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News
May 18, 2026
The 'Second Shift' Is Not Why Women Avoid News
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Oil price shocks and the term structure of the US yield curve: a time–frequency analysis of spillovers and risk transmission

Annals of Operations Research. 2022.
Umar Z., Gubareva M., Teplova T., Alwahedi W.
In press

This paper investigates the influence of oil demand, oil supply, and risk-driven shocks on the yield curve in the US between 1995 and 2020. The US term-structure shape is modeled by three structural factors, the level, slope, and curvature. Their empirical analysis is performed according to the Diebold-Li modified variant of the widely used Nelson-Siegel model. The technique of wavelet analysis allows investigating the interrelation of shocks in oil prices and the US yield curve along time and frequency domains, simultaneously. We report on low, medium, and high coherence zones, relative to the oil price movements and the changes in the three yield-curve factors. The low coherence intervals indicate the potential for the three latent factors to be used for creating diversification strategies capable of hedging adverse dynamics in the oil market, potentially workable through global crises. We document the variability of dynamic patterns observable for the US sovereign yield factors on per-type-of-shock basis, evidencing the potential role of the US sovereign debt investments for designing cross-asset hedge strategies for commodity and fixed-income markets.

Research target: Economics and Management
Language: English
Full text
DOI
Keywords: causality глобальный финансовый кризиспричинно-следственные связиВейвлетыКовид-19Hedge strategiesстратегии хеджированияWavelet coherence phase-differenceYield-curve structural factorsOil-demand shocksOil-supply shocksRisk-driven shocksGlobal financial crisisDiversification attributesструктурные факторы кривой доходностишоки спроса на нефтьшоки предложения нефтишоки, связанные с рискоматрибуты диверсификацииCOVID-19
Publication based on the results of:
Study of the sentiment of financial market participants and developing risk metrics (2022)
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