#Python quantitative trading
17 related articles
·2 min
Python Quantitative Backtesting in Practice: A Complete Guide to Building Stock Trading Strategies with Zipline
Learn how to use Python Zipline Reloaded for quantitative backtesting, covering SMA crossover, MACD strategies, YFinance data setup, leverage control, trading costs, and multi-asset portfolios.
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·3 min
Locally Deploying LLMs for Trading Bots: Hardware Selection & Model Recommendations
How to deploy LLMs locally on AMD RX 7800 XT 16GB for trading bots: ROCm ecosystem, 7B-14B model picks (Qwen2.5, Llama 3.1), Ollama/LM Studio setup, and system architecture design.
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·2 min
awesome-systematic-trading: A Complete Guide to the 9,000-Star Quantitative Trading Open Source Resource List
Deep dive into the 9,100-star awesome-systematic-trading GitHub project covering backtesting frameworks, strategy implementations, data tools, and classic books for quantitative traders.
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·3 min
GitHub Daily · July 28: From Claude Code Skill-ification to AI Agent Governance, the Toolchain Matures
GitHub Trending July 28: Microsoft's agent-governance-toolkit covers OWASP Agentic Top 10, book-to-skill gains 366 stars showing Claude Code skill ecosystem potential, plus browser-based 3D and GIS tools.
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Kronos Financial Foundation Model: Usi…
·7 min
Kronos Financial Foundation Model: Using AI to Read the Market Language of Candlesticks
Kronos is the first open-source foundation model treating candlestick data as the "language of financial markets," using an autoregressive Transformer and earning 32K GitHub Stars. A deep dive into its principles, applications, and limits.
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·2 min
TradingAgents-astock: A Practical Guide to the Multi-Agent Research Framework for A-Share Markets
TradingAgents-astock is a multi-agent A-share research framework with free domestic data sources, seven debating analyst agents, and support for DeepSeek, Qwen, and more.
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·6 min
GPT-5.6 Fully Available: A Deep Dive into the Sol/Terra/Luna Three-Tier Models and Four-Agent Parallelism
GPT-5.6 is now officially available to all users, launching the three-tier Sol, Terra, and Luna models with four-agent parallelism. An in-depth look at the official benchmarks, API pricing, safety, and Ultra mode.
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·3 min
Vibe-Trading: The Rise and Practice of Open-Source AI Trading Agents
HKUDS's open-source Vibe-Trading gained nearly 1,000 GitHub stars in a day. This deep dive covers its LLM+Tool Calling architecture, core modules, and the risks of AI-driven trading agents.
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·7 min
The C Readability Crisis: Engineering Reflections Behind Clever Tricks
Why do C programmers keep creating readability disasters? An in-depth look at macro abuse, fancy pointer tricks, and over-nesting—and how coding standards, static analysis, and code review protect maintainability.
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·3 min
Codex Powers Hedge Fund: Economic Analysis Cut from 2 Days to 30 Minutes
Balyasny Asset Management adopts OpenAI Codex and o3/4o models, cutting economic analysis from 2 days to 30 minutes with 97% daily active AI adoption.
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·4 min
5 Viable Paths to Making Money Independently with Python
5 proven paths to making money independently with Python: automation scripts, AI app development, quantitative trading, tool/course sales, and full-stack web services, with pricing references and practical tips.
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Tutorials·2 min
MCP Protocol in Practice: Building an AI Investment Analysis Agent with TradingView + Notion
A detailed guide on MCP protocol vs Skills, integrating TradingView and Notion MCPs to build an automated investment analysis Agent with market scanning, backtesting, and report generation.
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Tutorials·3 min
Connecting Claude Code to TradingView: A Practical Guide to AI-Powered Trading Analysis
Learn how to connect Claude Code to TradingView desktop via an open-source project for AI-powered chart reading, technical analysis reports, and automated PineScript coding with full setup guide.
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Tutorials·3 min
Building an On-Chain Trading Bot Management Dashboard with AI — Zero Coding Required
Learn how to use the open-source AI framework Bolt with DeepSeek LLM API to build a visual on-chain trading bot management dashboard through natural language — zero coding required.
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Tutorials·1 min
The Complete Guide to yfinance: Fetching Financial Data and Quantitative Analysis with Python
Complete guide to the yfinance library covering stock price retrieval, financial statements, options chains, batch downloads, and real-time data for Python quantitative analysis.
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Expert Opinions·2 min
In the Age of AI Coding, Is It Still Worth Learning to Program?
When AI writes code faster than most engineers, should ordinary people still learn to program? A veteran developer analyzes how coding skills become the lever for harnessing AI productivity.
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Product Reviews·3 min
Stock-MCP: An Open-Source MCP Server That Gives AI Agents Real-Time Access to Chinese and US Stock Data
Stock-MCP is an open-source MCP-based financial data server supporting China A-shares, US stocks, and crypto. Learn its core features, architecture, and use cases for building AI investment research assistants.
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