scholarly journals Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula

2021 ◽  
Vol 9 (2) ◽  
pp. 30
Author(s):  
John Weirstrass Muteba Mwamba ◽  
Sutene Mwambetania Mwambi
Keyword(s):  
South Africa ◽  
Crude Oil ◽  
South African ◽  
Asset Allocation ◽  
Markov Switching ◽  
Tail Dependence ◽  
Lower Tail ◽  
Oil Market ◽  
Oil Markets ◽  
Vine Copula

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.

scholarly journals Assessing Market Risk in BRICS and Oil Markets: An application of Markov Switching and Vine Copula

2021 ◽  
Author(s):  
John Weirstrass Muteba Mwamba ◽  
Sutene M Mwambi
Keyword(s):  
South Africa ◽  
South African ◽  
Asset Allocation ◽  
Inverse Relationship ◽  
Markov Switching ◽  
Tail Dependence ◽  
Particle Swarm Algorithm ◽  
Lower Tail ◽  
Oil Market ◽  
Vine Copula

This paper investigates the dynamic tail dependence risk between BRICS economies and world energy market in the context of the COVID-19 financial crisis of 2020, to determine optimal investment decisions based on risk metrics. For this purpose, the study employs a combination of novel statistical techniques ranging from Markov Switching, GARCH and Vine copula. Using a dataset consisting of daily stock and world crude oil prices; we find high probability of transition between lower and higher volatility regimes. 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 lower tail dependence between South Africa and India; South Africa and Brazil; South Africa and Oil. For the purpose of diversification in these markets, we formulate an asset allocation problem using C-vine copula-based returns and optimize it using Particle Swarm algorithm with a rebalancing strategy. The results show an inverse relationship between the risk contribution and asset allocation of South Africa and oil market supporting the existence of lower tail dependence between them. This suggests that when South African stocks are in distress, investors tend to shift their holdings in oil market. Similar results are found between China and oil. In the upper tail, South African asset allocation is found to have an inverse relationship with that of Brazil, Russia and India suggesting that these three markets might be good investment destinations when things are not good in South Africa and vice-versa.

Return and volatility spillovers between oil and stock markets in South Africa and Nigeria

2017 ◽  
Vol 8 (4) ◽  
pp. 484-497 ◽  
Author(s):  
Babajide Fowowe
Keyword(s):  
South Africa ◽  
South African ◽  
Stock Markets ◽  
Market Returns ◽  
Content Type ◽  
Volatility Spillovers ◽  
Oil Market ◽  
Oil Markets ◽  
Increasing Trend ◽  
Sub Saharan

Purpose The purpose of this paper is to empirically examine return and volatility spillovers between oil and the stock markets of Nigeria and South Africa. Design/methodology/approach The authors make use of an innovative new methodology of capturing spillovers, which is different from what many existing studies use. The authors employ the measures of return spillovers and volatility spillovers of Diebold and Yilmaz (2009, 2012), referred to as spillover indexes. The spillover index facilitates an assessment of the net contribution of one market in the information transmission mechanism of another market. Findings The empirical results show bi-directional, but weak interdependence between the South African and Nigerian stock markets returns and oil market returns. The results for volatility spillovers show independence of volatilities between Nigeria stock markets and oil markets, while weak bi-directional spillovers were found between South African equity volatilities and oil volatilities. The time-varying total spillover plots for returns and volatilities are broadly similar and show a trend that has been observed in other studies: an increasing trend during the non-crisis period, a burst in the crisis year, a maintained higher level of transmission afterwards. Originality/value Existing studies examining spillovers between oil and stock markets have largely ignored Sub-Saharan African markets. A common feature of existing studies is that they have been conducted for two groups of countries: either European and US markets; or Gulf Cooperation Council markets Thus, this study fills this gap in the literature by examining return and volatility spillovers between oil and the stock markets of Nigeria and South Africa.

