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ReCAP Minimal Implementation

The current repository is the smallest runnable code repository for ReCAP (Regime-Adaptive Continual Learning for Portfolio Management, KDD 2026), which implements the main process and core mechanism in the paper:

  • PPO base policy pretraining
  • Adaptive Regime Detection (ARD)
  • Dynamic Regime-Gate Module (RGM)
  • DOW30、NAS100、SP500、NIKKEI30、COMMODITY_ETF CRSRMDD evaluation.

Requirements

Suggest using the current finrl environment of the project, or installing it yourself:

pip install -r code/requirements.txt

Data

  • By default, the local cache under datasets/ is read first.
  • If there is no local cache, it will fall back to yfinance download.
  • You can use --data-dir to specify other cache directories.
  • After passing in --disable-local-cache, the 'read local cache first' behavior will be disabled.

Quick Start

The default command is executed within the time range of DOW30 in the paper:

python main.py --dataset DOW30

Notes

  • Due to the particularity of the application field of the paper, the current goal of this repository is to provide a minimum runnable implementation, rather than a complete replication of the experimental framework. Updates will be made in the future.
  • The current default observation feature is a 26 dimensional feature set. When vix or turbulence is unavailable, the gate and ARD will automatically revert to other market features.
  • Training steps and training processes are significantly less than the complete experimental settings in the paper, so that regression verification can be completed within a limited time.

About

The current repository is the smallest runnable code repository for ReCAP (Regime-Adaptive Continual Learning for Portfolio Management, KDD 2026))

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