On the volatility of WTI crude oil prices: A time-varying approach with stochastic volatility

This study investigates the impacts of crude oil-market-specific fundamental factors and financial indicators on the realized volatility of West Texas Intermediate (WTI) crude oil price. A time-varying parameter vector autoregression model with stochastic volatility (TVP-VAR-SV) is applied to weekly data series spanning January 2008 to October 2021. It is found that the WTI oil price volatility responds positively to a shock in oil production, oil inventories, the US dollar index, and VIX but negatively to a shock in the US economic activity. The response to the EPU index was initially positive and then turned slightly negative before fading away. The VIX index has the most significant effect. Furthermore, the time-varying nature of the response of the WTI realized oil price volatility is evident. Extreme effects materialize during economic recessions and crises, especially during the COVID-19 pandemic. The findings can improve our understanding of the time-varying nature and determinants of WTI oil price volatility. © 2022

Do oil, gold and metallic price volatilities prove gold as a safe haven during COVID-19 pandemic? Novel evidence from COVID-19 data.

The spreading COVID-19 outbreak has wreaked havoc on the world's financial system that raises an urgent need for the re-evaluation of the gold as safe haven for their money because of the unprecedented challenges faced by markets during this period. Therefore, the current study investigates whether different asset class volatility indices affect desirability of gold as a safe-haven commodity during COVID-19 pandemic. Long run and the short run relationship of gold prices with gold price volatility, oil price volatility, silver price volatility and COVID-19 (measured by the number of deaths due to COVID) has been analyzed in the current study by applying ARDL Bound testing cointegration and non linear ARDL approach on daily time series data ranging from January 2020 to Dec 2021. Findings of the study suggest that in the long run, oil price volatility and gold price volatility positively affect the gold prices, whereas the effect of silver price volatility on gold prices is negative in the long run. However in the short run, all the three indices negatively impact the gold prices. In contrast, the impact of COVID-19 is positive both in the short run and in the long run that proves the validity of gold as safe haven asset in the time of the deadly pandemic. The findings of this study have significant implications and offer investors with some indications to hedge their investments by considering the gold's ability of safe haven during this era of pandemic.

COVID-19 and the Mystery of Lumber Price Movements

The COVID-19 pandemic led to unprecedented changes in the U.S. price of softwood lumber by more than 300% between 2020 and 2022. The increased volatility of lumber prices after the COVID-19 outbreak remains unexplained. In this paper, we examine how a calibrated random walk can induce similar price volatility through the development of a stochastic process. As a preferred approach, we employ an event model to estimate the impact of COVID-19 and other key events on the price of softwood lumber. The econometric model serves to provide evidence that the price volatility of softwood lumber is not completely random, and we can instead attribute part of the variation to recent regional and global events. We found that, while COVID-19 did result in a price jump, it was smaller than a rainfall event that restricted imports from Canada, while import duties and other trade actions had no discernible impact on U.S. lumber prices.

The impacts of oil price volatility on financial stress: Is the COVID-19 period different?

This study analyses the effects of oil price volatility on financial stress with various measures for a large panel of countries. The study places a special focus on comparing the pattern of these effects during the Great Recession period and the COVID-19 recession period. Using the local projection approach, the paper finds that oil price volatility has a positive and persistent effect on financial stress. However, the magnitude and the degree of persistency of oil price volatility impacts on financial stress are much greater for the Great Recession period than for the COVID-19 recession period. A possible explanation for this result would be that COVID-19 is better thought of as a "natural disaster” in which companies under stress were not being mismanaged. Another explanation would be that active intervention by the government through monetary and fiscal channels reduces the sensitivity of financial instability to oil price volatility during the COVID-19 period.

