Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

Abstract

This paper examines the impacts of COVID-19 on the multifractality of gold and oil prices based on upward and downward trends. We apply the Asymmetric Multifractal Detrended Fluctuation Analysis (A-MF-DFA) approach to 15-min interval intraday data. The results show strong evidence of asymmetric multifractality that increases as the fractality scale increases. Moreover, multifractality is especially higher in the downside (upside) trend for Brent oil (gold), and this excess asymmetry has been more accentuated during the COVID-19 outbreak. Before the outbreak, the gold (oil) market was more inefficient during downward (upward) trends. During the COVID-19 outbreak period, we see that the results have changed. More precisely, we find that gold (oil) is more inefficient during upward (downward) trends. Gold and oil markets have been inefficient, particularly during the outbreak. The efficiency of gold and oil markets is sensitive to scales, market trends, and to the pandemic outbreak, highlighting the investor sentiment effect.

Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis

“…The paper may have some policy implications. As long as the BET index is not influenced by COVID-19 variables, this may suggest evidence of an inefficient market, in line with Beck, Flynn and Homanen [52], Mensi, Sensoy, Vo and Kang [72]. There are required policies to increase market efficiency though longstanding and sustainable growth rather than administering short-term interest rates [73].…”

“…Hence, Cheema, Faff and Szulczyk [20], Cheema, Faff and Szulczyk [21] advised that gold and silver lost momentum in favor of liquid and stable assets such as treasuries and the Swiss franc. Mensi, et al [72] proved that gold and oil turned out to be more inefficient throughout the corona crisis related to the pre-pandemic period. Hence, investors can establish profitable approaches by exploiting market inefficiencies to acquire abnormal returns [73].…”

Predicting the European stock market during COVID-19: A machine learning approach

“…The plausible reason could be that oil prices were falling due to its own dynamics [22] . Secondly, oil and gold showed inefficient behavior during the period understudy [23] …”

Measuring the global economic impact of the coronavirus outbreak: Evidence from the main cluster countries

“…Some studies investigate firm reactions to the pandemic and its economic consequences ( Gharehgozli et al, 2020 ; Gu et al, 2020 ; Mandel and Vipin, 2020 ; Martin et al, 2020 ; Nakamura and Managi, 2020 ). Other studies deal with the impact of COVID-19 on the commodity and energy markets by investigating the effect on oil prices and their volatility (e.g., Apergis and Apergis, 2020 ; Devpura and Narayan, 2020 ; Mensi et al, 2020 ; Sharif et al, 2020 ) or by investigating the stock returns of energy firms and energy firm performance (e.g., Iyke, 2020 ; Kanda and Kivimaa, 2020 ; Vaka et al, 2020 ; Yoo and Managi, 2020 ). The third strand focuses on the impact on financial and economic systems.…”