FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
Annuaire de skills
Découvrez des skills réutilisables pour les AI agents.
Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.
Résultats de recherche: investment
Annuaire en anglaisQlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Create a structured post-earnings equity research update with key metrics, estimate changes, charts, and thesis review.
Complete and link income statement, balance sheet, and cash flow statement model templates with formulas and checks.
[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
A traceable AI agent skill that provides original public views and investment methods of fund manager Zheng Xi with real fund data for research.
Stock Indicators for .NET is a C# NuGet package that transforms raw equity, commodity, forex, or cryptocurrency financial market price quotes into technical indicators and trading insights. You'll need this essential data in the investment tools that you're building for algorithmic trading, technical analysis, machine learning, or visual charting.
Finnhub Python API Client. Finnhub API provides institutional-grade financial data to investors, fintech startups and investment firms. We support real-time stock price, global fundamentals, global ETFs holdings and alternative data. https://finnhub.io/docs/api
Prepare a pre-earnings briefing with consensus estimates, beat-miss history, and current market context.
Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
Analyze a ticker with AlphaGBMs five-pillar framework: fundamentals, technicals, sentiment, flows, and valuation.
Research in investment finance with Python Notebooks