Corporate ESG performance as good insurance in times of crisis: lessons from US stock market during COVID-19 pandemic

Purpose: The COVID-19 outbreak and its confinement resulted in an unexpected stock market crash, hence the interest in environmental, social and governance (hereafter, ESG) policies. This paper aims to examine the association between ESG performance and stock market volatility before and after the COVID-19 pandemic. Design/methodology/approach: This paper examined 500 US companies listed in the S&P 500. The window period volatility refers to March 18, 2020, when the US President signed into law the Families First Coronavirus Response Act. Here, the Thomson Reuters database was used to collect ESG data and daily market information. Findings: The findings suggest that companies with high ESG performance have lower stock price volatility than companies with poor ESG performance. In other words, strong ESG performance reduces stock price volatility resulting from the COVID-19 shock and promotes resilience and stock price stability. Practical implications: This research contributes to current debates on emerging pandemics and unexpected risks and highlights the need to invest more in improving corporate sustainability. Originality/value: The results have substantial implications for managers and investors, as it highlights the relevance of customer and investor loyalty to the durability of ESG stocks. © 2023, Emerald Publishing Limited.

Assessing oil price volatility co-movement with stock market volatility through quantile regression approach

In times of financial crisis as well as during the COVID-19 era, gold and crude oil are the two commodities that have the most influence on global stock markets and the real economy. But research has mostly focused on the effects of these commodities' prices on their own, and the volatility of these commodities' prices as a whole hasn't gotten much attention. This research paper evaluates the impacts of crude oil prices volatility on shares marketplaces. This research examines the impact of crude oil uncertainty on the overall market returns in several economic sectors (China, Japan, the USA, France, and Germany) between 2000 and 2020 using the importance of the crude oil prices volatility index by applying a Quantile-on-Quantile regression(Q-Q), including dynamic copula with Markov-Switching. The results depict that because the effect of the OVX changes crosswise every single quantile level of stock return, it is cumbersome to ascertain the changes within the adverse impacts under varied stock market circumstances. Equally, to derive a comprehensive understanding of the correlation between crude costs volatility and stock returns, we utilize twofold quantile regression and quantile-quantile regression methods. We interpret these different features' impacts by applying the quantile regression approximates. Our experiential findings show that crude costs uncertainty has lop-sided impacts on stock returns;more so, these disproportionate performances alternate based not merely on the level of shares returns nonetheless equally crude market circumstances. More so, greater values match a robust risk decrease. Further, we observed heterogenous hedging effectiveness among the varied United States stock sectors. The findings demonstrate that growing crude prices volatility obtains an adverse impact on stock returns when the dual crude costs volatility and stock returns are minimal. Nevertheless, when shares returns are greater plus crude prices, volatility is minimal;growing crude volatility increases stock returns.

On the volatility of WTI crude oil prices: A time-varying approach with stochastic volatility

This study investigates the impacts of crude oil-market-specific fundamental factors and financial indicators on the realized volatility of West Texas Intermediate (WTI) crude oil price. A time-varying parameter vector autoregression model with stochastic volatility (TVP-VAR-SV) is applied to weekly data series spanning January 2008 to October 2021. It is found that the WTI oil price volatility responds positively to a shock in oil production, oil inventories, the US dollar index, and VIX but negatively to a shock in the US economic activity. The response to the EPU index was initially positive and then turned slightly negative before fading away. The VIX index has the most significant effect. Furthermore, the time-varying nature of the response of the WTI realized oil price volatility is evident. Extreme effects materialize during economic recessions and crises, especially during the COVID-19 pandemic. The findings can improve our understanding of the time-varying nature and determinants of WTI oil price volatility.

Explaining Post-Pandemic Lumber Price Volatility and its Welfare Effects

The COVID-19 pandemic led to an unprecedented increase in the U.S. price of softwood lumber by more than 300%. The price increase has been attributed to constraints on supply and increased demand for lumber caused by a pandemic-induced boom in domestic housing construction and, more so, home improvements. However, the volatility in lumber prices after the COVID-19 outbreak remains unexplained. In this paper, we employ a theoretical model to explain the cause of price volatility. We examine why demand and supply functions for lumber might be quite inelastic over the period from March 2020 to April 2022, despite very small shifts in demand. This implies that slight movements in interest rates or changes in the prices of substitutes, for example, can lead to large jumps in prices. Price volatility harms consumers while greatly benefitting lumber producers. Overall, as a result of the pandemic, U.S. producers gained some $5.3 billion, while U.S. consumers lost $7.3 billion per quarter. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

