Oil price effect on sectoral stock returns: A conditional covariance and correlation approach for Mexico

This paper analyzes the relationship between the volatility of oil price and selected sectoral stock returns in Mexico (industrials, materials, financials and consumer discretionary) by implementing a Diagonal VECH-type bivariate GARCH model in order to estimate conditional covariances and correlations. The econometric results suggest that there exists a statistically significant relationship between sector indices, as well as between Mexico’s aggregate stock exchange returns, and variations in oil prices. Conditional correlations suggest that during most of the analyzed period, the relationship between oil price fluctuations and sectoral stock returns is positive. The recommendation, supported by these results, is that investors should take into consideration the interaction between the analyzed variables in order to generate more robust risk-hedge strategies. An important limitation for this work is information availability at sector level in the country. The original contribution of this paper lies mainly in the analysis of the influence of oil prices over sectoral indices of the Mexican Stock Exchange. These results provide more support to the current that suggests that a price increase in oil has a direct spillover effect on stock market performance.

Volatility Transmission between Oil and LME Futures

This paper investigates the volatility transmission between oil and base metals to assess the possibility of hedge strategy across commodity markets. In order to identify the volatility linkage of oil to the base metals, the bivariate GARCH model is applied using daily returns data period over 2000-2016. It is found that evidence of volatility transmission between oil and base metals is somewhat strong with a 1% significant level. This result suggests the investment idea of commodity hedging strategy of cross-market is important.

Co-movements in stock market returns, Ireland and London 1869–1929

This article studies the relationship between the Irish and London stock markets over the period 1869 to 1929, using monthly data on capital gains. A bivariate GARCH model shows that there were significant volatility spillovers from the London to the Irish market, but not vice versa. This suggests that shocks originating in London were transmitted to Ireland, but that the reverse did not occur. Furthermore, the time-varying correlation indicates that the co-movement between London and Ireland declined during the Irish independence struggle and the establishment of the Irish Free State. The correlation appears to stabilise in the late 1920s.

Price Discovery In The Soybean Futures Market

This paper investigates the price discovery process between the nearby futures prices of soybean, soy meal, and soy oil contracts (Crush constituents) in the U.S. Relationships between these commodities may bear important implications for trading strategies, market inefficiencies, or the derived demand theory. Furthermore, our findings are relevant in light of market microstructure theories, which maintain that the price information disseminates from more liquid contracts. Our VAR and bivariate GARCH model estimates suggest a strong bi-directional causality in Crush futures prices. We also find that while soybean contracts bear the burden of convergence when the spread between soybean and soy meal contract prices widens, this is not true of soybean and soy oil contracts. Furthermore, we show evidence of considerable volatility persistence for the three contracts and volatility spillover between soybean and other Crush constituent futures. The statistical evidence suggests that information arrives in these markets simultaneously. Our findings do not support the derived demand theory.

Empirical Study on the Maturity Structures of the Volatility in the KOSPI200 Index and Futures Returns

This study analyzes the maturity structure of the volatility in the KOSPI200 index and futures returns. Using bivariate GARCH model, we obtain the empirical evidences that the maturity structure of the volatility is U-shaped unlike the well-known Samuelson effect. Remarkably. U-shaped structures are found not only in the futures market but also in the spot market These evidences imply that returns are more volatile around tile futures maturity date in both markets. Some explanations are suggested about U-shaped maturity structures. First, under Samuelson hypothesis it is possible to show that the volatilities are high around the maturity date because of the volatility clustering and the volatility spill-over. Second, we try the regression of the volatility on variables such as the proportion of the individual investors, the foreign investors, and the program trading. These variables are U-shaped or inverse U-shaped due to the remaining maturity. Only before 2000, it is found that the proportions of the foreign investors and the program trading are compatible with U-shaped volatility structures.

Intraday Volatility in the Korean Stock Ind and Korean Stock Index Futures Markets

This paper tries to find the information flow between KOSPI200 Index and KOSPI200 Futures more accurately by considering two models. First, three-stage least-squares regression is used to estimate lead and lag relationships based on the representation of a simultaneous-equations model because futures and cash returns may affect each other contemporaneously. Secondly, a bivariate GARCH model is used because the lead-lag relationships between the two markets should consider not only return itself but also return volatility. The results from the first regression suggest that KOSPI200 futures returns and the index are simultaneously related and that the lead from futures to cash returns extends for about 40 minutes and the lead from cash to futures returns extends for about 30 minutes, which means the lead-lag relationship between the two markets are not unidirectional. I find from the analysis of a bivariate GARCH model that the information flow between the two markets is rather symmetrical when the volatility relationships are also considered, although it seems non-symmetrical when the returns relationships alone are considered. I also find a much stronger dependence in both directions in the volatility of returns between the cash and futures markets than that observed in the returns alone. When I consider intraday volatility as well in the lead-lag relationship between the two markets, KOSPI200 futures markets strongly lead index markets but KOSPI index do not lead futures markets. Evidence also suggests strong intermarket dependences in the conditional volatilities and in the return shocks. So the results have implications for understanding the pattern of information flows between the two markets.