This project develops a new kind of model to better understand how interest rates change
over time not just a single rate, but the full range of rates that apply over different time
horizons. This structure, often referred to as the term structure of interest rates, affects
everything from savings accounts to government policy.
Most existing models face a trade-off: they either stick closely to economic principles,
respond flexibly to real data, or remain simple to use in practice but not all three at
once. This project aims to break that limitation by building a model that meets all three
goals: it respects core financial logic, adapts to data without relying on fixed formulas, and
remains practical and efficient.
One key innovation is the use of a modern tool called path signatures, which allows the
model to learn patterns in the data in a structured and reliable way. The result will be a
flexible system that can draw on market data, internal patterns, or both to explain how
interest rates behave.
At present, no open, practical implementation exists that brings these ideas together. This
project will develop the necessary theoretical foundations and deliver a working tool for
researchers, analysts, and policymakers who need dependable models grounded in both
data and financial principles.