Revisiting sovereign credit risk in Fiji: New evidence from high-frequency contingent claims analysis

This study applies Contingent Claims Analysis (CCA), based on the Black-Scholes option pricing framework, to assess Fiji’s sovereign credit risk and generate forward-looking risk indicators. While prior studies have used this method for Fiji, this analysis extends the literature by incorporating a broader array of indicators, high-frequency data from January 2016 to December 2022, and detailed sensitivity tests. The findings reveal that the distance to distress is highly volatile, with a sharp drop to three standard deviations in 2020 during the COVID-19 crisis compared to eight in 2018. The risk-neutral default probability surged to 90 percent during the pandemic period. Despite these concerns, the asset-to-distress barrier ratio remained relatively stable over the seven-year period, and credit risk indicators generally moved in line with economic growth. The sensitivity analysis highlights that volatility in local currency liabilities has a strong effect on risk metrics. To address concerns regarding benchmarking, we explicitly compare our findings to sovereign credit ratings and similar comparable models. The study also incorporates climate contingencies in measuring the risk indicators. Several robustness exercises are employed to validate the findings. We argue that these findings support the application of CCA in sovereign risk monitoring and policymaking in small developing economies such as Fiji.