Quant Model
Financial Market Analysis — April 2026
Comprehensive macroeconomic and equity analysis report generated through an AI-assisted research pipeline. Combines live market data, technical signals, and economic indicators into a structured analytical document.
Methods
Python, OpenBB Platform, yfinance, Kimi K2.5, HTML Report
Impact
Demonstrates end-to-end research automation—ingesting market data, computing signals, and synthesizing insights through an AI-augmented workflow.
A structured market research report generated through an automated analytical pipeline. The system pulls financial data via OpenBB Platform, computes technical and fundamental signals, and synthesizes findings into a readable analytical document.
Report Contents
- Market Overview — Broad indices, sector performance, volatility metrics
- Fixed Income — Treasury yields, credit spreads, yield curve dynamics
- Equity Analysis — Key stock screening results with technical signals
- Macro Context — Economic indicators, Fed policy implications
- Position Review — Portfolio-level analysis with risk metrics
The Pipeline Architecture
- Data Ingestion — OpenBB Platform for market data, yfinance for equities
- Signal Computation — Technical indicators (RSI, MACD, Bollinger), fundamental ratios
- AI Synthesis — Kimi K2.5 via Opencode Go API for narrative generation
- Structured Output — HTML report with embedded data tables and charts
- Obsidian Integration — Automatic export to knowledge vault
Key Signals Tracked
- Trend direction and momentum
- Support/resistance levels
- Valuation metrics vs. historical norms
- Sector rotation patterns
- Volatility regime shifts
This project demonstrates the data engineering and quantitative research skills needed for systematic market analysis—not providing investment advice, but building the tools to think through market dynamics rigorously.