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Detecting biotechnology industry's earnings management using Bayesian network, principal component analysis, back propagation neural network, and decision tree
Chen, Fu-Hsiang
;
Chi, Der-Jang
;
Wang, Yi-Cheng
- In:
Economic modelling
46
(
2015
),
pp. 1-10
Persistent link: https://www.econbiz.de/10011434701
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2
Financial stability and economic performance
Creel, Jérôme
;
Hubert, Paul
;
Labondance, Fabien
- In:
Economic modelling
48
(
2015
),
pp. 25-40
Persistent link: https://www.econbiz.de/10011452339
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3
Improving forecast accuracy of financial vulnerability : PLS factor model approach
Kim, Hyeongwoo
;
Ko, Kyunghwan
- In:
Economic modelling
88
(
2020
),
pp. 341-355
Persistent link: https://www.econbiz.de/10012417239
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4
Forecasting gold futures market volatility using macroeconomic variables in the United States
Fang, Libing
;
Yu, Honghai
;
Xiao, Wen
- In:
Economic modelling
72
(
2018
),
pp. 249-259
Persistent link: https://www.econbiz.de/10012100333
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5
High-dimensional covariance forecasting based on principal component analysis of high-frequency data
Jian, Zhihong
;
Deng, Pingjun
;
Zhu, Zhican
- In:
Economic modelling
75
(
2018
),
pp. 422-431
Persistent link: https://www.econbiz.de/10012101548
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6
Ratings based inference and credit risk : detecting likely-to-fail banks with the PC-Mahalanobis Method
Pompella, Maurizio
;
Dicanio, Antonio
- In:
Economic modelling
67
(
2017
),
pp. 34-44
Persistent link: https://www.econbiz.de/10011813761
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7
Energy insecurity in Asia : a multi-dimensional analysis
Thai-Ha Le
;
Youngho, Chang
;
Taghizadeh-Hesary, Farhad
; …
- In:
Economic modelling
83
(
2019
),
pp. 84-95
Persistent link: https://www.econbiz.de/10012205541
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8
Which types of commodity price information are more useful for predicting US stock market volatility?
Liang, Chao
;
Ma, Feng
;
Li, Ziyang
;
Li, Yan
- In:
Economic modelling
93
(
2020
),
pp. 642-650
Persistent link: https://www.econbiz.de/10012430321
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