quantified
Profitability using quantitative news analysis
Machine learning techniques for designing quant news strategies
Q&A
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Where Quantified news work
Machines are faster at responding to events than humans
Low latency event based trading (first to respond)
Machines can process a much vaster amount of information without any fatigue
Analyze broad spectrum of news to formulate broad views
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Where Quantified news work
Analyze broad spectrum of news to formulate broad views
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Where Quantified news work
Low latency event based trading (first to respond)
For synchronous (fixed releases) expected events (earnings releases/ economic figures)
• Company figures provided in xml format instead of text
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Where Quantified news work
Low latency event based trading (first to respond)
For synchronous (fixed releases) expected events (earnings releases/ economic figures)
• Company figures provided in xml format instead of text
• Economic figures provided in binary format instead of textual news articles
For asynchronous / unexpected news
• Are quantification algorithms robust enough to calculate trust-worthy sentiment, relevance, novelty scores ?
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Opportunities : initial under-reaction
Quantified news driven trades work even when the trade is done at the end of the day
(under-reaction to news immediately. Tetlock, et al)
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Late endof day response also profitable
Trading the news immediately = very profitable
At a broad level there is underreaction to news => entering into trades at the end of the day also makes profits
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Certain sectors more profitable
Moving from Non-Cyclicals to
Financials increased the profit
from 135BP to 147BP
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Sectors like Pharma, Defense, Auto, Energy, Banking more sensitive to news
Sensitivity of different sectors
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Small cap firms more profitable
Smaller Cap firms show greater response to extreme sentiment news event
(bigger firms have greater scrutiny)
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Hedged (market-neutral) is better
• Long +ve sentiment stocks only
OR
Short -ve sentiment stocks only. Will fail in different regimes
• Being long +ve sentiment stocks & short -ve sentiment stocks at the same time gives consistent returns
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Bigger moves happen when there is news in
• Stocks with low beta (i.e. surprises happen to sleepy stocks)
Surprises are more profitable
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Bigger moves happen when there is news in
• Stocks with low beta (i.e. surprises happen to sleepy stocks)
• VIX is low (i.e. surprises during calm times)
• When markets are improving (i.e. surprise to mostly long position holders)
Surprises are more profitable
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Strategy variation - sentiment changes
• Instead of absolute sentiment scores, look at changes in sentiment scores of firms
• Bought stocks with highest increase in sentiment
• Shorted stocks with highest decrease in sentiment
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Strategy variation - bottom fishing
• Bottom - fishing / turnaround stories
• Buying stocks with reversal in sentiment from grossly negative (a lot of the stocks turned out to be buybacks)
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Generating Alpha
• Soft (opinion based) vs. Hard (fact based) news
Hard news has a stronger short term reaction than soft news
How is news quantified → Profitability → Machine learning techniques → QA
Source: RavenPack, FactSet, Macquarie Research, September 2012
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
• Scheduled/expected vs. Unscheduled/unexpected
Investors react more strongly to unscheduled/ unexpected news than scheduled/ expected
How is news quantified → Profitability → Machine learning techniques → QA
Generating Alpha
Source: RavenPack, FactSet, Macquarie Research, September 2012
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
• Forecast vs Actual earnings
Investors react more strongly to forecasts than actual earnings news
How is news quantified → Profitability → Machine learning techniques → QA
Generating Alpha
Source: RavenPack, FactSet, Macquarie Research, September 2012
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
News Analytics works best with
• Small cap stocks
• Sectors like pharma, banking, etc
• Stocks with low beta
• When VIX is low
• When markets are improving
• Hard news (vis-a-vis Soft news)
• Unscheduled news events (vis-a-vis scheduled news events)
• Being market-neutral
• Doing fewer stocks, but those with stronger signals
To summarize
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - Where it fails ?
• On Sep. 7, 2008 Google’s newsbots picked up an old 2002 story about United Airlines possibly filing for bankruptcy
• UAL stock dived immediately
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News - Where it fails?
• News analytics were taught that ‘Osama-Bin-Laden’, and ‘killed’ had -ve sentiments for the markets
• On May 2 2012 when news reporting “Osama Bin-Landenkilled” were published, news bots treated this as a negative news article and sold stocks
• The two examples cited and their impacts show the extent to which people have embraced news analytics to automate trading
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Quantifying News – challenges
• Languages like Chinese and Japanese with large number of alphabetic symbols and complex grammar
However, there is a lot of development in this domain already
• The ever increasing volume of news articles from increased news sources, and from increased volumes in social media
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Background - how is news quantified
Profitability using quantitative news analysis
Machine learning techniques for designing quant news strategies
Q&A
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Machine Learning methodologies
Traditional approach => formulate hypothesis based on experience/expertise, validate statistically using historical data
Machine learning approach => output + raw data fed into a system. System reports factors within data that lead to output
Three broad approaches
• Tree
• Forest
• Planet
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Machine Learning - TREE method
Output: Post-event abnormal results
Input: Quantitative news analytics
Issues: Overfitting
(works with training data
does not work on real data)
Solution: Pruning
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Machine Learning - FOREST method
Multiple factors might impact output
Instead of one tree to solve everything,
have a forest of trees
Each tree has a vote in the output.
Weightage of vote depends on accuracy
of that tree
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Machine Learning - PLANET method
Instead of linear relationships between input and output,
Planet breaks the variable space into sections, fits linear functions within those sections
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Background - how is news quantified
Profitability using quantitative news analysis
Machine learning techniques for designing quant news strategies
Q&A
How is news quantified → Profitability → Machine learning techniques → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Contacts
For 4-month Executive Program in Algorithmic Trading:
E-PAT: 4 month weekend online program (3hrs every Sat + Sun)
• Statistics
• Quant Strategies
• Technology (coding on algorithmic trading platform)
For algorithmic trading advisory: [email protected]
To reach me directly: [email protected]
How is news quantified → Profitability → Machine learning techniques → QA