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This thesis presents a mathematical formulation of informational inhomogeneity in financial markets, with emphasis on its impact on asset volatility, the notion of information extraction, and the role of information providers. We begin with a brief review of the BHM framework, which models the market filtration by an information process consisting of a signal and a noise term, such that the signal-to-noise ratio is determined by the information flow rate. Motivated by the observations that valuable information is rarely circulated homogeneously across financial markets, and that the information flow rate is typically random, we introduce, in the first part of the thesis, an extension of the BHM approach that leads to the simplest class of stochastic volatility models. In this extended framework we derive closed form expressions: for (a) asset price processes; (b) pricing formulae for options; and (c) option deltas. We show that the model can be calibrated to fit volatility surfaces reasonably well, and that it can be used effectively to model information manipulation. In the second part we introduce a framework for the valuation of information. In particular, a new formulation of the utility-indifference argument is introduced and used as a basis for pricing. We regard information as a quantity that converts a prior distributions into a posterior distributions. The amount of information can thus be quantified by relative entropy. The key to our theory is to equate the maximised a posterior utility with the a posterior expectation of the utility of the a priori optimal strategy. This formulation leads to one price for a given quantity of upside, and another for a given quantity of downside information. Various intuitive, as well as counterintuitive implications (for example, price of information is not necessarily an increasing function of the volume of information) of our theory are discussed in detail.

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Petroleum markets are undergoing rapid financialization and integration, leading to increased volatility and exposing participants to potentially much greater risks. This thesis addresses the explicit modeling of petroleum price volatility in a multivariate framework and analyzes the relative merits of multivariate models to describe change in the context of petroleum markets risk. The focus of this thesis will be on explaining the dynamic interdependencies in petroleum markets and further demonstrate whether the existence of such interdependencies prompt for the need to assess risk differently, by which this thesis contributes to the existing economic or econometric theories in three aspects. The first empirical part examines the importance of volatility spillovers and asymmetry in petroleum markets and their influence on optimal hedging strategy. To address in a realistic way the dynamic conditional correlation of petroleum spot and futures markets, we develop a new theoretical framework by accounting for the effect of time-varying conditional correlations in the conditional volatility processes of the VARMA-AGARCH model in what is termed the VARMA-AGARCH-DCC model. Results demonstrate that the proposed model is the best for OHR calculation in terms of the variance of portfolio reduction and tail risk analysis. The second empirical part, for the first time in the literature of energy economics, examines the volatility and correlation interdependence between oil market and China stock market at the sector-level. Results indicate that oil price fluctuations constitute a systematic asset price risk at the sector level and information content embedded in oil market volatility is an effective and valuable variable for constructing an optimal oil-stock holding. Finally, the third empirical part, for the first time in the literature of energy economics, investigates the volatility transmission mechanism among three benchmark oil markets and quantifies the size and persistence of these connections through employing the Volatility Impulse Response Function (VIRF) methodology. Results suggest markedly different responsiveness to historical events and volatility/correlation dynamics across crude oil benchmark markets. Overall, the findings of this thesis have important implications for crude oil market trading and risk management, as well as stock market investors, by providing valuable information on the oil price volatility dynamics and will help market participants develop efficient risk measurement schemes and devise sound risk management strategies.

This thesis is organized in three self-contained projects which model predictability in both advanced and emerging stock markets and attempt to exploit it via construction of appropriate trading strategies. The objectives of this research are: 1) to model mean reversion in developed stock markets and re-assess the mixed empirical findings to date; 2) to characterize the returns generating process in emerging capital markets and examine the predictive ability and profitability of technical trading rules; 3) to develop and evaluate whether trading strategies involving dividend announcements in the UK are profitable and can be classified as statistical arbitrages, with consequent implications for the market efficiency hypothesis. We investigate the existence of mean reversion in the G-7 economies using a two factor continuous time model for national stock index data. Whilst maintaining the same modeling philosophy of previous studies, we rather focus on the effects of the "intrinsic" continuous time mean reverting coefficient. Our method produces support for mean reversion, even at low frequencies, and relatively small samples. We also aim to characterize the stock return dynamics in four Latin American and four Asian emerging capital market economies and assess the profitability of popular trading rules in these markets. We find that dollar denominated returns exhibit statistically significant long memory effects in volatility but not in the mean. "wading' our findings via a number of moving average and trading range break rules, we "beat" the buy and hold benchmark strategy in all markets before transaction costs, and in Asian markets even after transaction costs. Bootstrap simulations further reinforce the choice of the modeling framework and the trading outcomes, particularly for Latin American markets. Finally, we investigate whether trading strategies designed to exploit "abnormal" price behavior following dividend initiation/resumption and omission announcements of UK firms pass the statistical arbitrage test of Hogan et al. (2004). To mitigate concerns regarding "risky" arbitrage, we also calculate the probability of making a loss for each strategy. We find that strategies involving portfolios of dividend initiating/resuming firms are profitable and converge to riskless arbitrages over time, while this is not the case for strategies with dividend omitting firms, contrary to what is suggested by US studies. In general, the robustness of our results casts doubt on the market efficiency hypothesis in both developed and emerging capital markets.

