I Built an AI That Analyzes Chinese A-Share Stocks Using a Three-Pillar System — Here's What It Caught Today

Felixwang007 — Thu, 30 Jul 2026 04:10:35 +0000

Last week, I open-sourced an AI-powered stock analysis system for the Chinese A-share market. Today I want to show you what it actually does — with real data from the July 30 trading session.

The Problem

Most A-share analysis tools fall into one camp: purely technical (MACD/KDJ/RSI overlays), purely fundamental (PEG/ROE screens), or purely sentiment-based (social media buzz). None of them talk to each other. Retail investors are left stitching three separate dashboards together.

The Solution: Three-Pillar Scoring

The system (called A-Share Stock Analysis Expert) runs three independent analysis pipelines on every stock in the watchlist:

1. Technical Analysis (10 pts)

Python-native MACD, KDJ, RSI, Bollinger Bands, and moving average systems — all matching Tongdaxin (通达信) calculation standards. No external dependencies, no API keys needed.

2. Fundamental Analysis (10 pts)

DuPont ROE decomposition, PEG valuation, and Buffett-style "three ratios" screening with industry-specific weighting.

3. Intelligence Analysis (10 pts)

Majors capital flow tracking, Xueqiu sentiment, dragon-and-tiger list monitoring, institutional position changes, and policy timing.

Total score: 30 points. Only stocks scoring 12+ trigger a buy signal.

What It Flagged Today (July 30, 2026)

Today was a rough session — Shanghai Composite -1.15%, Shenzhen Component -3.79%. But the system spotted several interesting moves:

Limit Up Signal: 闰土股份 (002440) +10.00%

Technical score: 4/10 — Bullish MACD, golden cross on KDJ, touching upper Bollinger. The system flagged the bullish alignment before the breakout.

Confirmed Uptrend: 龙佰集团 (002601) +0.36%

Scored 5/10 technically — bullish MACD, bullish KDJ, neutral-bullish RSI. Not an explosive play, but steady accumulation in an otherwise red market.

Limit Down Warning: 兴业科技 (002674) -10.00%

The intelligence layer flagged "4 consecutive up days" (连涨4天) — a classic exhaustion signal. The system was already on watch for a reversal.

Pattern Recognition Samples

From the training pipeline (36 samples collected across 5 patterns):

Pattern	Example	Signal
Breakout	中国中免 +3.37%	Bullish breakout with volume — buy on confirmation
Trend	隆基绿能 +1.03%	Healthy uptrend channel — hold and add on dips
Pullback	北方华创 -1.20%	Low-volume pullback — accumulation zone

Training Pipeline

The system runs a daily cron job at 15:10 (market close +10min) to collect real-time quotes via the free Sina Finance API for 12 core A-share stocks. Each day's data is classified into one of 5 pattern types:

放量突破 (Breakout with Volume)
缩量回调 (Low-Volume Pullback)
高位放量下跌 (High-Level Volume Selloff)
趋势追踪 (Trend Following)
横盘震荡 (Sideways Consolidation)

The goal: accumulate 200+ labeled samples for QLoRA fine-tuning.

What's Next

Fine-tune a LLaMA model on the accumulated training data for better pattern recognition
Integrate the iTick API for real-time data without scraping
Add portfolio tracking with stop-loss alerts

Try It Yourself

The complete source code and tools are available:

GitHub: github.com/Felixwang007 (repo: daily-stock-analysis)
Xiaping Marketplace: Search "A-Share Stock Analysis Expert" on xiaping.coze.com for the ready-to-use skill

Whether you trade A-shares or just want to understand how AI agents can analyze financial markets, I hope this gives you a practical starting point. Pull requests and ideas welcome!

I Built a Free A-Share Stock Analysis Tool for AI Coding Agents (24 Indicators)

Felixwang007 — Mon, 27 Jul 2026 23:09:35 +0000

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