An information‐based index of uncertainty and the predictability of energy prices

Abstract

Summary We develop an index of uncertainty, the COVID‐19 induced uncertainty (CIU) index, and employ it to empirically examine the vulnerability of energy prices amidst the COVID‐19 pandemic using a distributed lag model that jointly accounts for conditional heteroscedasticity, autocorrelation, persistence, and structural breaks, as well as day‐of‐the‐week effect. The nexus between energy returns and uncertainty index is analyzed, using daily price returns of eight energy sources (Brent oil, diesel, gasoline, heating oil, kerosene, natural gas, propane, and WTI oil) and four news/information‐based uncertainty proxies [CIU, EPU, Global Fear Index (GFI) and VIX]. The CIU and alternative indexes are used, respectively for the main estimation and sensitivity analysis. We show the outperformance of CIU over alternative news uncertainty proxies in the prediction of energy prices. News (aggregate) and bad news are found to negatively and significantly impact energy returns, while good news has a significantly positive impact. Imperatively, energy variables lack hedging potentials against the uncertainty occasioned by the COVID‐19 pandemic, while we find no strong evidence of asymmetry. Our results are robust to the choice of news variables, forecast horizons employed, with likely sensitivity to energy prices.

A New Index for Measuring Uncertainty Due to the COVID-19 Pandemic

“…The resulting search volume variables were subsequently combined in a principal components' analysis, to create a news-index-COVID-19-Induced Uncertainty: Stock tracker (hereafter, ciustk.news)-by generating the first principal component factor. This bears some resemblance to the index in [22], except for the inclusion of stock worded searches. The inclusion of stocks-related keywords was informed by the need to give the proposed index a stock perspective, hence its consideration as a stock tracker.…”

“…The huge literature on the impact of the pandemic notwithstanding, extant studies have largely relied on information-based indexes/indicators, such as news about the COVID-19 disease or health in general. For instance, news about COVID-19 new cases of infection and fatality was used by [4][5][6]10,15,19,20,22,23]. This is also used by [3], in the generation of the COVID-19-induced global fear index for the analysis of uncertainty due to COVID-19 (see also, [19]).…”

Energy pricing during the COVID-19 pandemic: Predictive information-based uncertainty indexes with machine learning algorithm

“…1 The pandemic caused global economic uncertainty given the rapid rate of spread and death records in most countries of the world ( Hallack & Weiss, 2020 ). Its impact on the energy sector was quite severe, especially on the global prices of oil and petroleum products ( Olubusoye et al, 2021 ). In the early days of COVID-19, when most economic activities were either partially or completely shut down, and various forms of social distancing and isolation measures were put in place, there was a high level of uncertainty that affected both economic production and energy consumption patterns ( Hallack & Weiss, 2020 ).…”

“…Fortunately, this study is not in the vacuum of this procedure. Several studies have researched the impact of COVID-19 on the commodity market, (see for instance; Salisu et al, 2020 a, and Olubusoye et al, (2021) among others) and other related areas such as misinformation (e.g., Akintande & Olubusoye (2020) , Galvão (2020) , among others). Therefore, several extant pieces of literature are detailing different methodological procedures on the subject and COVID-19 related impact on the commodity prices (see Sharif et al, 2020; Salisu et al, 2020 ; Salisu & Ogbonna, 2019 ; Yaya et al, 2017 ; among many others).…”

“…Google trends provide relevant subject-based information from web sources such as web searches. The present study, therefore, harnesses this wealth of information reservoir in Google on the COVID-19 pandemic uncertainty, and subsequently adopts Olubusoye et al, (2021) information-based index of uncertainty (the CIU); and also develops a different variant of MIU. The relevance of these Google trends features (the CIU and MIU) are synonymous with deriving market information on the choice of investment to catalyze decisions making on investment, and related ventures.…”