On the predictability of crude oil market: A hybrid multiscale wavelet approach

Abstract

Past research indicates that forecasting is important in understanding price dynamics across assets. We explore the potentiality of multiscale forecasting in the crude oil market by employing a wavelet multiscale analysis on returns and volatilities of Brent and West Texas Intermediate crude oil indices between January 1, 2001, and May 1, 2015. The analysis is based on a shiftinvariant discrete wavelet transform, augmented by an entropy-based methodology for determining the optimal timescale decomposition under different market regimes. The empirical results show that the five-step-ahead wavelet forecast that is based on volatilities outperforms the random walk forecast, relative to the wavelet forecast that is based on returns. Optimal wavelet causality forecasting for returns is suggested across all frequencies (i.e., daily-yearly), whereas for volatilities it is suggested only up to quarterly frequencies. These results may have important implications for market efficiency and predictability of prices on the crude oil markets. K E Y W O R D Scrude oil markets, forecasting, multiscale, wavelets | INTRODUCTIONThe past decade witnessed fundamental changes in the composition of commodity markets. In the wake of the 2008 global financial crisis (GFC) and the 2009-2010 recession period that followed, predicting the price of crude oil, arguably the most important commodity in the world today, is of considerable interest to economists, policymakers, and investors, as the business cycle of crude oil prices is heterogeneous and volatile among the commodity classes. 1 The sharp rise and decline in the price of oil since the oil price shock of 2007-2008, which by any measure could be categorized as one of largest shocks to the international price of oil on record, and its consequences have renewed the debate on understanding the fundamental behavior of future oil prices (Hamilton, 2009).Forecasting crude oil price is important to policymakers because oil is a main source of energy, and fluctuations in its prices affect government planning and policymaking decisions with respect to taxation and subsidies in traditional and renewable energy sectors, as well as in the agricultural sector. The issue of stability in oil

Infectious disease equity market volatility, geopolitical risk, speculation, and commodity returns: Comparative analysis of five epidemic outbreaks

“… Mamatzakis and Remoundos (2011) , Beckmann et al (2014) , Joëts et al (2017) , de Albuquerquemello et al, 2018 , and Chowdhury et al (2021) used the threshold vector error-correction (TVECM) model, smooth transition regression (STR) model, structural threshold vector autoregressive (TVAR) model, self exciting threshold auto-regressive (SETAR) model, and nonlinear autoregressive distributed Lag (NARDL) model, respectively, to study the nonlinear dynamics of commodity prices. With the progress of econometric technology, Uddin et al (2019) used hybrid wavelet approaches to improve the predictability of crude oil markets, and Bekiros et al (2020) applied a wavelet multiscale analysis on returns and volatilities of Brent and West Texas Intermediate crude oil indices to forecast in the crude oil market. Yahya et al (2020) found that the conditional dependencies between commodity assets are time-varying and asymmetric with the potential for tail dependence by using time-varying copulas.…”

“…Moreover, no relevant literature focuses on their time-varying and nonlinear relationship during epidemics. The relationships between commodities and financial variables are more complex and nonlinear in reality ( Bekiros et al, 2020 , Chowdhury et al, 2021 ), which require improved evaluation by nonlinear models.…”

Bubbles in Crude Oil and Commodity Energy Index: New Evidence

“…They mention several factors, which differentiate Brent from other crude oils, including its representative quality standard, the proximity of the North Sea to an important region of oil consumption, and the main refining centers of Europe and the USA, stable and favorable fiscal regulation, a solid legal regime and relatively low political risk in the United Kingdom, as well as the status of Brent crude, which has been driven by the diverse ownership of production, see [37]. Nonlinear dynamics of crude oil markets are examined by Uddin et al [38]; also, the issue of oil price stability is further discussed by Bekiros et al [39].…”

Dynamic Characteristics of Crude Oil Price Fluctuation—From the Perspective of Crude Oil Price Influence Mechanism

“…The geopolitical relationship affecting commodity supply is also an important factor of oil price fluctuation [72], and even major public health events, COVID-19 for example, can cause price fluctuations [49]. As the correlation between the crude oil market, commodity market, and financial market gradually increases [73,74], there will be uncertainty in the demand of the world crude oil market in the future under extreme risk exposures, such as the COVID-19 pandemic. The future demand of crude oil would add a huge uncertainty or "recession premium" to the prices [75].…”