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Big Data and Machine-Learning: What’s Next for Quantitative Investing Sylvain Champonnois, Active Equities
January, 2018
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A world of new possibilities for generating alpha
Source: BlackRock, September 2017. For illustrative purposes only. FOR USE WITH FINANCIAL PROFESSIONALS ONLY – PROPRIETARY AND CONFIDENTIAL
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I want to talk about…
MINDSET
EXAMPLES
FUTURE
How we need to think to succeed in this space
Some things we learned along the way
Where we think things are going
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BlackRock Systematic Active Equity +30 years of Innovation
Research Focus Evolution
• +$100B AUM, a pioneer of quantitative investing
ESG/Impact Machine Learning
• Systematic investment management seeking consistent and high quality alpha
Big Data Macro Themes
• Research driven process blending deep investment experience and insight with cutting edge technology
Flows Earnings Quality Analyst Sentiment Fundamental Value 1985
1990
1995
2000
2005
2010
2015
2017
Source: BlackRock, September 2017. For illustrative purposes only. FOR USE WITH FINANCIAL PROFESSIONALS ONLY - PROPRIETARY AND CONFIDENTIAL
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Mindset
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Toy model Skepticism Hostile
Thoughtful
Dangerous Knowledge
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What is data science?
Source: BlackRock, September 2017, Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data. D. Hallac, S. Vare, S. Boyd, J. Leskovec For illustrative purposes only. FOR USE WITH FINANCIAL PROFESSIONALS ONLY - PROPRIETARY AND CONFIDENTIAL
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Examples
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Feature combination Signal Performance
StockÂSpecific Combinations
Stock Attributes
Source BlackRock: Data provided For illustrative purposes only, not meant to depict actual data
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ML Framework for Sentiment Based Signals Motivation: Reinforce every component of the model against the eventual objective (e.g., forecasting forward returns)
A stacked learner
Dictionary Learning
Time series Learning
Source: BlackRock, for illustrative purposes only
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How can we track consumption? More leading Online Search
Website traffic
GPS traffic data
Satellite images
E-transactions receipts
Booked sales
Credit card data
More accurate Source: BlackRock, 2016, for illustrative purposes only
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Future
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Direction of travel
Small Data Low Dimensionality General, Linear, Static
Big Data High Dimensionality Customized, Non Linear Dynamic
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TALENT
STYLE: CULTURE, ENVIRONMENT, MARKETING
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APPLICATIONS AND BUSINESS MODELS
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Lots of stuff going on…
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DATA: LARGE, FAST, UNSTRUCTURED
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ALGORITHMS: MATH, STATISTICS, COMPUTER SCIENCE,
CODE: COMPUTE INFRASTRUCTURE, OPEN SOURCE
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Key Points
Big data and machine learning do not replace investing; but increasingly, they are necessary for great investing.
Our competitors for technology, and increasingly for human capital, are not financial firms; they are technology firms.
These techniques are actively used in our models in an effort to generate alpha.
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Any research in this document has been procured and may have been acted on by BlackRock for its own purpose. The results of such research are being made available only incidentally. The views expressed do not constitute investment or any other advice and are subject to change. They do not necessarily reflect the views of any company in the BlackRock Group or any part thereof and no assurances are made as to their accuracy.
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