GANs and synthetic financial data: calculating VaR*

IF 1.8 3区经济学 Q2 ECONOMICS

Applied Economics Pub Date : 2024-06-18 DOI:10.1080/00036846.2024.2365456

David E. Allen, Leonard Mushunje, Shelton Peiris

引用次数: 0

Abstract

Generative Adversarial Neural nets (GANs) are a new branch of machine learning techniques. A GAN learns to generate new data from the training data set. We examine the characteristics of the fake f...

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GANs 和合成金融数据：计算 VaR*

生成对抗神经网络（GAN）是机器学习技术的一个新分支。GAN 学会从训练数据集生成新数据。我们研究了伪造数据的特征，并对其进行了分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Economics ECONOMICS-

CiteScore

3.80

自引率

4.50%

发文量

525

期刊介绍： Applied Economics is a peer-reviewed journal encouraging the application of economic analysis to specific problems in both the public and private sectors. It particularly fosters quantitative studies, the results of which are of use in the practical field, and thus helps to bring economic theory nearer to reality. Contributions which make use of the methods of mathematics, statistics and operations research will be welcomed, provided the conclusions are factual and properly explained.