Application of the American Real Flexible Switch Options Methodology A Generalized Approach

The paper deals with the inclusion of flexibility in financial decision-making under risk. It describes the application of the real options methodology with the possibility of sequential multinomial decision-making. The basic intention is to describe and apply a generalized approach and methodology of the flexibility modeling and valuation based on multiple choices and non-symmetrical switching costs under risk. The stochastic dynamic Bellman optimization principle is explained and applied. The optimization criterion of the present expected value is derived and used. Likewise, an option valuation approach based on replication strategy and risk-neutral probability is applied. An illustrative example of the application of the real multinomial flexible non-symmetrical switch options methodology is presented for three chosen modes. The option flexible values are computed. The usefulness, effectiveness, and suitability of applying the generalized flexibility model in company valuation and project evaluation is verified and confirmed. The significance of applying the generalized methodology in transition market economies is discussed and verified.financial options; real options; Discrete Binomial Model; pricing; stochastic dynamic Bellman Optimization Principle; switch options

Internet of Things and Their Coming Perspectives: A Real Options Approach

Internet of things is developing at a dizzying rate, and companies are forced to implement it in order to maintain their operational efficiency. The high flexibility inherent to these technologies makes it necessary to apply an appropriate measure, which properly assesses risks and rewards. Real options methodology is available as a tool which fits the conditions, both economic and strategic, under which investment in internet of things technologies is developed. The contribution of this paper is twofold. On the one hand, it offers an adequate tool to assess the strategic value of investment in internet of things technologies. On the other hand, it tries to raise awareness among managers of internet of things technologies because of their potential to contribute to economic and social progress. The results of the research described in this paper highlight the importance of taking action as quickly as possible if companies want to obtain the best possible performance. In order to enhance the understanding of internet of things technologies investment, this paper provides a methodology to assess the implementation of internet of things technologies by using the real options approach; in particular, the option to expand has been proposed for use in the decision-making process

Valuation and investment of generation assets

The re-regulation of electric power industry around the world has raised many new challenges for all stakeholders. This research is to valuate generation assets within re-regulated electricity markets, both in short-term and long-term. The focus is to valuate operation flexibility under market uncertainties from the viewpoint of a Generation Company (GENCO);This research proposes to model the movements of electricity markets with Hidden Markov Model (HMM) driven by underlying market forces. An electricity market is modeled as a dynamic system evolving over time according to Markov processes. At any time interval, the electricity market can be in one state and transit to another state in the next time interval. The true market states are hidden from a market participant behind the incomplete observation. The observations, such as market-clearing price and quantity, are modeled to follow multiple probabilistic distributions;This research proposes to further decompose the market forces into physical and economic drivers if a specific electricity market employs Location Marginal Price (LMP) mechanism. The physical drivers include transmission network topology and generation technology. The economic drivers include fuel prices, demand uncertainties, and profit maximization of market participants with incomplete information. The decomposition captures the strengths of engineering-based production cost approach and mark-to-market stochastic approach;This research valuates generation assets with real option analysis. The value of generation assets is maximized based on the Hidden Markov Model (HMM) and newest observation of electricity markets. Such an optimization problem is formulated as Partially Oberserable Markov Decision Problem (POMDP). The solution of a POMDP provides a GENCO both the optimal operating policy and values of generation assets. The value of perfect and imperfect information is also identified;Investment in generation assets is also analyzed with real option. This research incorporates fuzzy sets and numbers to capture the fuzziness and possibilities of long-term electricity markets movements. Fuzzy sets and numbers provide the modeler flexibilities to incorporate subjective judgments when rigorous approaches are not feasible. The real call options, capturing the investment value of generation assets, are formulated as Markov Decision Process (MDP) and solved with fuzzy linear programming

A fuzzy real option approach for investment project valuation

[[abstract]]The main purpose of this paper is to propose a fuzzy approach for investment project valuation in uncertain environments from the aspect of real options. The traditional approaches to project valuation are based on discounted cash flows (DCF) analysis which provides measures like net present value (NPV) and internal rate of return (IRR). However, DCF-based approaches exhibit two major pitfalls. One is that DCF parameters such as cash flows cannot be estimated precisely in the uncertain decision making environments. The other one is that the values of managerial flexibilities in investment projects cannot be exactly revealed through DCF analysis. Both of them would entail improper results on strategic investment projects valuation. Therefore, this paper proposes a fuzzy binomial approach that can be used in project valuation under uncertainty. The proposed approach also reveals the value of flexibilities embedded in the project. Furthermore, this paper provides a method to compute the mean value of a project’s fuzzy expanded NPV that represents the entire value of project. Finally, we use the approach to practically evaluate a project.[[incitationindex]]SCI[[booktype]]紙

COG-FPOM: adapted fuzzy pay-off method for real options valuation: application in the abandonment decision of petroleum producing fields

This paper presents the COG-FPOM, a model based on the Fuzzy Pay-Off Method (FPOM). The FPOM is a scenario-based real option valuation method that uses fuzzy numbers as possibility distributions. The paper shows an unexpected result generated by the original FPOM, in which the real option would have a negative value. It further analyses its reasons and suggests a way to overcome it, by using the center of gravity (COG) instead of the possibilistic mean to summarize a fuzzy number. The overall work is an ongoing project that aims to apply the presented model to support the abandonment decision of petroleum producing fields – an initial attempt together with its preliminary outcomes are shown here. Although not concluded, the COG-FPOM and its pilot results indicate a good potential for the sequence of the project

The Design of Financial Systems: Towards a Synthesis of Function and Structure

This paper proposes a functional approach to designing and managing the financial systems of countries, regions, firms, households, and other entities. It is a synthesis of the neoclassical, neo-institutional, and behavioral perspectives. Neoclassical theory is an ideal driver to link science and global practice in finance because its prescriptions are robust across time and geopolitical borders. By itself, however, neoclassical theory provides little prescription or prediction of the institutional structure of financial systems that is, the specific kinds of financial intermediaries, markets, and regulatory bodies that will or should evolve in response to underlying changes in technology, politics, demographics, and cultural norms. The neoclassical model therefore offers important, but incomplete, guidance to decision makers seeking to understand and manage the process of institutional change. In accomplishing this task, the neo-institutional and behavioral perspectives can be very useful. In this proposed synthesis of the three approaches, functional and structural finance (FSF), institutional structure is endogenous. When particular transaction costs or behavioral patterns produce large departures from the predictions of the ideal frictionless' neoclassical equilibrium for a given institutional structure, new institutions tend to develop that partially offset the resulting inefficiencies. In the longer run, after institutional structures have had time to fully develop, the predictions of the neoclassical model will be approximately valid for asset prices and resource allocations. Through a series of examples, the paper sets out the reasoning behind the FSF synthesis and illustrates its application.