The Effects of COVID-19 Pandemic on Oil Prices, CO2 Emissions and the Stock Market: Evidence from a VAR Model

Author(s):  
Hela Mzoughi ◽  
Christian Urom ◽  
Gazi Salah Uddin ◽  
Khaled GUESMI
2021 ◽  
Vol 70 ◽  
pp. 148-158
Author(s):  
Bo Sui ◽  
Chun-Ping Chang ◽  
Chyi-Lu Jang ◽  
Qiang Gong
Keyword(s):  

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 449
Author(s):  
Chenlu Tao ◽  
Gang Diao ◽  
Baodong Cheng

China’s wood industry is vulnerable to the COVID-19 pandemic since wood raw materials and sales of products are dependent on the international market. This study seeks to explore the speed of log price recovery under different control measures, and to perhaps find a better way to respond to the pandemic. With the daily data, we utilized the time-varying parameter autoregressive (TVP-VAR) model, which can incorporate structural changes in emergencies into the model through time-varying parameters, to estimate the dynamic impact of the pandemic on log prices at different time points. We found that the impact of the pandemic on oil prices and Renminbi exchange rate is synchronized with the severity of the pandemic, and the ascending in the exchange rate would lead to an increase in log prices, while oil prices would not. Moreover, the impulse response in June converged faster than in February 2020. Thus, partial quarantine is effective. However, the pandemic’s impact on log prices is not consistent with changes of the pandemic. After the pandemic eased in June 2020, the impact of the pandemic on log prices remained increasing. This means that the COVID-19 pandemic has long-term influences on the wood industry, and the work resumption was not smooth, thus the imbalance between supply and demand should be resolved as soon as possible. Therefore, it is necessary to promote the development of the domestic wood market and realize a “dual circulation” strategy as the pandemic becomes a “new normal”.


2021 ◽  
Vol 14 (3) ◽  
pp. 122
Author(s):  
Maud Korley ◽  
Evangelos Giouvris

Frontier markets have become increasingly investible, providing diversification opportunities; however, there is very little research (with conflicting results) on the relationship between Foreign Exchange (FX) and frontier stock markets. Understanding this relationship is important for both international investor and policymakers. The Markov-switching Vector Auto Regressive (VAR) model is used to examine the relationship between FX and frontier stock markets. There are two distinct regimes in both the frontier stock market and the FX market: a low-volatility and a high-volatility regime. In contrast with emerging markets characterised by “high volatility/low return”, frontier stock markets provide high (positive) returns in the high-volatility regime. The high-volatility regime is less persistent than the low-volatility regime, contrary to conventional wisdom. The Markov Switching VAR model indicates that the relationship between the FX market and the stock market is regime-dependent. Changes in the stock market have a significant impact on the FX market during both normal (calm) and crisis (turbulent) periods. However, the reverse effect is weak or nonexistent. The stock-oriented model is the prevalent model for Sub-Saharan African (SSA) countries. Irrespective of the regime, there is no relationship between the stock market and the FX market in Cote d’Ivoire. Our results are robust in model selection and degree of comovement.


Author(s):  
Panos Priftakis ◽  
M. Ishaq Bhatti

There are several hypotheses suggesting that some properties of oil prices make it interesting to focus on the predictive ability of oil prices for stock returns. This paper reviews some models recently used in the literature and selects the most suitable one for measuring the relationships and/or linkages of oil prices to the stock markets of the selected five oil producing countries in the Middle East. In particular, the paper uses two methodologies to test for the presence of a cointegrating relationship between the two variables and an unobserved components model to find a relationship between the two variables. The results rejects convincingly that there is no linkage between the prices of oil and the stock market prices in these oil-based economies.  


2021 ◽  
Author(s):  
Fakhri Hasanov

There is no commodity whose interlinkages with the macroeconomy have been studied as extensively as oil, starting with Hamilton’s (1983) seminal study. Thousands of subsequent studies have examined the relationship between oil prices and various economic variables, including the stock market. This strand of the literature began with the pioneering work of Kling (1985). Since then, other financial markets, such as banking, have also received a fair share of analysis.


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