Generative adversarial networks for financial trading strategies fine-tuning and combination

DOI10.1080/14697688.2020.1790635zbMath1479.91431arXiv1901.01751OpenAlexW3081659016MaRDI QIDQ5014212

Adriano Koshiyama, Nick Firoozye, Philip Treleaven

Publication date: 1 December 2021

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1901.01751

zbMATH Keywords

trading strategiesmodel combinationbacktestinggenerative adversarial networks

Mathematics Subject Classification ID

Financial networks (including contagion, systemic risk, regulation) (91G45) Financial markets (91G15)

Related Items (3)

Distributionally robust end-to-end portfolio construction ⋮ Generative adversarial networks applied to synthetic financial scenarios generation ⋮ Sig‐Wasserstein GANs for conditional time series generation

Uses Software

• Wasserstein GAN
• AdaGAN
• QuantGAN
• CorrGAN

Cites Work

• Unnamed Item
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• Markov cross-validation for time series model evaluations
• Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance
• Computer Age Statistical Inference
• Empirical properties of asset returns: stylized facts and statistical issues
• Quant GANs: deep generation of financial time series
• The elements of statistical learning. Data mining, inference, and prediction

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