PhD pathway in Credit and Uncertainty
PhD Supervisors in the Credit and Uncertainty pathway
Prof Rasha Alsakka; Professor Owain ap Gwilym; Dr Noemi Mantovan; Dr Ayan Orujov; Dr Valantis Vasilakis; Dr Gwion Williams.
Research theme associated with this PhD pathway
Supervisors research interests
Credit ratings and ESG ratings, credit risk and default probability, financial regulatory reforms, political economy and financial stability, corporate finance and governance, investment management including sustainable investing and climate finance, uncertainties and beliefs, structural estimation and dynamic modelling.
Outline of the pathway in Credit and Uncertainty
This research cluster focuses on economic modelling of credit and uncertainty. This group incorporates staff across the economics, banking and finance areas. The group intends to build on existing research in the School and to encourage new synergies and interdisciplinary research. Three members of the group have an established reputation in credit ratings research at Bangor over a period of recent years, along with an active PhD group. The cluster incorporates staff with cognate research interests in areas such as default probability, structural estimation, uncertainties and beliefs, and dynamical methods in macroeconomics.
Our analysis apply various empirical and theoretical frameworks. The econometric analysis in our research projects benefit from a quasi-experimental research design such as the difference-in-differences (DD) estimation, and the bias-corrected matching estimator of the Average Effect of the Treatment on the Treated (ATT). Variety of fixed effects and limited dependent variables models as well as event studies have been applied. Moreover, our research aims to develop innovative theoretical models of political economy, credit risk and financial matters, that can be tested using econometric analysis and simulations as well as calibration.
The Credit and Uncertainty also includes forLAB. forLAB is the Forecasting Laboratory, a lab dedicated to Forecasting Analytics to support operational and strategic decision making. Aspiring primarily to inform academics, practitioners and policy makers, we aim to advance the process of:
a) preparing an accurate set of forecasts
b) communicating the uncertainty around these forecasts
c) efficiently employing (a) and (b) to make informed operational and strategic decisions in finance and management.
We are currently seeking PhD candidates in the following areas:
- Credit risk, credit rating and debt pricing
- The impact of Covid-19 on economies and financial markets
- European Banking Union
- Financial regulatory reforms
- Political economy and financial stability
- Corporate finance and governance
- Structural estimation and dynamic modelling
- Probabilities, uncertainties and beliefs
- Machine learning and intelligent methods
Our current and recently completed PhD candidates focus(ed) on:
- Credit ratings in the insurance sector
- Political economy and financial instability.
- The impact of the transactional website adoption on banks’ performance
- Credit rating divergence and the role of opacity in emerging market banks.
- The impact of split credit ratings on U.S. corporates: Cost of capital, capital structure and debt maturity.
- The credit rating industry under new regulatory regimes: The case of financial institutions.
- Credit ratings and stock market.
- The impact of recent regulatory reforms of the rating industry.
- Sovereign credit ratings and financial market volatility: Bi-directional relationships and heterogeneous impact.
- Split sovereign credit ratings: The causes and implications for the financial markets.
- Forecastability of exchange rates using Intelligent methods
Please contact us if you have any enquiries related to this PhD pathway.