Andreas Joseph
Andreas Joseph
Research Economist, Bank of England
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Machine learning at central banks
C Chakraborty, A Joseph
Staff Working Paper Series, 2017
Parametric inference with universal function approximators
A Joseph
arXiv, 1903.04209, 2019
Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach
K Bluwstein, M Buckmann, A Joseph, S Kapadia, Ö Simsek
Journal of International Economics, 2023
All you need is cash: Corporate cash holdings and investment after the financial crisis
A Joseph, C Kneer, N Van Horen, J Saleheen
CEPR Discussion Paper No. DP14199, 2022
OTC Microstructure in a Period of Stress: A Multi-layered Network Approach
A Joseph, M Vasios
Journal of Banking & Finance, 106400, 2022
Cross-border portfolio investment networks and indicators for financial crises
A Joseph, S Joseph, G Chen
Scientific Reports 4 (3991), 2014
Compendium on the diagnostic toolkit for competitiveness
P Karadeloglou, K Benkovskis, G Aiello, B Bluhm, E Bobeica, C Buelens, ...
Network centrality and key economic indicators: A case study
A Joseph, G Chen
Network Models in Economics and Finance, 159-180, 2014
Composite centrality: A natural scale for complex evolving networks
AC Joseph, G Chen
Physica D: Nonlinear Phenomena 267, 58-67, 2014
Forecasting UK inflation bottom up
GK Andreas Joseph, Galina Potjagailo, Eleni Kalamara
Bank of England Staff Working Paper 915, 2021
Complex Networks & Their Applications V: Proceedings of the 5th International Workshop on Complex Networks and Their Applications (COMPLEX NETWORKS 2016)
H Cherifi, S Gaito, W Quattrociocchi, A Sala
Springer, 2016
An interpretable machine learning workflow with an application to economic forecasting
M Buckmann, A Joseph
An Interpretable Machine Learning Workflow with An Application to Economic …, 2022
Machine learning at central banks. Bank of England
C Chakraborty, A Joseph
Working Paper, 2017
Netconomics: Novel Forecasting Techniques from the Combination of Big Data, Network Science and Economics
A Joseph, I Vodenska, E Stanley, G Chen
arXiv preprint arXiv:1403.0848, 2014
Deep reinforcement learning in a monetary model
M Chen, A Joseph, M Kumhof, X Pan, R Shi, X Zhou
arXiv preprint arXiv:2104.09368, 2021
Degree-energy-based local random routing strategies for sensor networks
F Yan, AKH Yeung, AC Joseph, G Chen
Communications in Nonlinear Science and Numerical Simulation 20 (1), 250-262, 2015
A framework for statistical inference on machine learning models
A Joseph, S Regressions
Working Paper, Bank of England, 2019
Opening the machine learning black box
A Joseph
Bank Underground Blog, Bank of England, 2019
Interactions between financial and environmental networks in OECD countries
F Ruzzenenti, A Joseph, E Ticci, P Vozzella, G Gabbi
Plos one 10 (9), e0136767, 2015
Opening the black box: Machine learning interpretability and inference tools with an application to economic forecasting
M Buckmann, A Joseph, H Robertson
Data Science for Economics and Finance: Methodologies and Applications, 43-63, 2021
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