► Bratis, T., Kouretas, G. P., Laopodis, N. T., & Vlamis, P. (2023). Sovereign credit and geopolitical risks during and after the EMU crisis.
International Journal of Finance & Economics.
https://doi.org/10.1002/ijfe.2852
This paper focuses on the sovereign crisis of the Euro debt crisis era, and we address the existence of the relationship of CDS and bond markets sovereign credit risk pricing for selected core and periphery EMU countries, during and after the 2009 EMU crisis. We study this relationship in conjunction to geopolitical risk as a measure of macroeconomic uncertainty. We use daily observations for several bond maturities and CDS premium with reference to the core (France and Germany) versus periphery EMU countries (Portugal, Italy, Ireland Spain, and Greece) for the period 2009 to 2014. To measure global geopolitical risk, we employ the Caldara and Iacoviello (2022) global geopolitics index (GPR). Using alternative econometric approaches, we find adequate evidence of volatility spillovers between the geopolitical risk index and sovereign risk markets mainly during the crisis period (2009–2012) and weaker during the easing of the eurozone debt crisis period (2012–2014). Moreover, based on Granger causality the estimation of the short- term dynamics reveals a significant linkage during the post-crisis period rather than during crisis. During the crisis period, we found significant dynamic responses between GPR and bond yields.
► Bratis, T., Laopodis, N. T., & Kouretas, G. P. (2023).
CDS and equity markets’ volatility linkages: Lessons from the EMU crisis.
Review of Quantitative Finance and Accounting, 60(3), 1259–1281.
https://doi.org/10.1007/s11156-023-01126-7
We investigate the means and volatility feedback loop hypotheses in terms of the informational flow among credit distress conditions, equity market expectations and investor sentiment to identify the transmission channels among sovereign CDS, equity and volatility markets. We examine core (Germany, France) and periphery (Portugal, Italy, Ireland, Spain, Greece) EMU countries for the 2009–2014 period. Our findings support the volatility feedback loop hypothesis among markets. Specifically, the major transmitters of shocks (volatility) were both the core and periphery sovereigns, while investor sentiment was the main receiver of volatility. Further, we found that, before the EMU debt crisis (2008–2009), the information flow started from the equity towards the CDS market but turned bidirectionally, post-debt crisis (2010–2014). Finally, geopolitics as a measure of macroeconomic risk, was found to respond more to sovereign risk than to bank risk in the EMU, and to the core sovereign/bank risk than to the periphery.
► Katsikas, E., Laopodis, N. T., & Spanos, K. (2023).
Dynamic stability of public debt: Evidence from the Eurozone countries.
International Journal of Financial Studies, 11(4), Article 149.
https://doi.org/10.3390/ijfs11040149
This paper investigates the dynamic stability of public debt and its solvency condition in the face of crisis periods (1980–2021) in a sample of 11 euro-area countries. The focus is on the feedback loop between the dynamic stability of public debt and interest rates, discounted by economic growth, in conjunction with budget deficits during tranquil and turbulent periods. Using the GMM panel dynamic model, the results show that dynamic stability was the case before the global financial crisis (GFC), while from GFC to the pandemic, dynamic instability prevailed and persisted in the evolution of public debt. Furthermore, panel threshold estimates show that dynamic instability of debt starts to violate the solvency condition when the borrowing cost is above 3.29%, becomes even stronger when it is above 4.39%, and exerts even more pressure when the level of debt is greater than 91%. However, the debt sustainability condition reverses course when economic growth is higher than 3.4%. The main policy implication drawn from the results is that low interest rates can create a self-reinforcing loop of high debt, which itself is a serious matter for public authorities when designing economic policies.
► Laopodis, N. T. (2023).
When do and which Fama–French factors explain industry returns?
The Journal of Portfolio Management, 49(2), 141–161.
https://doi.org/10.3905/jpm.2022.1.432
The author examines the statistical significance of the five Fama–French factors and several macroeconomic variables by decade (since the 1960s) and industry. The main findings indicate that not all factors were significant in each decade and for each industry. Also, when the Fama–French factors were present in the regressions, the macroeconomic variables often lost their significance for these industries in each decade. Finally, when constructing factors out of the macro variables, it was found that they were significant for many industries, mainly from the 1970s through the 1990s and part of the 2010s. These findings have implications for portfolio managers when selecting industries based on factor models.
► Laopodis, N. T. (2024).
Are industry returns informative about other industries and fundamentals?
Journal of Economic Analysis, Article 87.
https://doi.org/10.58567/jea04010001
This paper examines the information content of selected US industries focusing on the dynamic linkages among these industries, the stock market and a number of fundamental variables. The period of investigation spans from January 1960 to December 2021. The empirical strategy includes several methodologies such as regressions, vector autoregressions and volatility models. The idea is to investigate the dynamic linkages among these series at both the mean and the volatility levels. The results point to significant industry returns’ explanatory power for many predictors of economic activity including the stock market. Further, time-varying analysis of the linkages among the industries and the stock market’s returns reveal that certain industries such as Oil and Financials provide consistent information leadership over other industries and across decades. Further, upon assessing the industry–market return volatility spillovers, it was found that a market risk–return profile may not always be economically significant and timely for investors. Finally, crises, financial or otherwise, affect industries but to differing degrees.
► Laopodis, N., Patra, T., & Thomas, V. (2023).
Dynamic correlations of bond and equity futures and macroeconomic determinants: International evidence.
International Journal of Financial Markets and Derivatives, 9(1/2), 114–135.
https://doi.org/10.1504/IJFMD.2023.129096
This paper examines whether the dynamic co-movements between stock-bond futures markets may be driven by domestic and international macroeconomic factors. The empirical analysis also investigates whether economic uncertainty and geopolitical risks have an impact on the dynamic conditional correlations of bond and equity futures markets. The results pointed to significance of domestic inflation and industrial production, while the 3M USD Libor and 3M Euribor surfaced as determinants of the dynamic equity-bond futures correlations. Finally, the paper examines the impact of the pandemic on the dynamic correlations with the split of the sample in pre- and post-pandemic periods and it was found that neither the uncertainty nor the geopolitical risk indices emerged as statistically significant in any country.
► Salachas, E., Kouretas, G. P., & Laopodis, N. T. (2024).
The term structure of interest rates and economic activity: Evidence from the COVID‐19 pandemic.
Journal of Forecasting.
https://doi.org/10.1002/for.3060
This paper tests the accuracy and predictability of two term structure models using both yields-only and factor-augmented specifications focusing on the recent COVID-19 crisis. In addition, we test the predictive ability of the yield curve on economic activity for the United States and other advanced countries. We provide evidence that models with an enhanced information set, including COVID-19 factors, improve interest rate forecasts for this period. Also, we point out that term structure models can determine future variations in economic activity but are time- and country-sensitive. Finally, out-of-sample analysis reveals that the use of factor-augmented term structure models, to reflect the current economic and market conditions, improves their forecasting accuracy.