Yield Curve Trading Strategies Exploiting Sentiment Data
Type
conference paper
Date Issued
2022-12
Author(s)
Abstract
This paper builds upon previous research findings that show macro sentiment data-augmented models are better at predicting the yield curve. We extend the dynamic Nelson-Siegel model with macro sentiment data from either Twitter or RavenPack. Vector autogressive (VAR) models and Markov-switching VAR models are used to predict changes in the shape of the yield curve. We build bond butterfly trading strategies that exploit our yield curve shape change predictions. Although the economic returns from our trading strategies based upon models exploiting macro sentiment data do not statistically significantly differ from those which do not rely on it, we find some evidence that models exploiting inflation sentiment are economically useful when trading the curvature of the yield curve.
Language
English
Keywords
Bond butterflies
Yield curve
Sentiment data
HSG Classification
contribution to scientific community
HSG Profile Area
SEPS - Quantitative Economic Methods
Eprints ID
268398
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Name
Yield Master Paper.pdf
Size
488.63 KB
Format
Adobe PDF
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