Previous studies document statistically significant evidence of crude oil return predictability by several forecasting variables. We suggest that this evidence is misleading and follows from the common use of within-month averages of daily oil prices in calculating returns used in predictive...

This paper uses monthly data from 1984:M10 to 2012:M8 to show that oil-sensitive stock price indices, particularly those in the energy sector, have strong power in predicting nominal and real crude oil prices at short horizons (one-month-ahead predictions), using both in- and out-of-sample...

This paper investigates whether augmenting models with the variance risk premium (VRP) and Google search data improves the quality of the forecasts for real oil prices. We considered a time sample of monthly data from 2007 to 2019 that includes several episodes of high volatility in the oil...

In this paper, we study the methods of combining different volatility forecasts using various GARCH models. Given that the major risk exposure for many investors in energy is the volatility of the electricity price, our motivation stems from the fact that there is no single best model for...

Electricity price forecasting has become an area of increasing relevance in recent years. Despite the growing interest in predictive algorithms, the challenges are difficult to overcome given the restricted access to relevant data series and the lack of accurate metrics. Multiple models have...

In this paper, we examine the relationship between volume and volatility for crude oil markets in the context of Mixture of Distribution Hypothesis (MDH). We find that there exists a positive and significant relationship between volume and volatility in case of WTI Crude oil, supporting the MDH....

A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the jump component is persistent when forecasting the oil...

The present paper presents three different short-term oil models on a weekly basis. With these models we try to forecast oil prices out-of-sample up to three months. Two of the models are based on the VAR methodology and consider fundamental factors like the net long position and oil...

The present paper presents three different short-term oil models on a weekly basis. With these models we try to forecast oil prices out-of-sample up to three months. Two of the models are based on the VAR methodology and consider fundamental factors like the net long position and oil...