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This thesis is concerning the problematic of derivatives which can be applicable for commodity risk hedging. The futures contracts and options are utilized for hedging commodity risk on oil market. For purposes of this work is designed a trading strategy, which consists of exponential moving average and expiration cycle of the options. The strategy is tested on historical oil prices. Because the strategy shows promising outputs it was employed on setting options strategy as well. The hedging options strategy collar is tested on historical prices of oil. Testing on historical prices discovered that it is profitable for processor to hedge the oil price by futures contracts. For producer it is more profitable to hedge the price by employing standard collar strategy. On the other side the bear collar strategy generated quite unconvincing outputs for processor. When the out-the-money bear collar war modified into in-the-money bear collar the outputs were satisfactorily profitable.

The thesis describes and applies two parametric option pricing models which partially ease the well-known discrepancy between real world and Black-Scholes model. Stochastic volatility and jumps encompassed by Heston and SVJ models explain implied volatility smile and its heterogeneous term-structure. Both models are calibrated to market data observed for EURUSD currency options on January 23, 2015. While SVJ model provided a better fit for the market, especially for mid-term expiry smile curvature, its estimated risk-neutral parameters were unrealistic comparing with their counterparts under statistical measure. Estimations suggest zero long term price volatility and 2 jumps during the year with average magnitude of 6 \%. Both models failed to match curvature of short time to expiry smile and provided a good fit of term-structure and long-expiry smile. Analysing delta ratios adjusted for non-constant volatility as a possible alternatives the study considered minimum variance delta estimated with Heston model, delta ratio recommended by Nassim Taleb and two deltas adjusted for local volatility assuming sticky moneyness and sticky tree dynamics of implied volatility. On data set of EURUSD options from 1.1.2014 to 30.5.2015, our research did not find any alternative which would be more reliable than common Black-Scholes delta.

This thesis studies two optimization problems: the optimization of a staffing policy assuming non stationary Poisson demand, and exponential travel and job times, and the optimization of investment decisions with an investment lag. In the staffing policy optimization, we solve a novel time-dynamic Hamilton-Jacobi-Bellman equation that models jobs as a Poisson jump process. The model gives the employer the flexibility to control the number of staff hired by two factors: the cost of hiring and the effect of delay. We have solved the optimal staffing policy problem using different approaches, which are compared. We produce accurate numerical results for different parameters, and discuss the advantages and disadvantages of each approach. Moreover, we have solved a staffing problem for a national utility company, using a standard linear programming approach, which is compared with our methods. In addition to the Poisson jump process, we extend the model to treat a continuous job model, and two locations model that is extendible to a larger network problem. In the investment lag problem, we use a mixture of numerical methods including finite difference and body fitted co-ordinates to form a robust and stable numerical scheme which is applied to solve the investment lag problem for a geometric Brownian motion presented in the paper by Bar-Ilan and Strange (1996). The problem is to calculate the optimal price to invest in a project that have a time lag period between the decision to invest and production, and the optimal price to mothball the project. The method presented in this thesis is more flexible as we compare it with the previous results, and solves the problem for different stochastic processes, such as Cox-Ingersoll-Ross model, which does not have analytic solution.

The development of new infrastructure invariably requires massive capital investments, take many years to design and deliver, and are expected to operate for several decades. During delivery and operational lifetime, the functional requirements are likely to change. To make the assets economically adaptable to foreseeable changes, sizeable investments in design flexibility may be required upfront. Under uncertainty about the future and tight budgets, multi-stakeholder teams must trade-off additional investments in flexibility with more affordable investments in rigid designs at risk of costly adaptation. How to help project teams bridge their divergences and coalesce their views of the world into a project strategy is the core question at the heart of this research. After reviewing the limitations of current practice and theory in the management of capital projects, this study turns to real options reasoning. By definition, investments in design flexibility can be equated with buying options: if the future resolves favourably, the options can be exercised to adapt the design economically. To advance theory and practice on capital design for evolvability, this study combines case-based with experimental work. First, an exploratory study reveals that, despite using options thinking, project teams find real options mathematical models inadequate to support mundane design decisions. A subsequent study on design practices at Network Rail shows the difficulties of designing for evolvability become amplified with multiple stakeholders. With asymmetry in capabilities, knowledge, and power to influence decisions, multi-stakeholder teams systematically resort to a combination of informal options thinking and ‘money talks’ to resolve concept design. Tensions flare up whenever stakeholders demanding investments in design flexibility cannot fund them. These findings suggest that a formal procedure to design for evolvability can offer a superior approach at front-end strategizing. To test this proposition, this research develops an original proof-of-principle of a formal design for evolvability framing that cross-fertilizes literature on project risk management and real options theory with insights from the fieldwork. It also develops a two-group experiment – grounded on fine-grained empirical data from a real-world rail station project – to compare the performance of the experimental and control groups in terms of effectiveness, efficiency, and satisfaction. The results show that a formal design for evolvability framing can improve front-end strategizing. As project teams become more efficient, they have more time to effectively resolve the design for evolvability strategy. Importantly, teams are unlikely to reject attempts to formalize the decision-making process. The study also shows that a formal design for evolvability strategy can improve the accountability of decision-makers for investments in design flexibility. Final considerations discuss the generalizability and limitations of these insights, and future directions.

