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Found 3 papers, 3 papers with code
Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
To deal with such situations, we propose a novel time-series trend-following forecaster that can quickly adapt to new market conditions, referred to as regimes.
Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture
We introduce the Momentum Transformer, an attention-based deep-learning architecture, which outperforms benchmark time-series momentum and mean-reversion trading strategies.
Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection
Back-testing our model over the period 1995-2020, the addition of the CPD module leads to an improvement in Sharpe ratio of one-third.
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