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E-TRENDS: Enhanced LSTM Trend Forecasting for Equities

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  • Harris Buchanan
  • Eric Benhamou

Abstract

Trend-following strategies underpin many systematic trading approaches yet struggle under nonstationary and nonlinear market regimes. We propose an LSTM-based framework to forecast next-day trend differences ($\Delta_t$) for the top 30 S\&P 500 equities, validated across market cycles (2005--2025). Key contributions include: (i) formal proof of bias-variance reduction via differencing, (ii) exhaustive empirical benchmarks against OLS, Ridge, and Lasso, (iii) portfolio simulations confirming economic gains in terms of overall PNL compared to other models like OLS, Ridge, Lasso or LightGBM Regressor

Suggested Citation

  • Harris Buchanan & Eric Benhamou, 2026. "E-TRENDS: Enhanced LSTM Trend Forecasting for Equities," Papers 2603.14453, arXiv.org.
    • Handle: RePEc:arx:papers:2603.14453
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    File URL: http://arxiv.org/pdf/2603.14453
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