Multivariate Markov-switching score-driven models: an application to the global crude oil market

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Szabolcs Blazsek ◽  
Alvaro Escribano ◽  
Adrian Licht
Keyword(s):  
Crude Oil ◽  
Moving Average ◽  
Local Level ◽  
Markov Switching ◽  
Impulse Response Functions ◽  
Common Trends ◽  
Vector Autoregressive ◽  
Oil Market ◽  
Long Run ◽  
Special Cases

Abstract A new class of multivariate nonlinear quasi-vector autoregressive (QVAR) models is introduced. It is a Markov switching score-driven model with stochastic seasonality for the multivariate t-distribution (MS-Seasonal-t-QVAR). As an extension, we allow for the possibility of having common-trends and nonlinear co-integration. Score-driven nonlinear updates of local level and seasonality are used, which are robust to outliers within each regime. We show that VAR integrated moving average (VARIMA) type filters are special cases of QVAR filters. Using exclusion, sign, and elasticity identification restrictions in MS-Seasonal-t-QVAR with common-trends, we provide short-run and long-run impulse response functions for the global crude oil market.

scholarly journals A comparison of retirement saving using discretionary investment and Regulation 28

2018 ◽  
Vol 21 (1) ◽  
Author(s):  
Gizelle D. Willows ◽  
Thomas Burgers ◽  
Darron West
Keyword(s):  
South Africa ◽  
South African ◽  
Asset Allocation ◽  
Pension Funds ◽  
Investment Risk ◽  
Retirement Savings ◽  
Primary Reason ◽  
Risk And Return ◽  
Retirement Saving ◽  
Retirement Fund

Background: There is growing uncertainty in global society with regard to how retirement savings should be approached. The primary reason for this is that most societies do not save enough and their citizens run out of money during retirement. Aim: This study investigates whether the limitations imposed by Regulation 28 of the Pension Funds Act of South Africa encourage optimal asset allocation and reduce investment risk for retirement savings when contrasted with discretionary investment. Setting: The study looks at hypothetical individuals who are subject to tax and retirement consequences as administered by South African legislation. Methods: A quantitative risk and return analysis was performed while considering two hypothetical investors who are identical in all aspects other than their choice of investments. Results: The findings indicate that Regulation 28 is effective in reducing the investment risk of retirement savings; however, it may also force the investor to sacrifice wealth. Conclusion: Depending on the tax bracket in which the investor sits, discretionary investment may be preferential to investing in a retirement fund under the mandate of Regulation 28.

scholarly journals Detection of structural regimes and analyzing the impact of crude oil market on Canadian stock market: Markov regime-switching approach

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammadreza Mahmoudi ◽  
Hana Ghaneei
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Return ◽  
Stock Exchange ◽  
Markov Switching ◽  
Stock Index ◽  
Var Model ◽  
Content Type ◽  
Oil Market ◽  
The Impact

Purpose This study aims to analyze the impact of the crude oil market on the Toronto Stock Exchange Index (TSX). Design/methodology/approach The focus is on detecting nonlinear relationship based on monthly data from 1970 to 2021 using Markov-switching vector auto regression (VAR) model. Findings The results indicate that TSX return contains two regimes: positive return (Regime 1), when growth rate of stock index is positive; and negative return (Regime 2), when growth rate of stock index is negative. Moreover, Regime 1 is more volatile than Regime 2. The findings also show the crude oil market has a negative effect on the stock market in Regime 1, while it has a positive effect on the stock market in Regime 2. In addition, the authors can see this effect in Regime 1 more significantly in comparison to Regime 2. Furthermore, two-period lag of oil price decreases stock return in Regime 1, while it increases stock return in Regime 2. Originality/value This study aims to address the effect of oil market fluctuation on TSX index using Markov-switching approach and capture the nonlinearities between them. To the best of the author’s knowledge, this is the first study to assess the effect of the oil market on TSX in different regimes using Markov-switching VAR model. Because Canada is the sixth-largest producer and exporter of oil in the world as well as the TSX as the Canada’s main stock exchange is the tenth-largest stock exchange in the world by market capitalization, this paper’s framework to analyze a nonlinear relationship between oil market and the stock market of Canada helps stock market players like policymakers, institutional investors and private investors to get a better understanding of the real world.

Crude oil price movements and their impact on South Africa

2006 ◽  
Vol 17 (4) ◽  
pp. 25-32 ◽  
Author(s):  
JC Nkomo
Keyword(s):  
South Africa ◽  
Crude Oil ◽  
South African ◽  
Oil Price ◽  
Supply Management ◽  
Crude Oil Price ◽  
The South ◽  
Starting Point ◽  
Price Movements ◽  
Oil Pricing

The purpose of this paper is to examine crude oil price movements and their impact on South Africa. A useful starting point is understanding the factors that have played a prominent role in influencing oil pricing. For this reason, I begin by focusing on OPEC producing countries and the challenges these countries face with supply management. After considering domestic oil pricing and accounting for fluctuations in crude oil price movements, I examine the domestic impact of oil price changes on the South African economy.

