Yield Curve Trading Strategies Exploiting Sentiment Data
Journal
North American Journal of Economics and Finance
ISSN
1062-9408
Type
journal article
Date Issued
2024-06-21
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. We find that 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.
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. We find that 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.
Language
English
Keywords
bond butterflies
yield curve
sentiment data
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Elsevier
Volume
74
Number
September 2024
Subject(s)
Division(s)
Contact Email Address
francesco.audrino@unisg.ch