Oil and portfolio risk diversification (original) (raw)
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Can oil diversify away the unpriced risk of a portfolio?
International Journal of Finance & Economics, 2011
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.
Is Oil a Financial Asset? An Empirical Investigation Spanning the Last Fifteen Years
SSRN Electronic Journal, 2009
The growing presence of financial operators in the oil markets has modified oil price dynamics. The diffusion of techniques based on extrapolative expectations-such as feedback trading-leads to departures of prices from their fundamental values and increases 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 and provides a model which is then estimated in a CCC GARCH-M framework, both the risk premium and the feedback trading components of the conditional means being nonlinear functions of the system's conditional variances and covariances. The empirical analysis 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 2000-2008. Oil acquires in the second period, besides its standard properties as a physical commodity, the characteristics of a financial asset. 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.
Keywords: Volatility spillover Oil market Stock markets Oil-importing and oil-exporting countries Portfolio and hedging implications Symmetric and asymmetric DCC-GARCH modelsJEL classification: F65 G11 A B S T R A C T This study analyses the volatility spillover between the oil market and the stock market of oil-importing and oil-exporting countries using daily data over the period from January 2010 to December 2016. The study also explores the portfolio and hedging implications based on dynamic conditional correlation (DCC) and corrected DCC (cDCC) GARCH models. For the analysis, we have used symmetric and asymmetric versions of DCC and cDCC models. Specifically, in the symmetric version of DCC and cDCC, the estimations are based on GARCH (1,1), and in the asymmetric version of DCC and cDDC, the estimations are based on GJR-GARCH (1,1), FIGARCH (1,1) and FIEGARCH (1,1) models, and for each case, we have explored the portfolio and hedging implications. Overall, the evidence indicates that oil-importing countries are severely affected by lagged oil price shocks, and there is less evidence of interdependence between stock markets for both oil-importing and oil-exporting countries. Further, we find that the lagged volatility in the oil market and stock market has a statistically significant impact on the current volatility in its respective markets. The results from the asymmetric analysis show that the magnitudes of the negative shocks are higher than those of the positive shocks. The overall results from portfolio optimization reveal that investors in oil-exporting countries should hold more oil assets in the portfolio to hedge the risk.
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.
Assessing for Time Variation in Oil Risk Premia: An Adcc-Garch-Capm Investigation
Energy Studies Review, 2015
This paper focuses on oil market dynamics through the investigation of oil systematic risk and oil risk premium dynamics over the period 1997-2012, which includes several different economic episodes, enabling us to capture a considerable number of statistical properties for oil prices. Interestingly, unlike previous studies, the authors retained data for several developed and emerging oil markets and used different oil prices in order to provide a comprehensive and wide-ranging vision of oil price dynamics. To this end and in order to take eventual time variation and asymmetry in oil price dynamics into account, the authors applied recent econometrics tests associated with the ADCC-GARCH class of model. This modelling enabled us to appropriately specify the dynamics of oil conditional variance and time-varying oil risk premium. Accordingly, this study offers three interesting findings. First, the hypotheses of asymmetry and time variation in oil risk premia are not rejected. Second,...
SAGE Open
Using the DCC-GARCH model, this study examines the return and volatility spillovers between crude oil and emerging Latin American stock markets during the entire studying period and two subsamples, including the global financial crisis and the Chinese Stock market crash. The findings reveal a positive causal effect from Brazil and Mexico’s stock price changes to the oil market during the global financial crisis. During the Chinese stock market crash, the return spillover is unidirectional from the oil to Brazil and Mexico equity markets. The findings show no significant volatility transmission between oil and Latin American stock markets during the global financial crisis. Contrarily, we observe bidirectional volatility transmission between the oil and Brazilian stock markets during the Chinese stock market crash. Finally, we calculate the optimal weights and hedge ratios for the oil and stock portfolios. In comparison to the global financial crisis, the results suggest that lesser ...
OIL PRICES AND STOCK MARKET CORRELATION: A TIME-VARYING APPROACH
2013
This paper examines the influence of oil prices on stock market time-varying correlation. Five stock market indices from both oil-importing (US, UK and Germany) and oilexporting economies (Canada and Norway) are considered for the period 1988-2011. The findings from the DCC-GARCH framework suggest that the effects of oil price changes on stock market correlation are not constant over time and they depend on the status of the economy, i.e. whether it is oil-importing or oil-exporting. In addition, utilising the identification of oil price shocks in [1], [2] and [3] it is found that the aggregate demand shocks and precautionary demand shocks tend to exercise a negative effect on stock market correlation, whereas no effects from the supply-side oil price shocks can be reported. These findings have important implications for international portfolio diversifications and risk management.
Oil volatility, oil and gas firms and portfolio diversification
Energy Economics, 2018
This paper investigates the volatility spillovers and co-movements among oil prices and stock prices of major oil and gas corporations over the period between 18th June 2001 and 1st February 2016. To do so, we use the spillover index approach by Diebold and Yilmaz (2009, 2012, 2014, 2015) and the dynamic correlation coefficient model of Engle (2002) so as to identify the transmission mechanisms of volatility shocks and the contagion of volatility among oil prices and stock prices of oil and gas companies, respectively. Given that volatility transmission across oil and major oil and gas corporations is important for portfolio diversification and risk management, we also examine optimal weights and hedge ratios among the aforementioned series. Our results point to the existence of significant volatility spillover effects among oil and oil and gas companies' stock volatility. However, the spillover is usually unidirectional from oil and gas companies' stock volatility to oil volatility, with BP, CHEVRON, EXXON, SHELL and TOTAL being the major net transmitters of volatility to oil markets. Conditional correlations are positive and time-varying, with those between each of the aforementioned companies and oil being the highest. Finally, the diversification benefits and hedging effectiveness based on our results are discussed.