The current literature does not provide efficient models for commodity prices and futures valuation. This inadequacy is partly due to the fact that the two main streams of the literature - structural models and reduced form models - are largely disjoint. In particular, existing structural models are developed under rigid discrete time framework that does not take into account the mean-reverting properties of commodity prices. Furthermore, most of the literature within this class does not analyze the properties of the futures prices. Current reduced-form models allow cash-and-carry arbitrage possibilities and do not take into account the dependence between the spot price volatility and the inventory levels. This thesis investigates three new models for the price of a storable commodity and futures valuation. Specifically, we develop a structural model and two reduced-form models. In doing so, we expand the leading models within each of the two streams of the literature, by establishing a link between them. Each of these models provide an advance of their type. This study makes several contributions to the literature. We provide a new structural model in continuous time that takes into account the mean reversion of commodity prices. This model is formulated as a stochastic dynamic control problem. The formulation provided is flexible and can easily be extended to encompass alternative microeconomic specifications of the market. The results provide an optimal storage policy, the equilibrium prices and the spot price variability. We also develop a numerical method that allows the construction and analysis of the forward curves implied by this model. We provide a separate analysis considering a competitive storage and considering a monopolistic storage. The results are consistent with the theory of storage. Furthermore, the comparison between monopoly and competition confirm the economic theory. We developed a simple reduced-form model that focuses both on the mean reverting properties of commodity prices and excludes cash-and-carry arbitrage possibilities. This model is compared with a standard single-factor model in the literature. This new model adds two important features to the standard model and motivates the development of a more sophisticated reduced-form model. Accordingly, the last model developed in this thesis is a reduced-form model. It is a two-factor model that represents the spot price and the convenience yield as two correlated stochastic factors. This model excludes cash-and-carry arbitrage possibilities and takes into account the relationship between the spot price volatility and the inventory level. We find an analytical solution for the futures prices. This model is tested empirically using crude oil futures data and it Is compared with one of the leading models in the literature. Both models are calibrated using Kalman filter techniques. The empirical results suggest that both models need to be improved in order to better fit the long-term volatility structure of futures contracts.

It is generally accepted in academic circles that the developed country capital markets with their advanced infra-structure, depth and liquidity are at a minimum Weak-Form efficient. Since the Weak-Form EMH proposes that current security prices immediately assimilate all historical information, it therefore also implies that technical analysis (which relies on charts and analysis of past price patterns to extrapolate future price movements) would be a futile exercise. Yet technical analysis has endured over time and is still an intensively and widely used investment analysis technique. This indicates a clear disconnect between technical analysis as employed by practitioners in the market and the technical analysis methodologies utilized by academics in prior Weak-Form EMH studies. The problem is prior technical analysis Weak-Form EMH studies were burdened with methodological weaknesses which severely handicapped the profit generating potential of technical analysis and suggest that previous Weak-Form EMH research findings were erroneous in being unable to reject the null Weak- Form market efficiency hypothesis. This study addresses the problem by eliminating prior methodological weaknesses and utilizing high frequency intra-day data, the combination of qualitative and quantitative techniques and volume signals to develop a portfolio of Intermarket Momentum technical analysis strategies that generate significant excess profits. The objective of this study is therefore to provide evidence that contrary to prior research findings, the developed country capital markets are not Weak-Form efficient. The results show that the portfolio of Intermarket Momentum trading strategies generated returns in excess of the market with a significantly positive Alpha of 8.52% that allowed the rejection of the Null Hypothesis and the acceptance of the Alternative Hypothesis that the developed country capital markets are not Weak-Form efficient, thereby refuting the widely accepted EMH. / Business Management / D.B.L.