Cross-Asset Trend Spillover: A Novel Factor for Corporate Bond Returns
Comprehensive empirical analysis examining cross-asset trend spillover factor (XTREND) and its impact on corporate bond pricing using extensive research designs.
What it examines
The paper presents a new method that uses stock market technical signals to predict corporate bond returns. Using machine learning techniques, it combines various indicators into a single forecasting model to address challenges in bond pricing and improve risk-return analysis.
What it concludes
The results show that adding stock trend information improves bond pricing and risk models. This method can help design better investment portfolios and manage risk. Future research should explore its use in different markets and further extend machine learning approaches in finance.
Evidence objects
A new study introduces the cross-asset trend factor, XTREND, integrating technical signals from equity markets into bond pricing models to significantly enhance corporate bond return predictions and mitigate pricing errors.
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Employing over 1.3 million model variations and a robust elastic net approach, the research demonstrates that a long-short XTREND strategy delivers an average monthly return of $$0.84%$$ with risk-adjusted performance.
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Surprisingly, the momentum spillover effect is notably stronger in higher-rated bonds, overturning earlier beliefs; extensive Bayesian analysis and robustness checks underscore XTRENDs superior ranking against conventional factors, bridging technical analysis.
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In this paper, \$XTREND\$ is a novel factor leveraging cross-asset spillover from equity market technical indicators to forecast bond returns. Integrating machine learning and fixed income pricing, it innovatively expands asset pricing frameworks, achieves methodological robustness and dataset testing, captivating readers with its originality, novelty, and compelling impact in finance.
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Raw abstract and provenance
- … price and volume data. Using two decades of US data, we apply machine learning … factor, suggesting its relevance for empirical bond pricing. Finally, the XTREND factor …
Source row: 473 · abstract type: snippet