Real Option Pricing in Mixed-use Development Projects

The application of real options theory to commercial real estate has developed rapidly during the last 15 Years. In particular, several pricing models have been applied to value real options embedded in development projects. In this study we use a case study of a mixed use development scheme and identify the major implied and explicit real options available to the developer. We offer the perspective of a real market application by exploring different binomial models and the associated methods of estimating the crucial parameter of volatility. We include simple binomial lattices, quadranomial lattices and demonstrate the sensitivity of the results to the choice of inputs and method.

Interest rate models with Markov chains

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Co-developing Johan Castberg and Alta/Gohta: a real options approach

Masteroppgave i Energy management - Nord universitet, 201

The Strategic Exploitation of Limited Information and Opportunity in Networked Markets

This paper studies the effect of constraining interactions within a market. A model is analysed in which boundedly rational agents trade with and gather information from their neighbours within a trade network. It is demonstrated that a trader’s ability to profit and to identify the equilibrium price is positively correlated with its degree of connectivity within the market. Where traders differ in their number of potential trading partners, well-connected traders are found to benefit from aggressive trading behaviour.Where information propagation is constrained by the topology of the trade network, connectedness affects the nature of the strategies employed

Economic Valuation Models for Insurers

Recently much attention has been given to the approaches insurers undertake in valuing their liabilities and assets. For example, in 1994 the American Academy of Actuaries created a Fair Valuation of Liabilities Task Force to address the issue. In 1997, the Academy established a Valuation Law Task Force and a Valuation Tools Working Group to investigate the various valuation approaches extant and to make recommendations on which models are best suited to the task. Much of the published work has focused on attributes of the various models, their strengths and shortcomings. Some of the work has addressed the larger questions, but in our view, it is useful and necessary to provide a taxonomy of approaches and evaluate them in a systematic way in accordance with how well they achieve their aims. In this paper we focus primarily on the economic valuation of insurance liabilities, although we do address some valuation issues for assets. We begin in Section I by defining insurance liabilities. Next, in Section II, we discuss the criteria for a good economic valuation model. This is followed by a taxonomy of valuation models in Section III. In Section IV, we examine insurance liabilities in the context of this taxonomy and identify the minimum requirements of an economic valuation approach that purports to value them adequately. An illustration of the application of a modern valuation model is given in Section V. We conclude in Section VI by discussing some limitations of our analysis, and offer some recommendations for implementation.

The History of the Quantitative Methods in Finance Conference Series. 1992-2007

This report charts the history of the Quantitative Methods in Finance (QMF) conference from its beginning in 1993 to the 15th conference in 2007. It lists alphabetically the 1037 speakers who presented at all 15 conferences and the titles of their papers.

Generation planning for electric power utilities under market uncertainties: a real options approach

The generation business in the U.S. is currently undergoing a transition from a regulated monopoly toward an uncertain, competitive market. Under the competitive market, the price of electric power as well as the corresponding revenue may be much less certain than before. These market uncertainties have increased the significance of two critical factors in generation planning. These factors are financial risks and managerial flexibilities.;In order to quantitatively and objectively address these two factors in generation planning, in this dissertation, we design and analyze a series of mathematical models based on the real options approach for generation planning. Hence, this dissertation can be viewed as a comprehensive study of the real options approach in generation planning.;The dissertation begins with a simple multiple-project single-option model based on the Black-Scholes option-pricing formula. This is followed by a single-project multiple-option model based on geometric Brownian motion process, binomial lattice, and backward dynamic programming.;Next, we design and analyze sophisticated multiple-project multiple-option models where the market values of the projects are assumed to be correlated. As before, we employ the backward dynamic programming over the lattice to determine the optimal options for the multiple projects and the corresponding values of the investment. Also, we investigate the roles of the correlation coefficients among projects in decision making and the value of an option.;In addition, we construct and analyze a traditional generation planning model that incorporates forced customer outage costs and forced utility outage costs. By incorporating forced customer outage costs, we attempt to take customer satisfaction level into account. We compare and contrast the models from the real options approach as well as the traditional approach.;We hope that the results of this dissertation will encourage utilities to effectively utilize the real options approach in generation planning under market uncertainties. As this approach can address the financial risks and managerial flexibility while the classical discounted cash flow approaches can not, we also hope that generation planning can be performed more quantitatively and objectively under the new economic uncertainties

Real Option Valuation of a Portfolio of Oil Projects

Various methodologies exist for valuing companies and their projects. We address the problem of valuing a portfolio of projects within companies that have infrequent, large and volatile cash flows. Examples of this type of company exist in oil exploration and development and we will use this example to illustrate our analysis throughout the thesis. The theoretical interest in this problem lies in modeling the sources of risk in the projects and their different interactions within each project. Initially we look at the advantages of real options analysis and compare this approach with more traditional valuation methods, highlighting strengths and weaknesses ofeach approach in the light ofthe thesis problem. We give the background to the stages in an oil exploration and development project and identify the main common sources of risk, for example commodity prices. We discuss the appropriate representation for oil prices; in short, do oil prices behave more like equities or more like interest rates? The appropriate representation is used to model oil price as a source ofrisk. A real option valuation model based on market uncertainty (in the form of oil price risk) and geological uncertainty (reserve volume uncertainty) is presented and tested for two different oil projects. Finally, a methodology to measure the inter-relationship between oil price and other sources of risk such as interest rates is proposed using copula methods.Imperial Users onl

CALLABLE SWAPS, SNOWBALLS AND VIDEOGAMES

Although economically more meaningful than the alternatives, short rate models have been dismissed for financial engineering applications in favor of market models as the latter are more flexible and best suited to cluster computing implementations. In this paper, we argue that the paradigm shift toward GPU architectures currently taking place in the high performance computing world can potentially change the situation and tilt the balance back in favor of a new generation of short rate models. We find that operator methods provide a natural mathematical framework for the implementation of realistic short rate models that match features of the historical process such as stochastic monetary policy, calibrate well to liquid derivatives and provide new insights on complex structures. In this paper, we show that callable swaps, callable range accruals, target redemption notes (TARNs) and various flavors of snowballs and snowblades can be priced with methods numerically as precise, fast and stable as the ones based on analytic closed form solutions by means of BLAS level-3 methods on massively parallel GPU architectures.Interest Rate Derivatives; stochastic monetary policy; callable swaps; snowballs; GPU programming; operator methods