Role of oil price volatility, energy efficiency, and financial stability on sustainable energy production

In the COVID-19 crisis, many economies suffered from sustainable energy production. The emergence of the COVID-19 crises, extreme volatility in oil prices, limited energy efficiency in energy systems, and weak form of financial stability were the key reasons for it. However, considering these issues, a recent study aims to analyze them. ASEAN countries' energy efficiency and crude oil price volatility are examined as a solution to how financial conditions might be utilized to handle energy efficiency issues and crude oil price volatility. Extending it, the study aims to identify the influence of financial stability on crude oil price volatility and energy efficiency issues. To do this, GMM is used. According to the study's findings, environmental mitigation was determined to be important at 18%, and financial stability and carbon risk significant at 21%. Global warming concerns have been raised due to the ASEAN nations' 19.5% link between financial stability and emissions drift. A country's financial stability is necessary for implementing green economic recovery strategies, among the most widely accepted measures to reduce energy efficiency and guarantee long-term financial potential on the national scale. The study on green economic growth also provides the associated stakeholders with sensible policy consequences on this importance.

Testing the fluctuations of oil resource price volatility: A hurdle for economic recovery

The influence of oil price volatility on significant international macroeconomic indicators is examined empirically. The vector auto-regression (VAR) system is used to examine the influence of oil price volatility. According to the Granger causality test, impulse response functions, and variance decomposition, economic recovery and investment have been significantly affected by oil price volatility from 2000Q1 to 2020Q4. According to this research, business investment and oil prices have shown great power throughout the international economic meltdown. Volatility in economic activity and oil prices are expected during this crisis, according to the recent COVID-19 outbreak. Furthermore, in the international financial crisis and COVID-19 crises, oil prices and economic growth are strongly linked. We propose that the COVID-19 epidemic and the global financial problems have major effects on economic activity when oil prices fall. The COVID-19 epidemic had the greatest total connectedness between oil prices and economic activities, which suggests that the speed of information propagation between the oil market and financial initiatives was greater during the COVID-19 outbreak than during past global financial crises. There are important consequences for policymakers based on the findings of this research.

Corporate governance and stock performance: The case of COVID-19 crisis

This paper analyzes the impact of COVID-19 on firm-level stock behaviors (including stock price volatility, trading volume and stock returns). Using US data, this paper examines whether confirmed cases (and deaths) of COVID-19 or COVID-19-associated online searches affect stock behaviors. The results show that our five COVID-19 proxies are all positively associated with stock price volatility and trading volume and negatively associ-ated with stock returns. This paper further investigates the mitigating effect of corporate governance (viz., board and ownership structures) in this COVID-19 crisis. Overall, the results suggest that good corporate governance can mitigate the impact of COVID-19 on stock price volatility and trading volume but may not help to enhance stock returns. This paper also considers key policies used to tackle the COVID-19 pandemic and finds that government intervention plays an important role in stabilizing stock markets in this COVID-19 crisis. (c) 2021 Elsevier Inc. All rights reserved.

Oil tail-risk forecasts: from financial crisis to COVID-19

The coronavirus outbreak has caused unprecedented volatility in oil prices. This paper extends previous studies on oil Value-at-Risk (VaR) by providing extra insights into Expected Shortfall (ES) forecasting over the last decade, including several oil crises. We introduce a conditional volatility model combined with the Cornish-Fisher expansion for ES forecasting. In comparison to the widely used volatility models and innovation distributions, this approach is superior for predicting the ES of long positions but overestimates VaR for short positions. Overall, the volatility model addressing leverage effects with skewed t innovation produces the most accurate joint VaR and ES forecasting. Moreover, the magnitude of ES relative to VaR varies across models and time, implying that ES should be used in conjunction with VaR to inform timely risk management decisions. The results would be of interest to the regulatory authorities, energy companies, and financial institutions for oil tail-risk forecasting.