An option is a contract between two parties where the holder has the option to buy or sell some underlying asset after a predefined exercise time. Options where the holder only has the right to buy or sell at the exercise time is said to be of European-style, while options that can be exercised any time before the exercise time is said to be of American-style. Asian options are options where the payoff is determined by some average value of the underlying asset, e.g., the arithmetic or the geometric average. For arithmetic Asian options, there are no closed-form pricing formulas, and one must apply numerical methods. Several methods have been proposed and tested for Asian options. For example, the Monte Carlo method isslowforEuropean-styleAsianoptionsandnotapplicableforAmerican-styleAsian options. In contrast, the finite difference method have successfully been applied to price both European- and American-style Asian options. But from a financial point of view, one is also interested in different measures of sensitivity, called the Greeks, which are hard approximate with the finite difference method. For more accurate approximations of the Greeks, researchers have turned to the finite element method with promising results for European-style Asian options. However, the finite element method has never been applied to American-style Asian options, which still lack accurate approximations of the Greeks. Here we present a study of pricing European- and American-style Asian options using the finite element method. For European-style options, we consider two different pricing PDEs. The first equation we consider is a convection-dominated problem, which we solve by applying the so-called streamline-diffusion method. The second equation comes from modelling Asian options as options on a traded account, which we solve by using the so-called cG(1)cG(1) method. For American-style options, the model based on options on a traded account is not applicable. Therefore, we must consider the first convection-dominated problem. To handle American-style options, we study two different methods, a penalty method and the projected successive over-relaxation method. For European-style Asian options, both approaches give good results, but the model based on options on a traded account show more accurate results. For American-style Asian options, the penalty method give accurate results. Meanwhile, the projected successive over-relaxation method does not converge properly for the tested parameters. Our result is a first step towards an accurate and fast method to calculate the price and the Greeks of both European- and American-style Asian options. Because good estimations of the Greeks are crucial when hedging and trading of options, we anticipate that the ideas presented in this work can lead to new ways of trading with Asian options.

Stochastic Differential Equations (SDE) offer a rich framework to model the probabilistic evolution of the state of a system. Numerical approximation methods are typically needed in evaluating relevant Quantities of Interest arising from such models. In this dissertation, we present novel effective methods for evaluating Quantities of Interest relevant to computational finance when the state of the system is described by an SDE.

The joint hypotheses of informationally efficient markets, transparent financial statements, and adequate accounting disclosure suggest that announcements of changes in the accounting treatment of employee stock options from footnote disclosure to expense recognition should not trigger stock price reactions because free-cash-flows will not change. Event study results from a sample of 241 firms that announce such changes reveal statistically significant negative price changes followed by positive price changes about equal in magnitude. We propose the learning, sophisticated investor, neglected firm, and firm size hypotheses to explain the observed announcement-period stock price reaction.

In his book The Limits of Morality, Shelly Kagan claims that contractarian approaches to ethics are incompatible with our common, everyday, "moderate" morality. In this thesis I defend a version of contractarianism that I believe leads to both deontological constraints and options; i.e., to a genuinely moderate morality. On my account, the parties to the agreement are conceived of as being motivated not only to promote self-interest, but also to formulate a code of ethics that gives proper respect to their moral status as persons. If such a picture of the bargainers' motivations is defensible, as I believe it is, then the 'moderate' may in fact have recourse to contractarianism in her defense of everyday morality, for - as my thesis argues - bargainers that are thus motivated will arrive at a moderate morality. / Master of Arts