scholarly journals Climate bond, stock, gold, and oil markets: Dynamic correlations and hedging analyses during the COVID-19 outbreak

2021 ◽  
Vol 74 ◽  
pp. 102265
Author(s):  
Anupam Dutta ◽  
Elie Bouri ◽  
Md Hasib Noor
Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4354 ◽  
Author(s):  
Changyu Liu ◽  
Muhammad Abubakr Naeem ◽  
Mobeen Ur Rehman ◽  
Saqib Farid ◽  
Syed Jawad Hussain Shahzad

The research investigates the safe-haven, hedging, and diversification function of crude oil for conventional currencies, among which five are major oil exporters, and six are major oil importers. In order to model time-varying dynamic correlations between crude oil and currencies, the study uses the Asymmetric-DCC model. The findings highlight low or negative correlations, especially during the crisis period. Next, we employ a quantile based regression framework and conclude distinct safe-haven and hedge functions of oil for major currencies. We provide additional evidence on the safe-haven, hedging, and diversification function of crude oil using the cross-quantilogram framework. The findings of out of sample analysis illustrate that the hedging effectiveness of oil is greater for oil-exporting countries. In addition, the conditional diversification benefit of oil is higher in the lower quantiles, i.e., when both foreign exchange and oil markets are in a bearish state. Finally, implications for investors, portfolio managers, and policymakers are further discussed.


2009 ◽  
Author(s):  
Berlinda Liu ◽  
Srikant Dash
Keyword(s):  

2013 ◽  
Author(s):  
Hillard Huntington ◽  
Saud M. Al-Fattah ◽  
Zhuo Huang ◽  
Michael Gucwa ◽  
Ali Nouri
Keyword(s):  

2021 ◽  
Vol 9 (2) ◽  
pp. 30
Author(s):  
John Weirstrass Muteba Mwamba ◽  
Sutene Mwambetania Mwambi

This paper investigates the dynamic tail dependence risk between BRICS economies and the world energy market, in the context of the COVID-19 financial crisis of 2020, in order to determine optimal investment decisions based on risk metrics. For this purpose, we employ a combination of novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, and vine copula methods. Using a data set consisting of daily stock and world crude oil prices, we find evidence of a structure break in the volatility process, consisting of high and low persistence volatility processes, with a high persistence in the probabilities of transition between lower and higher volatility regimes, as well as the presence of leverage effects. Furthermore, our results based on the C-vine copula confirm the existence of two types of tail dependence: symmetric tail dependence between South Africa and China, South Africa and Russia, and South Africa and India, and asymmetric lower tail dependence between South Africa and Brazil, and South Africa and crude oil. For the purpose of diversification in these markets, we formulate an asset allocation problem using raw returns, MS GARCH returns, and C-vine and R-vine copula-based returns, and optimize it using a Particle Swarm optimization algorithm with a rebalancing strategy. The results demonstrate an inverse relationship between the risk contribution and asset allocation of South Africa and the crude oil market, supporting the existence of a lower tail dependence between them. This suggests that, when South African stocks are in distress, investors tend to shift their holdings in the oil market. Similar results are found between Russia and crude oil, as well as Brazil and crude oil. In the symmetric tail, South African asset allocation is found to have a well-diversified relationship with that of China, Russia, and India, suggesting that these three markets might be good investment destinations when things are not good in South Africa, and vice versa.


2017 ◽  
Vol 46 (4) ◽  
pp. 248-257 ◽  
Author(s):  
Dennis Bergmann ◽  
Declan O’Connor ◽  
Andreas Thümmel

Price and volatility transmission effects between European Union (EU) and World skimmed milk powder (SMP) prices, as well as those between both SMP series, soybeans and crude oil prices from 2004 to 2014 were analysed using a vector error correction model combined with a multivariate GARCH model. The results show significant transmission effects between EU and World SMP prices, but no significant transmission effects from soybeans or crude oil to either of the SMP prices. For policymakers and modellers, these results indicate the need to consider World SMP prices when considering EU prices. On the other hand, the finding of no transmission effects from soybean to SMP prices reduces the opportunity for a successful cross-hedging for dairy commodities using well-established soybean derivative markets.


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