Feverish sentiment, lockdown stringency, oil volatility, and clean energy stocks during COVID-19 pandemic

Purpose - This study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020-16 August 2021. Design/methodology/approach - At the empirical stage, the Fourier-augmented vector autoregression approach has been used. Findings - According to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns;and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers. Originality/value - Among the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.

THE VOLATILITY OF BROILER MEAT PRICES IN TRADITIONAL AND MODERN MARKETS BEFORE, AT THE BEGINNING OF, AND DURING THE COVID-19 PANDEMIC IN JAMBI CITY

This study aimed to analyze the volatility of broiler meat prices before, in the beginning, and during the Covid-19 pandemic in traditional and modern markets in Jambi City and the forecast model. This study uses weekly time series data on broiler meat prices with the following periods: a) before the Covid-19 pandemic, the period March 2019 to February 2020;b) the beginning of the Covid-19 pandemic for the period March 2020 to August 2020;c) the Covid-19 pandemic period September 2020 to August 2021, sourced from the National Strategic Food Price Information Center. Data analysis was conducted using the coefficient of variation, ARIMA, ARCH, and GARCH. The price volatility of broiler meat in traditional markets is higher than in modern markets before, early, and during the Covid-19 pandemic. The highest price volatility occurred before the Covid-19 pandemic. The ARIMA model can predict the future price value of broiler meat in traditional and modern markets. The novelty of this research is the behavioral diversity and volatility of broiler meat prices before, in the beginning, and during the Covid-19 pandemic in traditional and modern markets in Jambi City. In addition, another novelty is the right forecast model to predict the future broiler meat prices in traditional and modern markets. © 2022 Science Press. All rights reserved.

Hedging commodities in times of distress: The case of COVID‐19

This study examines the relation between the COVID-19 pandemic and hedge efficiency in commodities futures markets. In particular, we first evaluate the informational content of commodity futures by investigating whether futures prices are accurate and unbiased predictors of future-spot prices, and then we identify key financial and real economy transmission channels associated with the pandemic. We use data of all contracts from all commodities traded at Brazilian futures markets from 2018 to 2020. We document market inefficiency and bias for all commodities. We also find that COVID-19 has a negative correlation with hedge efficiency, and that liquidity, economic activity, export, and agriculture's employment share are transmission channels to hedge efficiency.

Will Oil Price Volatility Cause Market Panic?

It is generally known that violent oil price volatility will cause market panic;however, the extent to which is worthy of empirical test. Firstly, this paper employs the TVP-VAR model to analyze the time-varying impacts of oil price volatility on the panic index using monthly data from January 1990 to November 2021. Then, after using the SVAR model to decompose the oil price volatility, this paper uses the PDL model to analyze the heterogeneous impacts of oil price volatility from different sources. Finally, based on the results of oil decomposition, this paper uses the TARCH model to analyze the asymmetric impacts of oil price volatility in different directions. The results show that: (1) oil price volatility can indeed cause market panic, and these impacts exhibit time-varying characteristics;(2) oil price volatility from different sources has different impacts on the panic index, and the order from high to low is oil-specific demand shocks, supply shocks, and aggregate demand shocks;and (3) oil price volatility has asymmetric impacts on the panic index, and positive shocks have greater impacts than negative.

Testing oil price volatility during Covid-19: Global economic impact.

This paper is occasioned by the current events in the crude oil markets throughout the Covid pandemic time. The study analyzes the evolving nature of crude oil cost unpredictability caused by the variations that influence the crude sector throughout the current contagion. Every day's dataset is within the first month of 2020 and December 30, 2021 were measured by applying VAR and GARCH models. The results corroborate that the current contagion has adverse effects on the crude sector, primarily in two ways. It resulted in the headwinds for demand and cut international demand for crude oil, increasing uncertainty for major advanced and developing nations. Next, it resulted in output headwinds as the pandemic caused hydrocarbons conflicts among the leading crude supplying countries. The two headwinds seem to have caused the more than necessary crude unpredictability. Moreover, it was found that the United States output, total requirements, and crude-leaning demand shocks adversely affect the supply unpredictability of the United States and the extractive sectors. The findings depict that crude price instability responded significantly to the contagion caused by crude headwinds. Specifically, the study recorded the effect of uncertainty because of these headwinds beyond financiers' concerns about crude price instability. This study indicates that spillovers do not have meaningful forecast data, igniting critical debates concerning the relevance of the spillover indicator for predicting at minimal sampling occurrence.

