Financial product models can feel overwhelming because of the sheer number of attributes involved. There are many product types, many market-specific conventions, and many fields that appear to describe small details. A single product may involve notionals, quantities, currencies, rates, spreads, indices, strikes, effective dates, termination dates, reset dates, fixing dates, payment dates, credit events, … Continue reading AI-Native Financial Data Foundation (7) — F-PAL: A Framework for Organising Financial Product Attributes →

A few years back, I made an attempt to define and classify financial products from a data modelling perspective. I wrote about this in one of my earlier blog posts, Buy-Side Financial Data Models (2) – Financial Instruments. At that time, I organised financial instruments using a framework based on asset classes, derivative types, and … Continue reading AI-Native Financial Data Foundation (3) – What is a Financial Product at all? →

In the previous post, I talked about why my thinking around QuantFlow has changed. The short version is that I am starting to believe that the future users of many financial data platforms may not be human quants, analysts, or engineers directly. Increasingly, the real users may be AI agents. However, there is one important … Continue reading AI-Native Financial Data Foundation (2) – FICC Canonical Data Model →