scholarly journals Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4147
Author(s):  
Krzysztof Echaust ◽  
Małgorzata Just
Keyword(s):  
At Risk ◽  
Crude Oil ◽  
Value At Risk ◽  
Tail Dependence ◽  
Oil Price ◽  
Health Crisis ◽  
Oil Market ◽  
Volatility Index ◽  
Conditional Copula ◽  
The Impact

This study investigates the dependence between extreme returns of West Texas Intermediate (WTI) crude oil prices and the Crude Oil Volatility Index (OVX) changes as well as the predictive power of OVX to generate accurate Value at Risk (VaR) forecasts for crude oil. We focus on the COVID-19 pandemic period as the most violate in the history of the oil market. The static and dynamic conditional copula methodology is used to measure the tail dependence coefficient (TDC) between the variables. We found a strong relationship in the tail dependence between negative returns on crude oil and OVX changes and the tail independence for positive returns. The time-varying copula discloses the strongest tail dependence of negative oil price shocks and the index changes during the COVID-19 health crisis. The findings indicate the ability of the OVX index to be a fear gauge with respect to the oil market. However, we cannot confirm the ability of OVX to improve one day-ahead forecasts of the Value at Risk. The impact of investors’ expectations embedded in OVX on VaR forecasts seems to be negligible.

scholarly journals Measuring the impact of COVID-19 surveillance variables over the international oil market

2022 ◽  
Vol 9 (1) ◽  
pp. 27-33
Author(s):  
Alshdadi et al. ◽  
Keyword(s):  
Saudi Arabia ◽  
Crude Oil ◽  
Global Economy ◽  
Oil Prices ◽  
Oil Reserves ◽  
Oil Market ◽  
Crude Oil Prices ◽  
Oil Markets ◽  
Long Term Impact ◽  
The Impact

Coronavirus (COVID-19) has turned to be an alarm for the whole world both in terms of health and economics. It is striking the global economy and increasing the unpredictability of the financial market in several ways. Significantly, the pandemic spread stimulated the social distancing which led to the lockdown of the countries’ businesses, financial markets, and daily life events. International oil markets have accommodated the crude oil prices during the early COVID-19 period. However, after the first 50 days, Saudi Arabia has surged the market with oil, which caused a certain decrease in crude oil prices, internationally. Saudi Arabia is one of the biggest oil reserves in the world. International trade is based on oil reservoirs which in turn, have been significantly dislodged by the pandemic. Therefore, it is crucial to study the impact of COVID-19 on the international oil market. The purpose of this study is to investigate the short-term and long-term impact of COVID-19 on the international oil market. The daily crude oil price data is used to analyze the impact of daily price fluctuation over COVID-19 surveillance variables. The correlation between surveillance variables and international crude oil prices is calculated and analyzed. Consequently, the project will help in stabilizing the expected world economic crises and particularly will provide the implications for the policymakers in the oil market.

scholarly journals Modeling Nonlinear Granger Causality and Co-Integration Between Gold Price Returns and Crude Oil Price Returns

2018 ◽  
Vol 14 (2) ◽  
pp. 105-116
Author(s):  
Nawaz Ahmad ◽  
Keyword(s):  
Crude Oil ◽  
Granger Causality ◽  
Oil Prices ◽  
Oil Market ◽  
Crude Oil Prices ◽  
Long Run ◽  
Gold Market ◽  
Oil Markets ◽  
Causality Tests ◽  
Multiplicative Effects

To model the nonlinear analysis of commodities, Gold market and crude oil market have importance to test their lead and lag price mechanism between the two. For this purpose, the log transformation has been done to calculate easier multiplicative effects. However, to record the dynamic effects of long run cointegreation model applied and tested to find the significance of the problem statement issues. Furthermore, granger causality approach also uses to examine the fundamental linkages between Gold Prices and Crude Oil prices. Meanwhile, the study of Gold markets and oil markets gained popularity among development economists during in last some decades. And try to find out stochastic relationship between the two nonlinear markets. The academic practitioners paved their efforts to run casual time series models in order to find out the robust results which help the economists and financial experts to drive the industry indicator in positive way. This study confirmed that there is cointegration between the two important indicators of large market commodities i.e Gold and crude oil and also casual interactions. Pairwise Granger Causality Tests concluded that Gold Prices return has Granger Cause on Oil Prices return in the long run and if the βeta change in the prices of gold may affect on the prices of crude oil in the long run.

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