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Credit default swap prediction based on generative adversarial networks
Shu Ying Lin,
Duen Ren Liu
*
, Hsien Pin Huang
*
此作品的通信作者
資訊管理研究所
研究成果
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同行評審
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引文 斯高帕斯(Scopus)
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Keyphrases
Prediction Method
100%
Generative Adversarial Networks
100%
Credit Default Swaps
100%
Prediction Model
25%
Network Applications
12%
Risk-taking Behavior
12%
Design Methodology
12%
Price Forecast
12%
Network Model
12%
Machine Learning Algorithms
12%
Feature Extraction Methods
12%
Sampling Strategy
12%
Performance Prediction
12%
Credit Risk
12%
Regression Model
12%
Application-oriented
12%
Financial Leverage
12%
Machine Learning Techniques
12%
Trading Decisions
12%
Data Sampling
12%
Selected Features
12%
Overfitting
12%
Traditional Regression
12%
Proposed Work
12%
Market Risk
12%
Stock Price Prediction
12%
Financial Applications
12%
Convolution Network
12%
Commercial Value
12%
Component Features
12%
Credit Default Swap Prices
12%
News Information
12%
Long Short-term Memory Network
12%
Credit Risk Prediction
12%
News Features
12%
Computer Science
Generative Adversarial Networks
100%
Prediction Model
40%
Experimental Result
20%
Machine Learning Algorithm
20%
Prediction Performance
20%
Sampling Data
20%
Lstm
20%
Machine Learning
20%
Learning System
20%
Feature Extraction
20%
Historical Process
20%
Economics, Econometrics and Finance
Credit Derivative
100%
Investors
22%
Machine Learning
22%
Credit
22%
Price
22%
Finance
11%
Capital Structure
11%
Prediction Market
11%