|dc.description.abstract||My thesis investigates three major issues related to futures markets namely, market efficiency, risk premium, and information diffusion in futures. This thesis makes a significant contribution to the existing literature of futures markets in several ways. First, it introduces a novel market efficiency test in the presence of a time-varying risk premium. Second, it introduces a new market efficiency index based on the proposed efficiency test to measure the degree of efficiency of futures markets. Third, it estimates and extensively investigates futures market risk premiums. Fourth, it introduces a new common factor to explain variations common to a cross section of futures returns. The empirical analysis in this thesis is based on a comprehensive sample of 202 futures traded on 36 exchanges globally that represent six market sectors over the period 2000-2011. The impacts due to the recent financial crisis periods are also analysed in my thesis.
Chapter 1 of this thesis demonstrates the background and research questions, motivations, objectives, and contribution. Chapter 2 is dedicated to explain the fundamentals of futures markets. In chapter 3, I introduce a new efficiency test for futures markets that accounts for time-varying risk premium and conditional heteroscedasticity of spot prices. Such a test does not exist in the literature. Using a Monte Carlo simulation, I demonstrate that the proposed test is superior to the conventional approaches in the literature. The test is used to analyze the efficiency of crude oil, corn, copper and gold futures and finds that gold is inefficient during the entire period 2000-2011 while the others are efficient after the global financial crisis (GFC) in 2008. Moreover, I find a significant impact on risk premiums of the four futures contracts due to the GFC where both the size and the volatility of the premiums have been increased. Chapter 4 introduces the new market efficiency index which is based on the efficiency test introduced in chapter 3. This efficiency index is based on the price information corresponding to a series of lagged time points prior to the maturity of a contract unlike in a traditional efficiency test which is normally based on the information of a single lagged time point. An efficiency test finds whether a market is efficient or not, whereas the efficiency index can be used to quantify the degree of price efficiency of a futures market. The proposed efficiency index uses a kernel based weighting method where the weights are decreased over the time lags towards the maturity to reflect the importance of the price information. This index is used to examine the market efficiency of 202 futures from energy & fuel, precious metals, industrial materials, and agricultural & live stock markets during 2000-2011. An extensive comparison of both efficiency and risk premiums across market sectors, exchanges, and regions is done. As a result, I find that the market sector as a key factor for varying risk premiums but not for the market efficiency. Futures exchanges and regions where those exchanges are located in can be considered as minor factors that may influence the risk premiums. Moreover, I find that the GFC has significantly caused to change the risk premiums but not the market efficiency. More specifically, a major shift in risk premiums towards a positive status can be observed after the GFC.
In chapter 5, I construct a common factor for futures returns which can be used to explain the commonality of returns in a market sector caused by global macroeconomic forces. This factor assumes conditional heteroscedasticity in returns and extracts common market specific information in futures returns into an index by filtering asset-specific idiosyncratic variations. The proposed common factor is used to examine fundamentals of different futures market sectors. In this chapter, I find that conditional variances of the common factors are increased mainly due to the GFC. Eurozone crisis (EUC) has also made an impact to increase conditional variances but it is not severe as the GFC. In the same chapter, I perform a dynamic conditional correlation analysis and find evidence for increasing trend in correlations among market sectors during 2005-2011. This reveals that information related to global macroeconomic factors are shared among the futures markets. Financial turmoil temporarily relaxes these linkages between commodity and non-commodity futures markets. Moreover, the information diffusion process in futures markets is examined in chapter 6. In chapter 6, using a Granger causality analysis, I show that the fluctuations in mean returns of precious metals and grains & oilseeds have major impacts on other market dynamics especially during crisis periods. Volatility in currency futures has also influenced other market volatilities during the GFC. Granger causality in extreme downside risks is prominent from commodity markets such as industrial materials, precious metals, and agricultural & livestock. Finally, rolling spillover indices developed in the same chapter based on impulse response functions demonstrates that the impact of shocks of one futures market on other futures markets is also boosted during the GFC and EUC. In this thesis, I document that, commodity futures markets play a major role in diffusing information related to market shocks to other market sectors. In contrast, the index futures market absorbs information from other markets.||