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

By Tobias Lausser, Joao Eduardo Vuolo, Rudi Zagst

Published 2026-06-25

Everscope rating

1318.2

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

3 / 5

About this paper

Methodology: Hybrid Econometric-ML Framework for Term Structure Forecasting. Problem types: Time Series Forecasting, Dimensionality Reduction, Portfolio Optimization, Regression, Risk Management.

arXiv:2606.26815 · Paper rankings

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