Study On The Complexity Of Petroleum Markets And Its Multi-Agent Simulation Approach

In recent decades, with the rapid growth of China's economy and drastic fluctuations of international petroleum markets, oil price behaviors and dynamics have a great impact on both China's economy and social welfare. Petroleum markets, consisting of heterogeneous agents with different utilities, expectations and capabilities, are typical complex systems in that they are greatly influenced by many factors, such as macro-economic situations, international affairs, political and military outbursts, financial speculations, market psychology, etc, as well as fundamental factors like supply and demand. The mutual interactions among those factors make the market dynamics highly complex and even a minor disturbance of one factor can induce unexpectable outcomes. Numerous empirical studies put forward evidence that international petroleum markets are nonlinear dynamic systems with chaotic and fractal features. As for these complex systems, traditional linear paradigms are of nullification, while reductiomsm becomes one of major barriers to understand the true underlying dynamics and mechanisms of those markets.In order to obtain the reliable analytical results and applicable strategies and policy suggestions, the dissertation applies the methods and approaches of Chaos and Fractal theories and Multi-Agent based System, to carry out systematical empirical and simulation study on the petroleum price dynamics mainly on the contexts of Complex Systems and Complexity Science, by investigating experimentally and empirically the underlying dynamics and mechanisms of those markets, thus to come to applicable conclusions of international price dynamics and behaviors, and thereby provide quantitative and qualitative evidence for the policy making of China's energy strategy.The main contributions and findings of this dissertation can be summarized as follows:(1) Using the Phase Space Reconstruction Technique (PSRT), the evidence of the existence of chaos are found in the time series of the monthly and daily Brent and WTI crude oil price fluctuations in the markets. By applying G-P algorithm, the low dimensional (less than 3) non-integer correlation dimensions are obtained, which imply that those above-mentioned systems are low dimensional deterministic chaotic systems with fractal features. Using a Wolf algorithm, the dissertation acquires positive largest Lyapunov exponents, thus identify the existence of chaos in all 4 systems under study. Furthermore, the dissertation also obtains positive Kolmogorov entropies which can be used for estimating the periods of effective prediction of Brent and WTI crude oil prices in markets, e.g., the Kolmogorov entropy of daily returns of Brent is 0.2787, which means the reliable prediction period be less than 36 days.(2) The fractal behaviors for the prices are investigated in international petroleum price systems by using the Rescaled Range analysis (R/S analysis) based on the time series of Brent & WTI crude oil prices (daily spot) and Rotterdam & Singapore leaded gasoil prices (daily spot). The dissertation estimates the Hurst exponents of the systems under study, whose results are greater than 0.5 at all characteristic time scales, which imply that those systems are biased and consistent with positive persistency and fractal features. Furthermore, using V statistics, the dissertation discovers long-term memory effects in the systems and estimate the lengths of the persistent memory of historical information, e.g., 683 days is the approximate non-periodic cycles of the long-term memory in Brent 60-day returns. By tracing the evolution tracks of H(t)\s.t , three phases divided by different system dynamic behaviors are found and thus we put forward a hypothesis that the dynamics of the three phases are dominated by the three categories of heterogeneous agents, which are noise traders, producers and fundamentalists respectively. Finally, the empirical study also demonstrates nontrivial multifractal spectra in the petroleum price systems, which gives evidence of irregularity and heterogeneity in the fractal structures of the systems.(3) Based on the time series of Brent crude oil and Rotterdam gasoil prices, the dissertation analyses the information of price fluctuations with the two important parametersτ(investor's time scale of investment) andε(investor's expectation of returns) by using Zipf-type analysis, i.e. by mapping theτ- returns of prices into binary sequences (relative frequencies) and 3-charactered sequences (absolute frequencies), which containing the fundamental information of price fluctuations. According to the quantitative results of above mentioned analysis, the dissertation obtains some non-trivial findings. Firstly, by analyzing the deviations of the ups and downs at different time scales, the dissertation finds that there exist non-zero (mainly positive) deviations which are getting greater as the time scales increasing, which imply the price systems are biased and asymmetric. Secondly, this dissertation investigates the parametersτandεempirically and identifies various types of investors' cognition patterns of price behaviors. Thirdly, the dissertation discusses the causes of formation of those cognition patterns and enormous distortion of price behaviors by the patterns and finds that generally speaking, the higher the parametersτgets, the probabilities of ups are greater; the greedier the investors are, the more distortions of price behaviors are from the actual price dynamics. Fourthly, as long asεreaches its critical points, it will not be able to distort the price behaviors because otherwise the investors will be cleared out of the markets. Finally, the comparisons between Brent and Rotterdam price systems show that although there are some minor differences of numerical results in the two systems, they are fundamentally similar regarding of their price behaviors.(4) A virtual financial market model is introduced which is based upon an analogue of two-dimensional and three-state random field Ising model (RFIM) under a market maker scenario. By applying the grid network and torus topology, we introduced the periodic boundary condition and parameters of self confidence and idiocratical expectations of agents to the virtual market with heterogeneous agents and a market maker. Combining the scaling/multiscaling analysis, we acquired some non-trivial findings: first, in accordance with many empirical results, the price returns of this virtual market generated by this RFIM-type model display stylized facts in real markets, e.g. volatility clustering; secondly, we find that the inherent price behaviors have the surprising similarities with the real financial market returns in a qualitative sense; in addition to the above-mentioned findings, we find that the quantitative results, e.g. Hurst exponents, of the virtual markets are highly similar to those empirical results of the real ones. Our findings imply that although the real markets demonstrate complex superficial behaviors and phenomena, the innate dynamics of the real markets may be fundamentally simple.Based on the above-mentioned quantitative and qualitative results, this dissertation carries out further policy studies of domestic petroleum markets and petroleum price risks respectively. Some applicable policy suggestions are proposed for China's energy strategy and policy-making of improving China's petroleum price security on the background of economical globalization and financial petroleum markets nowadays.Through the above-mentioned systematic analyses of empirical and experimental results as well as relevant policy study, this dissertation arrives at a series of conclusions and policy suggestions.