Oxford team revives simple math to outsmart deep learning in market forecasting
A new Oxford study introduces OFTER, an online forecasting pipeline that combines ARIMA models, PCA-based dimensionality reduction, k-nearest neighbors and ...
A new Oxford study introduces OFTER, an online forecasting pipeline that combines ARIMA models, PCA-based dimensionality reduction, k-nearest neighbors and ...
A new study shows how data leakage and flawed backtesting protocols can manufacture apparently strong machine learning predictions in financial ...
A change-point analysis of the Altman Z″-score reveals that Telefónica del Perú's slide into insolvency unfolded across six distinct regimes, ...
A new hybrid quantum-classical operator splitting method solves nonlinear parabolic PDEs up to 100 dimensions with provably faster convergence, promising ...
Researchers in India have built a reinforcement learning trading agent that combines generative language model sentiment analysis with proximal policy ...
Researchers have built a dual-agent deep reinforcement learning framework that classifies market strength using classic technical indicators and dynamically selects ...
A new study shows that large language models can dynamically reallocate portfolio risk across 55 U.S. equities, delivering a 46.4% ...
Researchers in India have built a reinforcement learning day-trading agent that combines CNNs, attention-based LSTMs, and explainable AI to outperform ...
Researchers in Tehran have developed Confidence-MPT, a hybrid framework that embeds LSTM neural network forecasts and a measure of predictive ...
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© 2025 Scienmag - Science Magazine