ARR-TC-2026-019·Technical Commentary·2026-04-24

The Fractional Riccati Equation and Tractable Pricing under Rough Heston

· rough Heston· fractional Riccati· Hawkes limit· affine structure
§ Reviewed Work
The characteristic function of rough Heston models
O. El Euch, M. Rosenbaum
arXiv:1609.02108 · Mathematical Finance 29(1), 2019
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§01

Abstract

The paper derives the characteristic function of the log-price in the rough Heston model via a limit of nearly-unstable, heavy-tailed Hawkes processes, showing that the classical Heston Riccati ODE is replaced by a fractional Riccati equation. This restores semi-analytic Fourier pricing to a non-Markovian model and, for the desk, supplies a microstructural derivation of roughness from order-flow self-excitation.

§02

Notation / Conceptual Frame

The characteristic function solves a fractional Riccati equation of order α = H + 1/2 ∈ (1/2, 1) in place of the classical Heston ODE; the rough Heston variance arises as the macroscopic limit of a Hawkes intensity whose kernel decays as a power law near criticality.

§03

Commentary

The conceptual bridge — that price-level roughness can emerge from the high-frequency self-exciting structure of trades — is the part we weight most. It links the rough-volatility literature to the Hawkes / reflexivity literature under one generator, rather than leaving them as parallel empirical coincidences.

§04

Implications for Research Methodology

Lets the desk reason about event windows with a single mental model: elevated endogeneity at the microstructure level and rough macroscopic variance are two views of one state. Near-critical order flow is therefore a prior for unstable implied dynamics.

§05

Limitations

The fractional Riccati must be solved numerically; calibration is materially heavier than classical Heston, and the Hawkes-to-rough limit is an idealization that abstracts away venue fragmentation.

§ Related Notes
This note is informational and interpretive. It does not constitute personalized investment advice. Market activity involves risk. Historical analysis and model outputs do not guarantee future results.