24 documents matched the search for the 2022-10-17 issue of the NEP report on Computational Economics (nep-cmp), currently edited by Stan Miles.
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11121
Model-based gym environments for limit order book trading,
Joseph Jerome, Leandro Sanchez-Betancourt, Rahul Savani and Martin Herdegen,
from arXiv.org
(2022)
Weak Supervision in Analysis of News: Application to Economic Policy Uncertainty,
Paul Trust, Ahmed Zahran and Rosane Minghim,
from arXiv.org
(2022)
Two-stage Modeling for Prediction with Confidence,
Dangxing Chen,
from arXiv.org
(2022)
An Attention Free Long Short-Term Memory for Time Series Forecasting,
Hugo Inzirillo and Ludovic De Villelongue,
from arXiv.org
(2022)
Forecasting World Trade Using Big Data and Machine Learning Techniques,
Andrei Dubovik, Adam Elbourne, Bram Hendriks and Mark Kattenberg,
from CPB Netherlands Bureau for Economic Policy Analysis
(2022)
Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques,
Nghia Chu, Binh Dao, Nga Pham, Huy Nguyen and Hien Tran,
from arXiv.org
(2023)
Tree-Based Learning in RNNs for Power Consumption Forecasting,
Roberto Baviera and Pietro Manzoni,
from arXiv.org
(2022)
Artificial Intelligence Models and Employee Lifecycle Management: A Systematic Literature Review,
Saeed Nosratabadi, Roya Khayer Zahed, Vadim Vitalievich Ponkratov and Evgeniy Vyacheslavovich Kostyrin,
from arXiv.org
(2022)
Computing XVA for American basket derivatives by Machine Learning techniques,
Ludovic Goudenege, Andrea Molent and Antonino Zanette,
from arXiv.org
(2022)
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations,
Ricardo M\"uller, Marco Schreyer, Timur Sattarov and Damian Borth,
from arXiv.org
(2022)
Uncertainty analysis of contagion processes based on a functional approach,
Zonghui Yao, Dunia López-Pintado and Sara López-Pintado,
from Universidad Pablo de Olavide, Department of Economics
(2022)
Keywords: contagion; uncertainty; functional data.
Interpreting and predicting the economy flows: A time-varying parameter global vector autoregressive integrated the machine learning model,
Yukang Jiang, Xueqin Wang, Zhixi Xiong, Haisheng Yang and Ting Tian,
from arXiv.org
(2022)
Labour supply responses to income tax changes in Spain,
Antonio Cutanda and Juan A. Sanchis,
from Department of Applied Economics II, Universidad de Valencia
(2022)
Keywords: Labour Supply; Labour Income Tax; Intertemporal Elasticity of Substitution of Leisure; Simulations
Statistical Learning of Value-at-Risk and Expected Shortfall,
D Barrera, S Cr\'epey, E Gobet, Hoang-Dung Nguyen and B Saadeddine,
from arXiv.org
(2024)
What does machine learning say about the drivers of inflation?,
Emanuel Kohlscheen,
from arXiv.org
(2023)
The boosted HP filter is more general than you might think,
Ziwei Mei, Peter Phillips and Zhentao Shi,
from arXiv.org
(2024)
Artificial Intelligence, Surveillance, and Big Data,
David Karpa, Torben Klarl and Michael Rochlitz,
from University of Bremen, Faculty of Business Studies and Economics
(2021)
Keywords: Artificial intelligence, political institutions, big data, surveillance, innovation, China
Smiles in Profiles: Improving Fairness and Efficiency Using Estimates of User Preferences in Online Marketplaces,
Susan Athey, Dean Karlan, Emil Palikot and Yuan Yuan,
from arXiv.org
(2023)
A Dynamic Stochastic Block Model for Multi-Layer Networks,
Ovielt Baltodano L\'opez and Roberto Casarin,
from arXiv.org
(2022)
Income inequality and redistribution in Lithuania: The role of policy, labor market, income, and demographics,
Nerijus Černiauskas, Denisa Sologon, Cathal O'Donoghue and Linas Tarasonis,
from GRAPE Group for Research in Applied Economics
(2021)
Keywords: income inequality, redistribution, decompositions, microsimulation, tax-benefit policies.
Housing Boom and Headline Inflation: Insights from Machine Learning,
Yang Liu, Di Yang and Yunhui Zhao,
from International Monetary Fund
(2022)
Keywords: Housing Price Inflation; Rent; Owner-Occupied Housing; Machine Learning; Forecast; machine-learning model; machine learning method; housing boom; D. forecasting result; Inflation; Housing prices; Housing; Consumer price indexes; Global; Europe; Australia and New Zealand; North America; Caribbean;VAR model
Understanding and Predicting Systemic Corporate Distress: A Machine-Learning Approach,
Burcu Hacibedel and Ritong Qu,
from International Monetary Fund
(2022)
Keywords: Nonfinancial sector; Probability of default; Early warning systems; Macroprudential policy; balance-sheet weakness; appendix B constructing predictor; distress events; appendix C machine learning model; PD indices; Corporate sector; Banking crises; Credit; Financial statements; Global
Decisions and Performance Under Bounded Rationality: A Computational Benchmarking Approach,
Dainis Zegners, Uwe Sunde and Anthony Strittmatter,
from CRC TRR 190 Rationality and Competition
(2020)
Keywords: cognitively bounded rationality; benchmark computing; artificial intelligence; decision quality; decision time;
Dynamic Early Warning and Action Model,
Hannes Mueller, Christopher Rauh and Alessandro Ruggieri,
from Barcelona School of Economics
(2022)
Keywords: C44, D74, E17
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