trading-momentum-transformer and slow-momentum-fast-reversion

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Stars: 603
Forks: 247
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 266
Forks: 106
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About trading-momentum-transformer

kieranjwood/trading-momentum-transformer

This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).

This project helps quantitative traders and portfolio managers develop and test systematic trading strategies, specifically for futures markets. It takes historical futures contract data and outputs optimal position sizing recommendations, aiming to improve risk-adjusted returns and adapt to changing market conditions. The primary users are quants, hedge fund managers, and institutional investors focused on systematic trading.

quantitative-trading futures-trading systematic-strategies algorithmic-trading portfolio-management

About slow-momentum-fast-reversion

kieranjwood/slow-momentum-fast-reversion

This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (https://arxiv.org/pdf/2105.13727.pdf).

This project helps quantitative traders and portfolio managers build more resilient trading strategies by combining slow momentum with fast mean-reversion. It takes historical futures contract data as input and provides improved trading signals that are better at adapting to sudden market shifts and identifying turning points. This is particularly useful for managing alternative investments like commodity trading advisors (CTAs).

quantitative-trading algorithmic-trading portfolio-management futures-trading financial-modeling

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