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Debt structure instability using machine learning

Journal of Financial Stability 2021 57, 100948
Applying a machine-learning algorithm to a large sample of U.S. public firms, we document that more than 30% of the firms substantially alter debt structures in a year, even when leverage ratio is stable, when short-term debt is trivial, and when little cash outlay is required for operations. The instability of debt structure reveals new costs of financial constraints: compared to high-credit-quality firms, low-credit-quality firms have to change debt structure more frequently to accommodate their financing needs, even with increased borrowing costs; low-credit-quality firms lack the opportunity available to high-credit-quality firms to reduce borrowing costs through switching debt instruments.

Does CEO Succession Planning (Disclosure) Create Shareholder Value?

Journal of Financial and Quantitative Analysis 2022 57(6), 2355-2384 open access
Average cumulative abnormal returns around proxy statements containing “in-depth” disclosures of planning for CEO succession are significantly positive indicating that succession planning is a value-added undertaking. Exploiting a quasi-natural experiment based on a 2009 SEC ruling that induced more succession planning disclosures, we find that succession planning is not value-adding for all firms. Rather, succession planning is value-enhancing for larger, more complex, and more stable firms. Importantly, CEO succession planning appears to be value reducing for smaller, simpler, and less stable firms.