Analysing volatility spillover between the oil market and the stock market in oil-importing and oil-exporting countries: Implications on portfolio management (original) (raw)
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Oil Volatility Spillover on MENA Stock Markets: a DCC-GARCH Approach and Portfolio Analysis
European Modern Studies Journal , 2022
This study examines the effect of oil volatility on MENA stock market return. We select four oil importer countries (Egypt, Lebanon, Morocco, and Tunisia) and four oil exporter countries (Oman, EAU, Qatar, and Saudi Arabia). The time horizon of the study is from January 2014 to August 2021. We use in the first step a univariate Threshold-GARCH (1,1) by employing the calculated oil volatility as an exogenous variable in the mean and variance equation of stock returns. In the second step, we employ a multivariate DCC-GARCH to compute the dynamic conditional correlation between oil and the stock market, the optimal portfolio and Hedge effectiveness index. The results indicate that oil volatility has a weak influence on stock market returns but has a very significant effect on stock market volatility for oil-importing (negative) and exporting (positive) countries. We also discover a strong correlation between the oil market and the stock market of oil-exporting countries. In addition, investing in oil assets is more efficient in terms of minimizing portfolio risk.
Volatility spillovers and hedging: Evidence from Asian oil-importing countries
JEL classification: F65 G11 Keywords: Stock market returns Oil prices Volatility spillover Portfolio Hedge ratio A B S T R A C T In this study the volatility spillover between stock market returns (Shanghai stock exchange, Nikkei stock exchange and Bombay stock exchange) and crude oil returns in the top three Asian oil-importing countries are investigated. BEKK-GARCH, DCC-GARCH, cDCC-GARCH and GO-GARCH estimation techniques are applied using daily data from 1st January 2000 to December 27th, 2016. Further, these estimation results are used to analyze the optimal portfolio weights and hedge ratios for oil-stock portfolios. The findings reveal that shocks dependence and conditional volatility in its own market have more important role than volatility spillover. Also, the bidirectional spillover is confirmed between Nikkei stock return and oil returns. The unidirectional spillover from Indian stock returns to oil returns. There is, however, no evidence of volatility spillover in case of China. According to optimal portfolio weights and hedge ratios, the oil assets are useful instrument to minimize the portfolio risk in studied markets. The investors, however, should choose more stocks than oil assets to form an optimal portfolio. We also notice that the cDCC-GARCH model is better for risk minimization.
The Puzzle of Asymmetric Effects of Oil: New Results from International Stock Markets
efmaefm.org
Previous work has documented that oil price changes have nonlinear effects in the economy and in stock market returns. We show that the nonlinear effects are different depending on whether countries are energy dependent or not. While price soars seem to have a negative effect on the stock markets of oil energy dependent countries, they have a positive effect on the stock markets of oil exporting countries. Stock market returns are negatively affected by oil price volatility in energy dependent countries and positively in oil exporting countries. Moreover, we find bi-directional effects between oil price increases and some oil volatility measures that can be reinforced with volatility feedback. The asymmetric effects found in oil dependent and oil exporting countries seem to fit into the offset mechanism proposed in the literature where oil price shocks interact both with oil price volatility and the economy. The results are also consistent with the finding that oil exporting countries benefit economically from oil price hikes.
The importance of oil assets for portfolio optimization: The analysis of firm level stocks
JEL classification: C22 C32 G11 G12 G15 G19 This study aimed to analyze the shock transmission and volatility spillover between firm stocks and oil assets by using the BEKK-GARCH model in which a variance and covariance series are used for portfolio optimization. For this purpose, we use the daily data from 107 Pakistani-listed firms covering the period from January 2000 to August 2017. Our overall results confirm the interdependence between firm stocks and oil assets. Additionally, there is strong evidence of volatility spillover from stocks to oil and from oil to stocks. The results from the portfolio optimization show the importance of oil assets in the formation of an optimal portfolio. Moreover, we find that in the case of manufacturing firm stocks, the investors should spend N50% of their total investment to purchase oil assets, while the remaining investment should be used to acquire firm stocks. On the other hand, in the case of investments in oil and gas firm stocks, it is evident that investors can form an optimal portfolio by spending a larger proportion of their investments on firm stocks rather than on oil assets. This research implication can be valuable for portfolio managers and individual investors who are willing to invest in Pakistani stocks.
Analyzing and forecasting volatility spillovers, asymmetries and hedging in major oil markets
Energy Economics, 2010
Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover and asymmetric effects across and within the four markets, using three multivariate GARCH models, namely the constant conditional correlation (CCC), vector ARMA-GARCH (VARMA-GARCH) and vector ARMA-asymmetric GARCH (VARMA-AGARCH) models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecast conditional correlations between pairs of crude oil returns have both positive and negative trends. Moreover, the optimal hedge ratios and optimal portfolio weights of crude oil across different assets and market portfolios are evaluated in order to provide important policy implications for risk management in crude oil markets.
