Big Data, Machine Learning, and Quantum Computing at the ... · Big Data, Machine Learning, and...
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Big Data, Machine Learning, and QuantumComputing at the Riksbank
Isaiah Hull
Sveriges Riksbank
October 20, 2019
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Big Data
Traditional Big Data
I Trade credit.
I Jacobson and von Schedvin (2015); Amberg et al. (2016);Amberg, Jacobson, von Schedvin (2018).
I Household finance.
I Jansson et al. (2012); Jansson, Haliassos, and Karabulut(2012); Jansson (2017); and Jansson, Haliassos, andKarabulut (2017).
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Big Data
Nontraditional Big Data: Housing
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Big DataNontraditional Big Data: Grocery Prices
Figure: Figure taken from Hull, Lof, and Tibblin (2017).
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Big Data
Nontraditional Big Data: Grocery Prices
Figure: Figure taken from Hull, Lof, and Tibblin (2017).
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Big Data
Nontraditional Big Data
I Housing transactions
I Rental contracts
I Satellite images
I Financial filings
I Local public services
I Online loan funding
I Fruit and vegetable prices
I Foreign travel packageprices
I Central bank speeches
I Newspaper archive
I EPU index
I Fraud complaints
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Big Data
Nontraditional Big Data: Central Bank Communication
Figure: Dynamic plot of Bank of England net sentiment.
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Big DataNontraditional Big Data: Central Bank Communication
au
in
it
jp
ez
es
be
at
lu
cz
ca
cnfr
de
pt
mx
kr
gb
us
noidse
ch
Figure: Figure taken from Armelius, Bertsch, Hull, and Zhang (2018)
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Big DataNontraditional Big Data: Housing Transactions
Figure: Daily approximation of monthly apartment price index.
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Big DataNontraditional Big Data: Housing Transactions
1973 1978 1983 1988 1993 1998 2003 2008 2013−3.5
−3.0
−2.5
−2.0
−1.5
−1.0
−0.5
0.0
JPUSGBSE
Figure: Impact of manufacturing’s decline on house price volatility(Hull, Olovsson, Walentin, and Westermark, 2017)
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Big Data
Nontraditional Big Data: Online Lending
-0.25
0.00
0.25
-200 0 200Hours Since Liftoff
Rol
ling
Mea
n of
Coe
ffici
ents
Figure: Figure taken from Bertsch, Hull, Zhang (2016).
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Machine Learning
Machine Learning
I Tax capitalizationmeasurement
I Fraud classification
I Real estate bubbleprediction
I Central bankcommunication
I Corporate defaultprediction
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Machine Learning
Machine Learning: Debiased Machine Learning
Figure: Figure taken from Grodecka and Hull (2019).
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Machine LearningMachine Learning: Transfer Learning
.........
... ...
...
...
Agree Disagree
you underestimated inflation
t+1 t+2t
0 0 0 0 21 257 351... ...
... ... ...
ht+2t+1h ht+2 ht+2
...
...
...
Figure: Figure taken from Apel, Blix Grimaldi, and Hull (2019).
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Quantum Computing
Diamanti, Hull, Sattath, Wendin (2019)
I Quantum supremacy achievable within a few years(Wendin, 2017).
I Speed-ups will enable advancement of econometrics andcomputational economics.
I Attacks will render classically-secured financial systemvulnerable.
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Quantum Computing
Diamanti, Hull, Sattath, Wendin (2019)
I MathematicalPreliminaries
I Notational Preliminaries
I Quantum Circuits
I Quantum States
I Quantum Dynamics
I Quantum Algorithms
I True Random NumberGeneration
I Quantum Money
I Pseudocode
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Quantum Computing
True Random Number Generation
Hq0 : |0
c00 : 0
Figure: Figure taken from Diamanti, Hull, Sattath, Wendin (2019).
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Quantum Computing
Diamanti, Hull, Sattath, Wendin (2019)
I Working paper available 2019:Q4.
Email: [email protected]
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