Interest Rates and Information Geometry
Dorje C. Brody, Lane P. Hughston

TL;DR
This paper explores the geometric structure of probability distributions related to interest rates, using information geometry to analyze yield curve dynamics and their representation in Hilbert space.
Contribution
It introduces a geometric framework for interest rate modeling by mapping yield curves to probability densities in Hilbert space, linking arbitrage-free dynamics with information geometry.
Findings
Yield curves can be represented as density functions in Hilbert space.
Interest rate dynamics correspond to processes in the space of smooth densities.
Derived dynamics for moments of the distribution related to yield curves.
Abstract
The space of probability distributions on a given sample space possesses natural geometric properties. For example, in the case of a smooth parametric family of probability distributions on the real line, the parameter space has a Riemannian structure induced by the embedding of the family into the Hilbert space of square-integrable functions, and is characterised by the Fisher-Rao metric. In the nonparametric case the relevant geometry is determined by the spherical distance function of Bhattacharyya. In the context of term structure modelling, we show that minus the derivative of the discount function with respect to the maturity date gives rise to a probability density. This follows as a consequence of the positivity of interest rates. Therefore, by mapping the density functions associated with a given family of term structures to Hilbert space, the resulting metrical geometry can be…
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Taxonomy
TopicsStochastic processes and financial applications · Statistical Methods and Inference · Financial Risk and Volatility Modeling
