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Data-Driven Duration Management -- Term Structure Forecasting Using Machine Learning
Joao Eduardo Vuolo / Rudi Zagst / Tobias Lausser
fixed income / interest ratesResource overview

Data-Driven Duration Management -- Term Structure Forecasting Using Machine Learning

Paper2026

by Joao Eduardo Vuolo, Rudi Zagst, Tobias Lausser

Tags
fixed incomeinterest ratesmachine learningneural networksterm structure models

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Understand this paper

Suggested foundations for rates and fixed income and financial machine learning. Specialist prerequisites vary by paper.

Before you read

  1. The Bank Account, Short Rate, and the Fundamental Pricing Equation

    Understand discounting in a stochastic-rate model.

  2. DV01, Dollar Duration, and One-Factor Price Sensitivity

    Translate yield movements into first-order price risk.

  3. Time-Ordered Train, Validation and Test Design

    Preserve time order and avoid future information in training.

  4. Linear Regression

    Establish an interpretable baseline before a flexible model.

Go further

  1. Bootstrapping the Spot Curve from Market Instruments

    Build a consistent discount curve.

  2. The Vasicek Model: Mean Reversion, Affine Bond Prices, and the Gaussian Distribution

    Study a tractable mean-reverting rate model.

  3. Finance-aware validation

    Account for dependence and overlapping observations.

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