COVID-19 and A-share banks' stock price volatility: From the perspective of the epidemic evolution in China and the US

With a financial market dominated by indirect financing, China's banking system played a critical role in the government's response to COVID-19, which piqued our interest in the short-term impact of COVID-19 on the risk of China's banks. Examining the stock price of A-share listed banks and the number of confirmed cases in China and the US during the short time window surrounding the COVID-19 pandemic's outbreak, this study reveals that COVID-19 increased the A-share banking price volatility in both China and the US, reflecting a strong spillover effect of the US economic and financial system. Furthermore, COVID-19 in China has a smaller impact on the stock price volatility of China's state-owned banks (SOBs) than that of medium- and small-sized (M&S) banks, reflecting the higher risk resistance capability of large SOBs. Further analysis confirms that the impact primarily reflected systematic risk rather than idiosyncratic risk, as small and micro enterprises and M&S banks received more targeted financial support from the government. In contrast, large banks took on more responsibilities in the emergency financial stimulus, narrowing the idiosyncratic risk gap between the two types of banks and allowing the banking industry to better play its core role in the recovery of real economy in China. These findings will assist us in better understanding the effectiveness of financial assistance policies during the epidemic and will provide insights for future policymaking during similar crises.

Oil value-at-risk forecasts: a filtered semiparametric approach

The Covid-19 pandemic has set the stage for greater volatility in oil prices. Given this unprecedentedly volatile environment, protection against market risk has never been more important. Value-at-risk (VaR) is a popular metric to measure and control risk. However, the widely used historical simulation approach is unresponsive to upticks in stress. Therefore, the need has arisen for an alternative method that is easy to implement while still achieving forecast accuracy. We propose the generalized autoregressive conditional heteroscedasticity (GARCH) model combined with the Cornish–Fisher expansion (a semiparametric approach to address skewness and excess kurtosis as well as volatility dynamics) for the oil VaR forecast. We com-pare the performance of the proposed approach with that of historical simulation and GARCH-type models with alternative residual distributions: historical simulation, normal, skewed Student t and generalized Pareto. The study is based on the daily spot data from the Energy Information Administration for the period from December 19, 2012 to October 30, 2020 for Brent and from November 13, 2012 to October 30, 2020 for West Texas Intermediate, each with a total of 2001 observations. We find that the historical simulation approach significantly underestimates the risks for both long and short positions during the recent market turmoil, which confirms the importance of the filtering process in VaR forecasts. Moreover, the proposed approach provides the most accurate VaR forecasts, especially at high confidence levels for the long position. The analysis serves as a useful guide to energy market risk quantification for practitioners and policy makers. © Infopro Digital Limited 2022. All rights reserved.

Integrating the Role of Green Fiscal Policies With Energy Prices Volatility and Energy Efficiency: Presenting a COVID-19 Perspective

Energy and other related sectors are changing in China. This study attempted to estimate the energy product price volatility with energy efficiency during COVID-19 with the role of green fiscal policies. For this, we applied unit-root tests, ADCC-GARCH, and CO-GARCH techniques to infer the study findings. The results showed that energy price volatility was significantly connected until 2018. More so, the green fiscal policies were significantly connected between energy product price volatility and energy efficiency during COVID-19 (2019-2020). From energy products, the crude oil price volatility was significant at 16.4%, heating oil volatility was significant at 18.2%, natural oil price volatility was 9.7%, gasoline price volatility was 28.7%, and diesel price volatility was 34.1% significant with energy efficiency, due to the intervening role of green fiscal policies. The findings of this study are robust in comparison to previous studies. Multiple stakeholders can take guidelines from the findings of the recent study. As per our best understanding and knowledge, if suggested recommendations are implemented effectively, these results will help to enhance energy efficiency through green fiscal policies in the post-COVID period.