Navigating Crude Oil Volatility Forecasts: Assessing the Contribution of Geopolitical Risk

We assess whether the importance of geopolitical uncertainty is also ”translated” into valuable predictive information for oil price volatility forecasts. The paper shows that geopolitical uncertainty offers superior predictive information when combined with other uncertainty indicators. More importantly, we show that the inclusion of geopolitical uncertainty in a DMA framework generates superior trading profits and risk management measures’ predictions, in comparison with benchmark models, especially in longer-run horizons.

Trading VIX on Volatility Forecasts: Another Volatility Puzzle?

We study the economic usefulness of stock market implied volatility forecasts, based on their ability to improve the short-run trading decision-making process. To do so, we evaluate whether the multiple days ahead stock market volatility forecasts vis-à-vis the 1-day ahead forecasts can improve the 1-day ahead trading profits from VIX and the S&P500 futures. Our results suggest that indeed the 1-day ahead trading profits are significantly improved when the trading decisions are based on longer term volatility forecasts.

Determinants of regional business cycle synchronization in Greece

We assess the determinants of regional business cycle synchronization in Greece vis-à-vis the national reference business cycle, using NUTSII annual data. The computation of the time-varying synchronization is based on the dynamic estimate of a conditional variance–covariance model and subsequently, a panel regression model is used to evaluate its determinants. The findings show that island regions, industrial structure, imports, savings and disposable income are the key determinants, based on the GVA business cycle synchronization vis-à-vis the national reference cycle.

What should be taken into consideration when forecasting oil implied volatility index?

In this study, we forecast the oil volatility index (OVX) by incorporating information from other implied volatility (IV) indices. Apart from the statistical evaluation, a straddle options trading strategy validates our results from an economic point of view. The IV of Dow Jones is highly significant for short- and mid-run forecasting horizons, whereas, at longer horizons, the IV of Energy Sector provides accurate forecasts but only from an economic point of view.

What matters when developing oil price volatility forecasting frameworks?

In this paper, we examine and evaluate the main factors that oil price volatility forecasters should consider before constructing their forecasting models. Such factors are related to (i) direct versus iterated forecasts, (ii) the incorporation of continuous and jump components, (iii) the importance of semi variance volatility measures, and (iv) ordinary least squares (OLS) versus time-varying parameter (TVP) estimation procedures. The results show that depending on whether end users are interested in forecasting the realized or the implied volatility, the factors influencing the accuracy of forecasts are different. In particular, for the realized volatility, direct forecasting based on TVP estimation procedure, as well as using the information obtained in the semi variance measures, is capable of producing significantly superior forecasts.

Forecasting oil price volatility using spillover effects from uncertainty indices

We consider spillovers between oil price volatility and key uncertainty indicators and we extend the applicability of the spillover index beyond economic inference, by generating forecasts of oil price volatility. The paper shows that spillovers do not contain significant predictive information, raising critical questions regarding the usefulness of the spillover index for forecasting exercises at low sampling frequency. 

GDP Revisions: Patterns around turning points, with N. Apergis.

Disaggregated inflation rates by household category, with S. Degiannakis, and G. Filis.

Fixed event surveys of macroeconomic expectations during volatile periods, with G. Kontogeorgos.