Corporate debt announcements in the post-crisis eras

About the Project

This research project aims to extend the empirical investigation of corporate debt issuance by incorporating a longer time horizon that includes multiple macro-financial crises. While previous studies, such as Marshall, McColgan and McCann (2016) and Marshall, McCann, and McColgan (2018), focused on the period around the 2008 Global Financial Crisis (GFC), this project expands the analysis to cover the years 2001 to 2025. This extended period captures the GFC as well as subsequent economic shocks, including the BREXIT referendum and transition (2016 - 2020), the COVID-19 pandemic (2020 - 2022), the Russia-Ukraine war (2022 - ongoing), and the recent economic dislocations surrounding the so-called "Traffic War" of 2025. By examining these serial crises, the project investigates whether and how the informational content of different types of debt issuance has evolved in a U.K. market context.

Previous findings suggest that syndicated bank loan announcements play a unique role and have historically elicited a significantly positive stock market reaction in the U.K., reflecting the market’s interpretation of such loans as a credible signal of firm creditworthiness due to lender certification. In contrast, announcements of public bond and privately placed debt issuance generally produced weak or neutral price responses. However, post-GFC data from the same study revealed a diminished market reaction to syndicated loans, potentially reflecting declining credibility in bank lending standards and reputational capital.

This project revisits and expands these insights by asking whether the reduction in signalling value of bank loans persisted or reversed in response to subsequent shocks. Moreover, it evaluates whether public bonds and privately placed debt have grown in informational relevance as UK firms have increasingly diversified their financing sources amid heightened constraints in bank credit access, global liquidity stress, and geopolitical uncertainty. Breedon (2012) highlighted the U.K.’s relatively underdeveloped public bond and private placement markets. However, recent structural shifts, such as regulatory changes and evolving investor preferences, may have enhanced the perceived value of these instruments, particularly during crisis periods.

Employing regression and event study methodology on a comprehensive sample of publicly listed firms, this research will estimate debt source choices and abnormal returns surrounding announcements of debt issuance, disaggregated by instrument type (public, syndicated bank, bilateral bank, and private placement), crisis period, and firm characteristics (industry, size, crisis sensitivity). The comparative analysis across sub-periods and crisis events will enable insights into how the market’s interpretation of funding announcements varies with external macroeconomic conditions, financial sector credibility, and liquidity constraints.

This study contributes to the literature on capital structure, market signalling, and debt market segmentation. It also offers relevant policy insights into the changing dynamics of corporate finance under stress. Given the persistent macroeconomic uncertainties and structural reliance on bank finance in the U.K., a deeper understanding of the shifting informational value of debt issuance across instruments is vital for firms, investors, and financial regulators.

Applicants interested in pursuing this project are invited to submit a detailed research proposal (maximum 2,000 words) that builds on this outline. Informal inquiries can be made to Dr Seungho Lee (seungho.lee@abdn.ac.uk) or Dr Laura McCann (l.mccann@abdn.ac.uk), accompanied by a CV and cover letter outlining motivation and interest.

Essential background of student

The successful applicant is expected to have (or be close to graduating with) an MSc in Finance or in a related area, e.g., MSc in Economics, MSc in Accounting, or MSc in Data Science, with prior knowledge of prediction. Applicants should have a strong interest or experience in data preparation and in the implementation of projects. The project requires excellent skills in statistic applications or programming (Eviews, Stata, Python, or R). Comprehensive knowledge in regulations in various stock markets is desirable.

Funding

This PhD project has no funding attached and is therefore available to students (U.K./International) who are able to seek their own funding or sponsorship. Supervisors will not be able to respond to requests to source funding.