MASS: Multi-Agent Simulation Scaling for Portfolio Construction

📜 Paper Link

🧑‍💻Usage

1. dependency installation

conda create -n your_env_name python==3.10 -y
conda activate your_env_name
pip install pdm
pdm install

2. dataset fetching The dataset is under review now. We will release our dataset once the review is finalized. After fetching dataset, change all ROOT_PATH variables to your dataset directory.

3. Compute resources configuration. We use Qwen2.5-72B-Instruct as our foundation model. You can change your foundation model url here. For SSE 50 and the default configuration, 80GiB RAM is needed. You can save memory overhead by adjusting the agent parallelism here.

4. Running MASS

python stock_disagreement/main.py