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Predicting default in high yield bond markets: a comprehensive regression approach evaluating the significance of market sentiment indicators
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Resumo(s)
This thesis addresses the challenge of predicting defaults in high-yield bond markets by
integrating forward-looking market data into regression analysis. While traditional models
focus on firm-specific financial ratios, this study emphasizes the pivotal role of market
sentiment data. These indicators capture real-time market dynamics and risk perceptions,
offering a nuanced view of investor sentiment. In contrast, financial ratios, derived from
historical financial statements, lack the timeliness to predict defaults effectively. The inclusion
of market sentiment data enriches the model, providing a comprehensive and timely assessment
of default risk in high-yield bond markets.
Descrição
Palavras-chave
High-yield Default Regression Market sentiment