> For the complete documentation index, see [llms.txt](https://docs.candelacharts.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.candelacharts.com/investing/macro-and-liquidity/quantitative-equity-model/features.md). # Features Quantitative Equity Model Features The Quantitative Equity Model offers a deeply customizable engine that analyzes five critical dimensions of the market, allowing you to tailor your risk exposure precisely to your investment philosophy. * **The Five-Pillar Framework**: Analyzes Market Regime (35%), Risk Metrics (25%), Valuation (20%), Sentiment (15%), and Macro (5%) to determine optimal allocation. * **Automated Crisis Detection**: Employs hard-coded thresholds for catastrophic conditions (extreme VIX, massive drawdowns, or credit spread blowouts) to instantly de-risk the portfolio. * **Portfolio Risk Scaling**: Allows you to define maximum acceptable portfolio drawdowns and target volatility, mathematically constraining your exposure. * **Visual Buy Zones**: Clearly marks persistent "Buy Zones" with lower-bound chart fills (0-40% equity) and background highlights, representing periods of maximum fear and generational buying opportunities. * **Comprehensive Dashboard**: An on-chart UI that displays real-time status for all five pillars, risk targets, and crisis monitors. * **Highly Customizable Engine**: Full control over pillar weighting, crisis thresholds, baseline aggressiveness (Risk-Averse, Balanced, Risk-Seeking, Adaptive), and underlying calculation symbols. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.candelacharts.com/investing/macro-and-liquidity/quantitative-equity-model/features.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.