{"repo":"simbovk/EDiffusion-QL-Multimodal-Stock-Trading","free":true,"listed":false,"github":"https://github.com/simbovk/EDiffusion-QL-Multimodal-Stock-Trading","clone":"git clone https://github.com/simbovk/EDiffusion-QL-Multimodal-Stock-Trading.git","description":"This repository provides implementation of EDiffusion-QL: a diffusion-based reinforcement learning framework for multimodal stock trading.","language":"Jupyter Notebook","stars":18,"topics":["algorithmic-trading","deep-reinforcement-learning","diffusion-models","financial-ai","portfolio-optimization","quantitative-finance","reinforcement-learning","stock-trading"],"license":null,"category":"trading","readme_excerpt":"Enhanced Diffusion Policy for Robust Multimodal Stock Trading This repository contains the implementation of my B.Sc. thesis project, presented as: Enhanced Diffusion Policy for Robust Multimodal Stock Trading through the Integration of Technical Indicators and Fundamental News Amirali Vakili, Mahan Veisi, Mahdi Shahbazi Khojasteh, Armin Salimi-Badr IEEE conference paper, IICAI 2026 The project applies an Enhanced Diffusion-QL (EDiffusion-QL) framework to automated stock trading. The model combines technical indicators , financial news embeddings , a Bi-LSTM temporal state encoder , a diffusion-based actor , and twin Q-learning critics to generate robust continuous trading actions under volatile market conditions. --- Overview Financial markets are noisy, non-stationary, and influenced by both historical price behavior and external information. Standard deep reinforcement learning methods often rely on restrictive policy distributions, which may not capture the multi-modal nature of trading decisions. This project addresses that limitation by using a diffusion-based policy for action generation. Instead of producing a single deterministic or unimodal action, the policy learns to generate diverse buy/sell allocations through an iterative denoising process. --- Key Contributions - Multimodal trading state combining technical indicators and FinBERT-based financial news embeddings. - Bi-LSTM state encoder for capturing temporal dependencies over a 20-day observation window. - Dif","default_branch":null,"files":null,"tree":[],"storefront":"/r/simbovk","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/simbovk/EDiffusion-QL-Multimodal-Stock-Trading/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}