Dirty Quart Dozen: Functional Programming Approaches for Trading & Risk Systems
Abstract
A practical exploration of functional programming paradigms applied to the real-world constraints of trading and risk system architecture. Drawing on experience across Sophis, QuantLib, and multi-asset pricing infrastructure, this paper examines how Scheme, and related functional techniques improve correctness, testability, and maintainability in high-stakes financial software.
Overview
This paper presents Practical Work — derived from applying functional programming to production trading and risk systems. The patterns are grounded in real deployments across commodity desks, credit portfolios, and multi-asset pricing engines.
Topics Covered
- Immutable data structures for market-data pipelines
- Composable pricing functions and curve construction
- Type-driven modelling of financial instruments
- Scheme 48
- Testing strategies for stochastic models
Background
The ideas emerged from more than a decade of building pricing and risk infrastructure at HVB/UniCredit , where the gap between theoretical elegance and production constraints is very real.
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