Paper [I] tests the success rate of trades and the returns of the Opening Range Breakout (ORB) strategy. A trader that trades on the ORB strategy seeks to identify large intraday price movements and trades only when the price moves beyond some predetermined threshold. We present an ORB strategy based on normally distributed returns to identify such days and find that our ORB trading strategy result in significantly higher returns than zero as well as an increased success rate in relation to a fair game. The characteristics of such an approach over conventional statistical tests is that it involves the joint distribution of low, high, open and close over a given time horizon. Paper [II] measures the returns of a popular day trading strategy, the Opening Range Breakout strategy (ORB), across volatility states. We calculate the average daily returns of the ORB strategy for each volatility state of the underlying asset when applied on long time series of crude oil and S&P 500 futures contracts. We find an average difference in returns between the highest and the lowest volatility state of around 200 basis points per day for crude oil, and of around 150 basis points per day for the S&P 500. This finding suggests that the success in day trading can depend to a large extent on the volatility of the underlying asset. Paper [III] performs empirical analysis on short-term and long-term Commodity Trading Advisor (CTA) strategies regarding their exposures to unanticipated risk shocks. Previous research documents that CTA strategies offer diversification opportunities during equity market crisis situations when evaluated as a group, but do not separate between short-term and long-term CTA strategies. When separating between short-term and long-term CTA strategies, this paper finds that only short-term CTA strategies provide a significant, and consistent, exposure to unanticipated risk shocks while long-term CTA strategies do not. For the purpose of diversifying a portfolio during equity market crisis situations, this result suggests that an investor should allocate to short-term CTA strategies rather than to long-term CTA strategies.

Support for this work from Praxair; the McMaster Advanced Control Consortium; and the Natural Sciences and Engineering Research Council of Canada (NSERC), Grant CRDPJ 445717, is gratefully acknowledged. / In the air separation industry, cryogenic distillation is the dominant technology for separating large quantities of air into individual high purity component products. Due to the complexity of the process, in addition to significant energy input, air separation units (ASUs) also have high degrees of material and thermal integration and low process agility. As markets become more competitive and dynamic, especially after electricity market deregulation, ASUs can no longer practice mostly stationary operations, and are in need for design and control strategies to achieve high adaptability. In this study, we address such issues through a dynamic optimization framework. The use of rigorous dynamic models is important for developing economically beneficial designs and operating practices. The first part of this study focuses on the modeling aspect. For the column section of the plant, a full-order stage-wise model and a collocation based reduced order model are proposed. Model size, simulation time and predication accuracy are compared. For the primary heat exchanger, a novel moving boundary model is derived to handle the phase change in such a multi-stream heat exchanger. Simulation results demonstrate the capability of the proposed model in tracking the boundary points of the phase change occurrence, as well as the potential pinch point, along the length of the heat exchanger. The second part of the study addresses the operation aspects of ASUs through conducting dynamic optimization studies with collocation based dynamic models. We first performed a comprehensive analysis for a storage-then-utilization strategy on a nitrogen plant, following a two-tier multi-period formulation. As the parameter varies with time, the plant collects liquid, either directly from liquid product or by liquefaction of overproduced gas product, and then redistributes it for meeting gas product demand or as additional reflux. Effects of electricity price and demand profiles, additional operation costs, as well as product specifications are explored. Then we investigated the economic incentive for employing preemptive actions on a super-staged argon system, which allows the plant to take actions before external changes arrive. In the evaluation, changes are in the gas oxygen product demand. During the preemptive period, the plant takes either a single set or multiple sets of control actions. In the demand increase case, operation degrees of freedom are introduced to or removed from the set of decision variables. The demand decrease scenarios are explored with an under-supplied or saturated liquid oxygen market. / Dissertation / Doctor of Philosophy (PhD)