The Impact of Change in Oil Prices on the Equity Markets of Oil Exporting and Importing Countries
Business & IT, 2018
This research work examines the level of the integration of equity markets of both oil importer and exporter countries based on impact of change in oil price attained by using the daily stock index data and oil price. The sample comprised of three oil importer countries Pakistan, India and Bangladesh along with three oil exporter countries Saudi Arab, Oman and UAE. For the purpose of analysis, the econometric technique mean and volatility spillover (ARMA 1, 1 and GARCH in Mean) is used. This investigation continues in two steps. First, is the impact of the economic shock in the prices of oil on returns of equity markets of both oil importer and exporter countries is studied and in the next step the impact of the same shock affecting the volatility of equity market of the sample countries is measured. The mean spillover impact from the variation in the oil price is constructive for oil importer and oil exporter countries both except for India. Volatility spillover impact is negative and significant for two oil importing countries like Pakistan, Bangladesh, and two oil exporting countries e.g. Saudi Arab and UAE but positive for Oman and India, one oil importing and one oil exporting country. The negative correlation among the variation in the oil price and equity returns of Pakistan, Bangladesh, Saudi Arab and UAE indicate the presence of portfolio divergence opportunities for foreign stockholders and portfolio executives. India, the only country for which the equity returns and their volatility are not under the influence of the change in the oil rate. Finally it is concluded that prices of oil are the cause of mean and volatility spillover in the Arab countries more significant than in subcontinent countries. The practical implication, limitations as well as directions for future research are discoursed later in this research article.
Oil price asymmetric effects: Answering the puzzle in international stock markets
Energy Economics, 2013
Although studies have found an asymmetric pattern in the response of aggregate output to oil price changes, parallel studies in stock markets have not been conclusive about their existence. This paper finds evidence that effects for oil-importing and oil-exporting countries run in opposite directions. Oil price hikes have a negative effect on the stock markets of oil-importing countries, while the impact is positive for the stock markets of oil-exporting countries. Statistical tests support the presence of asymmetric effects only in oil-importing countries. Oil price volatility has a negative impact in stock markets of oil-importing countries and positive in oil-exporting countries. Moreover, oil volatility seems to be affected asymmetrically by oil price changes. Oil price drops increase oil volatility more than oil price hikes do. Overall, the evidence seems to support that falls in oil prices do not impact stock markets because their positive effects are offset by negative effects of oil price volatility, canceling out effects for oil-importing countries.
Oil and portfolio risk diversification
2009
The growing presence of financial operators in the oil market has brought about the diffusion of techniques -such as feedback trading -which lead to departures of prices from their fundamental values and increase their variability. Oil price changes are here associated with changes in stocks, bonds and effective USD exchange rate. The feedback trading mechanism is combined with an ICAPM scheme. This original model is estimated in a four asset CCC GARCH non linear framework, where the risk premium and the feedback trading components of the conditional means are multiplicative functions of the system's conditional variances and covariances. The empirical analysis, which encompasses the 2008-2009 financial crisis, identifies a structural change in the year 2000. From then on oil returns tend to become more reactive to the remaining assets of the model and feedback trading more pervasive. A comparison is drawn between three and four asset minimum variance portfolios in the two sub-periods, 1992-1999 and 2000-2009. Indeed, the trade-off between risk and returns -measured here by the average return per unit of risk index -indicates that in the last decade oil diversifies away the empirical risk of our portfolio. n n J J J J J t jz z t z z t z
Energy Economics, 2014
This study attempts to contribute to the literature on stock markets and energy prices by examining the dynamic volatility and volatility transmission between oil and Ghanaian stock market returns in a multivariate setting using the recently developed VAR-GARCH, VAR-AGARCH and DCC-GARCH frameworks. In turn, the models' results are used to compute and analyze the optimal weights and hedge ratios for oil-stock portfolio holdings. For comparison purposes and to put the paper more in the perspective of West Africa, the Nigerian stock market is also included in the analysis. Our findings point to the existence of significant volatility spillover and interdependence between oil and the two stock market returns. While spillover effects are stronger for Nigeria, the transmission of volatility is much more apparent from oil to stock than from stock to oil in the case of Ghana. Also, the study demonstrates evidence of short-term predictability in oil and stock price changes through time and reveals that conditional volatility changes more rapidly as result of substantial effects of past volatility rather than past news/shocks for all market returns. Moreover, we show that there is a slightly more effective hedge in the two stock markets under the DCC-GARCH framework (our preferred model) compared to the other two models, although hedging effectiveness is much greater for Ghana. On the whole, our findings for optimal hedge ratios are consistent with other studies and particularly the view that oil assets should be an integral part of a diversified portfolio of stocks and suggest that a better understanding of volatility links is crucial for portfolio management in the presence of oil price risk. Finally, the existence of multivariate asymmetric effects and dynamic conditional correlations as revealed by the VAR-AGARCH and DCC-GARCH models make it clear that the assumptions of symmetric effects and constant conditional correlations are not supported empirically.