Search

This study discovered market determinants of credit default swap (CDS) spreads in the North American oil and gas industry. Due to the limited theoretical background on market sources of CDS price fluctuations, we chose to alleviate model uncertainty and possible misspecification issues using Bayesian model averaging. This robust framework allowed us to aggregate results from a vast number of linear panel models estimated over the 2017&ndash, 2020 period. We identified oil price volatility, major shifts in the OPEC+ supply policy, natural gas prices and industrial metal prices as the most robust determinants of CDS spreads. We show that following the onset of the COVID-19 pandemic, oil prices ceased to be a notably important determinant of credit risk, as factors indirectly related to oil prices, such as global and sectoral uncertainty, financial conditions and the macroeconomic stance became more influential. Additionally, we show that the CDS spreads of shale companies are determined by similar common factors, but they are more sensitive to the OPEC+ decisions on the global supply and are less affected by the domestic activity. Finally, we also prove that our modelling approach may help investors and risk officers to identify robust determinants behind the dynamics of credit risk.

Purpose – Value relevance studies, in particular international comparative studies, use market values sampled at different dates relative to the fiscal year-end. This paper aims to contribute a theoretical and empirical analysis of the relationship between value relevance and the month of market value sampling. Design/methodology/approach – The paper examines two components of value relevance, coincident relevance and forecast relevance, which the paper develops on the basis of the Ohlson model. The paper measures value relevance by estimating separate panel-data regressions for each of the 12 months around fiscal year-end. The sample consists of companies listed in two continental European countries, France and Germany, over the 1989-2008 period. Findings – In both country panels, the paper finds that overall value relevance is higher when market value is sampled before or close to fiscal year-end, but incremental value relevance varies between domestic and International Financial Reporting (IFRS) accounting standards. Regression results reveal significant variations in coefficients over the following months of market value in French panel and its IFRS sub-sample only. Research limitations/implications – The scope of the study is limited to the average value relevance parameters of companies listed on stock exchanges in France and Germany. Future research may be devoted to other countries and study additional determinants of value relevance. Practical implications – The study shows that the selection of the month of market value sampling can have significant impact on value relevance regression results. Therefore, sensitivity analysis needs to be included in research studies which rely on the value relevance approach. Originality/value – The paper contributes the first systematic analysis of the variation in value relevance parameters in response to the selection of the month in which market value is sampled.

Value relevance studies, which examine the relationship between accounting numbers and equity valuation, use market values sampled a number of months after the publication of annual financial reports. Although it stems from the researchers' belief that accounting information needs to be made available before it can be discounted in market prices, this approach disregards a substantial body of literature that proves to the contrary. Our study provides empirical evidence that directly supports the interpretation of value relevance as the ability of accounting numbers to capture value-relevant information that has already been included in market valuation. In order to describe the temporal relationship between accounting-based equity valuation and market value of equity we introduce two new concepts: coincident and forecast relevance of accounting numbers. The first represents the relevance of accounting information for market values sampled during the reporting year, while the latter represents the relevance of accounting numbers for market values sampled after fiscal year-end. We measure coincident and forecast relevance by estimating Ohlson model parameters with country panel regressions for exchange-listed companies from France and Germany. The results confirm that coincident relevance is stronger than forecast relevance in both countries. The findings contribute to the studies on value relevance by suggesting improvements to current research methods.