> For the complete documentation index, see [llms.txt](https://dgpt.gitbook.io/dgpt-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://dgpt.gitbook.io/dgpt-docs/product-architecture/quantitative-income-platform.md). # Quantitative Income Platform The Quantitative Income Platform is a proprietary model of artificial intelligence for financial solution capabilities based on the DGPT model. By extending DGPT's capabilities in the financial domain, the platform is better able to handle financial data and tasks, and performs well in financial benchmarks. With a large number of financial data sources, we have built a dataset containing 363 billion labels to support all types of financial tasks. The Quantitative Income Platform is built on the DGPT platform and uses AI financial models to analyse market sentiment factors, capital flows and spread data to arbitrage between major platforms and earn spread returns. We combine state-of-the-art GPT algorithmic capabilities with the perception of macro changes in the market to maximise returns. We continuously update our optimal return algorithms in real time and perform high frequency arbitrage on different trading channels. Users can access the Quantitative Finance platform and select suitable underlying for compounding. When you inject funds on the platform, the quantitative financial model will automatically allocate your funds for investment arbitrage. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://dgpt.gitbook.io/dgpt-docs/product-architecture/quantitative-income-platform.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.