THE A.I. REVOLUTION: IS THE PORTFOLIO MANAGER A DYING ... · IS THE PORTFOLIO MANAGER A DYING...
Transcript of THE A.I. REVOLUTION: IS THE PORTFOLIO MANAGER A DYING ... · IS THE PORTFOLIO MANAGER A DYING...
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N a m e
N E W Z E A L A N D I N V E S T M E N T B R I E F I N G 2 0 1 7
THE A. I . REVOLUTION:IS THE PORTFOLIO MANAGER A DYING BREED?
N E W Z E A L A N D I N V E S T M E N T B R I E F I N G 2 0 1 7
D a v i d S c o b i eH e a d o f C o n s u l t i n g , N Z
H a m i s h D i n g w a l lTe c h n o l o g y A n a l y s t , B a i l l i e G i f f o r d
J o a n n a N a s hA u s t r a l i a n E q u i t i e s V P, B l a c k r o c k
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I N T H E B E G I N N I N GA R E V O L U T I O N T A K E S H O L D
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A R T I F I C I A L I N T E L L I G E N C ET H E A L L - S E E I N G M E C H A N I C A L E Y E
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A S K I N G T H E O R A C L EA . I . O N A . I .
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N AV I G AT I N G T H E I R R E G U L A RW H O I S T H E H O L D E R O F T R U E K N O W L E D G E ?
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A . I . T O D AY, A . I . T O M O R R O WA P A T H T O W A R D ‘ T H I N K I N G M A C H I N E S ’
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P O R T F O L I O M A N A G E R O F T H E F U T U R EM A N T O B E R E P L A C E D B Y M A C H I N E ?
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T E C H – TA K E 1E D I N B U R G H 1 9 8 7
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T E C H – TA K E 2E D I N B U R G H 2 0 1 7
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T E C H – TA K E 3T H E N E W B A I L L I E A N D G I F F O R D ?
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W H AT I S B I G D ATA ? A W O R L D O F N E W P O S S I B I L I T I E S F O R G E N E R A T I N G α
Big Data is often:• Less structured
• Larger in volume
• Higher in frequency
• Digital traces of human behaviour
• A relative term
Examples:• Text: email, filings, broker reports,
conf. call transcripts• Internet search activity• Social media: Twitter, Facebook,
Google+, LinkedIn• Images
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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 to generate alpha.
A P P LY I N G B I G D ATAK E Y P O I N T S
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H O W C A N W E U S E I T ? P R E D I C T I N G E L E C T I O N R E S U L T S
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• Apply large-scale learning algorithm to produce alpha forecasts based on stock specific attributes combinations.
• 400 attributes × 45,000 stocks × 20 years = 250 GB of historical data.
• Similar techniques used for ad click predictions.
Signal Performance
Stock Attributes
Stock-Specific Combinations
• Source BlackRock: Data provided For illustrative purposes only
S T O C K L E V E L S I G N A L C O M B I N A T I O N
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I M P L I C AT I O N S O F A . I .Q & A
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• A.I. continues to improve at:
- Codifying and ‘squeezing’ market patterns
- Executing data and momentum-driven trades
• But A.I. struggles to:
- Deduce what is currently priced into a stock
- Predict disruption and second-order effects
• Many insight-driven firms will be dominated by human input
• But the hiring question will increasingly be – should he/she be a data scientist?
C O N C L U D I N G T H O U G H T SI S T H E P O R T F O L I O M A N A G E R A D Y I N G B R E E D ?
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F I N A L W I S D O M
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