Chanlun Analysis Prov5.2.3

Retail and semi-professional traders use the skill to identify Chanlun buy/sell points (第一、二、三类买卖点) on individual A-share stocks and indices, combining fractal, stroke, and central hub analysis with MACD divergence to time entries and exits during multi-week swings.

Quant developers integrate the provided Python routines (chan.py/czsc) into backtesting pipelines to validate Chanlun-based strategies on historical A-share data, optimizing parameters for central hub detection and divergence confirmation across multiple timeframes.

Securities analysts and investment advisors leverage the skill to produce structured Chanlun technical reports for clients, decomposing sector rotation (e.g., semiconductor, new energy) and forecasting index movements with bilingual output for domestic and international audiences.

Trading educators and course creators use the skill as a reference to generate teaching materials, annotated chart examples, and step-by-step explanations of 缠论108课 concepts, accelerating the production of beginner-to-advanced training modules.

Developers building automated trading bots for Chinese markets embed the skill's Chanlun recognition logic to trigger real-time buy/sell orders, using multi-level joint analysis to filter signals and manage risk dynamically.

Offer a web or mobile platform where users input stock codes and receive automated Chanlun analysis reports, buy/sell point alerts, and multi-timeframe charts. Tiered subscriptions unlock advanced features like real-time divergence scanning and sector rotation dashboards.

License the Chanlun analysis engine as a RESTful API or Python SDK to hedge funds, prop trading desks, and fintech apps, allowing them to integrate signal generation directly into their own trading systems with usage-based pricing.

Provide white-label solutions to brokerages and wealth management platforms to embed Chanlun tools into their client-facing apps, alongside consulting services for custom strategy development and staff training.