{"id":25763354,"url":"https://github.com/ajagtapdev/traider","last_synced_at":"2026-05-01T21:33:31.713Z","repository":{"id":277674229,"uuid":"933089465","full_name":"ajagtapdev/traider","owner":"ajagtapdev","description":"traider is an educational platform that provides beginner investors with mock trading simulations and instantaneous AI-powered feedback for their trades.","archived":false,"fork":false,"pushed_at":"2025-12-05T01:46:05.000Z","size":52390,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-12-08T08:34:57.354Z","etag":null,"topics":["cplusplus-20","fastapi","nextjs","nvidia-gpu"],"latest_commit_sha":null,"homepage":"https://traider-omega.vercel.app","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ajagtapdev.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-02-15T05:42:54.000Z","updated_at":"2025-12-05T01:46:08.000Z","dependencies_parsed_at":null,"dependency_job_id":"9b217edc-e136-4d37-b2b0-051249025ea5","html_url":"https://github.com/ajagtapdev/traider","commit_stats":null,"previous_names":["ajagtapdev/traider"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ajagtapdev/traider","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajagtapdev%2Ftraider","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajagtapdev%2Ftraider/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajagtapdev%2Ftraider/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajagtapdev%2Ftraider/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ajagtapdev","download_url":"https://codeload.github.com/ajagtapdev/traider/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajagtapdev%2Ftraider/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32513700,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-30T13:12:12.517Z","status":"online","status_checked_at":"2026-05-01T02:00:05.856Z","response_time":64,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cplusplus-20","fastapi","nextjs","nvidia-gpu"],"created_at":"2025-02-26T20:16:28.373Z","updated_at":"2026-05-01T21:33:31.703Z","avatar_url":"https://github.com/ajagtapdev.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📈 traider - High-Performance AI-Powered Stock Trading Simulator\n\n## 🚀 Inspiration  \nFinance isn’t a subject commonly taught thoroughly in schools, yet it plays a crucial role in everyone’s lives. Furthermore, professional trading tools are often inaccessible or too complex for beginners. We created **traider** to bridge this gap, providing a risk-free environment that combines **high-performance C++ analytics** with **AI-driven insights** to help users master the markets.\n\n---\n\n## 🎯 What It Does  \n**traider** is a next-generation educational platform that leverages a **hybrid C++/Python architecture** to deliver professional-grade trading simulations:\n\n- 🚀 **High-Performance C++ Core** – Backtesting and technical analysis executed with bare-metal speed.\n- 📊 **Real-Time Simulation** – Trade using historical \u0026 current data with millisecond-latency processing.\n- 🤖 **AI-Powered Feedback** – Instantaneous trade analysis using **Llama 70B** on **NVIDIA Cloud Compute**.\n- 📈 **Advanced Technical Indicators** – Real-time calculation of SMA, EMA, RSI, VWAP, and Bollinger Bands using our custom C++ engine.\n- 📰 **Market Sentiment Analysis** – AI synthesis of financial news to inform trading decisions.\n- 🏆 **Gamified Learning** – Compete on leaderboards and track portfolio performance metrics like Sharpe Ratio and Max Drawdown.\n\n**traider** differentiates itself by running its heavy-lifting simulation logic in **C++**, ensuring accuracy and scalability, while using Python and AI for high-level reasoning and user interaction.\n\n---\n\n## 🛠️ How We Built It  \n\n### 🔹 Core Engine (C++)\nThe heart of **traider** is a high-performance C++ extension (`traider_cpp`) exposed to Python via **Pybind11**. This layer handles all compute-intensive tasks:\n- **Backtesting Engine**: Simulates trading strategies over historical data with O(n) efficiency.\n- **Technical Indicators**: Optimized implementations of SMA, EMA, RSI, VWAP, and Bollinger Bands.\n- **Data Processing**: Fast normalization and manipulation of OHLCV (Open, High, Low, Close, Volume) market data.\n- **Portfolio Analytics**: Real-time calculation of risk metrics like Sharpe Ratio, variance, and returns.\n\n### 🔹 Backend (Python \u0026 AI)\nOur Python backend acts as the orchestration layer, integrating the C++ engine with modern AI capabilities:\n- **FastAPI** – High-performance API server bridging the frontend and the C++ core.\n- **NVIDIA Cloud Compute** – Hosting **Llama 3.3 70B** for deep semantic analysis of market news.\n- **Google Search API** – Real-time financial news scraping.\n- **Yahoo Finance API** – Source for raw historical market data.\n\n### 🔹 Frontend\n- **Next.js** – React framework for a responsive, interactive dashboard.\n- **Tailwind CSS \u0026 ShadCN** – Modern, clean UI components.\n- **Recharts** – Visualizing the high-frequency data streams from our backend.\n- **Convex \u0026 Clerk** – Real-time database and secure authentication.\n\n---\n\n## ⚡ Challenges We Faced  \n- **C++/Python Integration**: Developing a seamless interface between the C++ simulation engine and the Python backend using Pybind11.\n- **Memory Management**: Ensuring zero-copy data transfer where possible to maintain high performance.\n- **Cross-Platform Compilation**: configuring the build system (`setup.py` / `CMake`) to work reliably across different environments.\n- **AI Hallucination Control**: Fine-tuning prompts for the Llama 70B model to ensure financial advice remained grounded in data.\n- **Real-Time Data Sync**: coordinating the C++ calculation pipeline with live frontend updates.\n\n---\n\n## 🏆 Accomplishments We're Proud Of  \n### 🔹 System Architecture\n- Built a **hybrid execution environment** where C++ handles the math and Python handles the logic.\n- Achieved **significant performance gains** in backtesting speed compared to pure Python implementations.\n- Successfully integrated **NVIDIA's Llama 70B** for context-aware financial commentary.\n\n### 🔹 Product Quality\n- Designed a **professional-grade dashboard** that abstracts away the complexity of the underlying C++ engine.\n- Created a robust educational tool that offers both **quantitative rigor** and **qualitative insights**.\n\n---\n\n## 📚 What We Learned  \n- **Systems Programming**: The importance of memory safety and type strictness when building financial engines.\n- **Foreign Function Interfaces (FFI)**: How to effectively bridge high-level and low-level languages.\n- **Financial Engineering**: Deepened our knowledge of technical analysis algorithms and portfolio theory.\n- **Scalable Architecture**: Designing a system that leverages the best tools for each specific job (C++ for speed, AI for reasoning).\n\n---\n\n## Screenshots\n![image](https://github.com/user-attachments/assets/6130bbbe-776c-4c00-a901-3e43c6684e36)\n![image](https://github.com/user-attachments/assets/46d866d7-dc41-4405-83ad-c7bb2ad005b6)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajagtapdev%2Ftraider","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fajagtapdev%2Ftraider","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajagtapdev%2Ftraider/lists"}