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Chain-structured neural architecture search for financial time series forecasting

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  • Denis Levchenko
  • Efstratios Rappos
  • Shabnam Ataee
  • Biagio Nigro
  • Stephan Robert

Abstract

We compare three popular neural architecture search strategies on chain-structured search spaces: Bayesian optimization, the hyperband method, and reinforcement learning in the context of financial time series forecasting.

Suggested Citation

  • Denis Levchenko & Efstratios Rappos & Shabnam Ataee & Biagio Nigro & Stephan Robert, 2024. "Chain-structured neural architecture search for financial time series forecasting," Papers 2403.14695, arXiv.org.
    • Handle: RePEc:arx:papers:2403.14695
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    References listed on IDEAS

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    1. Lim, Bryan & Arık, Sercan Ö. & Loeff, Nicolas & Pfister, Tomas, 2021. "Temporal Fusion Transformers for interpretable multi-horizon time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1748-1764.
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