Explainable Machine Learning in Credit Risk Management
N. Bussmann,
Paolo Giudici,
D. Marinelli,
Jochen Papenbrock
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7 |
2019 |
7
2019
|
Forecasting of Real GDP Growth Using Machine Learning Models: Gradient Boosting and Random Forest Approach
Jaehyun Yoon
|
7 |
2020 |
7
2020
|
Reinforcement Learning in Economics and Finance
Arthur Charpentier,
R. Élie,
Carl Remlinger
|
7 |
2020 |
7
2020
|
Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market
Bangzhu Zhu,
Shujiao Ma,
R. Xie,
Julien Chevallier,
Yi-Ming Wei
|
6 |
2017 |
6
2017
|
Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering
Sami Ben Jabeur,
N. Stef,
Pedro Carmona
|
6 |
2022 |
6
2022
|
Accuracy, Speed and Robustness of Policy Function Iteration
A. W. Richter,
Nathaniel A. Throckmorton,
Todd B. Walker
|
6 |
2013 |
6
2013
|
An Effective Computational Model for Bankruptcy Prediction Using Kernel Extreme Learning Machine Approach
Dong Zhao,
Chunyu Huang,
Yan Wei,
Fanhua Yu,
Mingjing Wang,
Huiling Chen
|
6 |
2016 |
6
2016
|
Efficient Sampling and Meta-Modeling for Computational Economic Models
I. Salle,
Murat Yıldızoğlu
|
6 |
2013 |
6
2013
|
Causality in Continuous Wavelet Transform Without Spectral Matrix Factorization: Theory and Application
O. R. Olayeni
|
6 |
2015 |
6
2015
|
Machine Learning in Economics and Finance
Periklis Gogas,
Theophilos Papadimitriou
|
6 |
2021 |
6
2021
|
Machine Learning and Sampling Scheme: An Empirical Study of Money Laundering Detection
Yan Zhang,
Peter Trubey
|
6 |
2018 |
6
2018
|
A Computational Method Based on the Moving Least-Squares Approach for Pricing Double Barrier Options in a Time-Fractional Black–Scholes Model
A. Golbabai,
O. Nikan
|
6 |
2019 |
6
2019
|
Analysis of Correlation Based Networks Representing DAX 30 Stock Price Returns
Jenna Birch,
A. Pantelous,
Kimmo Soramäki
|
6 |
2015 |
6
2015
|
