Option Valuation Method Research Articles

Practical possibilistic fuzzy pay-off method for real option valuation

This paper describes a set of proposed additions to the recently introduced possibilistic fuzzy pay-off method for real option valuation that enhances the practical usability of the method. The additions are focused on the practical usability of the method and concentrate on emphasizing the consideration of the downside-risk found in projects. Technically the additions are based on using a novel interpretation of the possibilistic mean as a proxy respectively for the weight of the downside and the upside of a possibility distribution in the context of project profitability. This interpretation of the possibilistic mean is a new theoretical contribution.The proposed new method-variant, called the “practical possibilistic fuzzy pay-off method for real option valuation”, can effectively distinguish between projects with an identical upside and non-identical downsides and allows for a more finance-theoretically comprehensive consideration of situations, where the circumstances surrounding the downside risk of a project change. Changes in the downside are reflected in the real option value. The proposed changes constitute the first variant of the possibilistic fuzzy pay-off method for real option valuation and they remarkably increase the practical usability of the method.

부동산 임대료의 현금 흐름에 대한 리스크 분석

Investment decisions in real estate development projects need to be made more flexibly in uncertain environmental changes such as legal and economic conditions in competitive business in the rapidly changing real estate market. In analyzing the economic feasibility of real estate development projects, the valuation method of the investment plans using the traditional NPV method is evaluated based on a fixed standard planned in advance. Therefore, it was not possible to flexibly cope with uncertain changes in the business environment. In the face of growing uncertainty in the real estate development market, a more sophisticated evaluation method that can evaluate investment plans is needed according to changes in the market. Accordingly, the valuation of real estate development projects was analyzed using real options approach. In this study, an analytical framework was presented to evaluate the return value of commercial rental properties from a financial engineering perspective and to analyze the risk of rent cash flows. Real estate rate assessment methods, risk analysis methods, rent derivatives valuation methods, and real estate option valuation methods were analyzed for uncertainty in rent, tenant residence, vacancy, and real estate price using Monte Carlo simulation. In terms of financial engineering probability models, research in the field of valuation and risk analysis of real estate is now in its infancy, and the framework for analysis itself is not sufficiently established. Based on these studies, various analysis methods will be developed, and in this sense, this study can play a fundamental role.

Solar Energy Investment Valuation With Intuitionistic Fuzzy Trinomial Lattice Real Option Model

Under the uncertain and the flexibility required conditions, the conventional capital budgeting techniques are insufficient to decide the most feasible investment due to their static nature. Classical real option valuation techniques have been used for various investment options such as deferment and abandonment. Although these techniques help to evaluate the projects in uncertain environments, they still follow the static, certain Boolean logic assumptions. Therefore, further improvement in the real option valuation has been introduced with the usage of fuzzy logic. Fuzzy logic is applied by binomial and Black–Scholes real option valuation methods up to date, but not with the trinomial lattice. Moreover, Types-1 and 2 fuzzy numbers are used; however, the intuitionistic fuzzy numbers are not analyzed in detail in the real option valuation. In this article, we propose an intuitionistic fuzzy trinomial lattice real option valuation model for a solar energy investment project. While valuing the deferment option, expert opinions, two different volatility methods, and a tailor-made electricity price-forecasting model are used. According to our results, the deferment option is valuable and delaying the start of the project provides a much higher expanded net present value than an immediate start. The contribution of this article is that the uncertainty in the real option valuation is modeled from a broader perspective with intuitionistic fuzzy numbers by taking the hesitancy of the decision-maker and the market into account. Consequently, the proposed method would increase the accuracy of the real option valuation in uncertain environments such as renewable energy sector.

A Neural Network Model for Digitizing Enterprise Carbon Assets Based on Multimodal Knowledge Mapping.

In this paper, a multimodal knowledge mapping approach is used to digitize enterprise carbon assets, and a corresponding neural network model is designed for use in the practical process. Rich textual entity labels associated with images are obtained using an entity annotation system. A topology-based data fusion method is also designed based on the hierarchical relationship between WordNet and DBpedia to fuse the knowledge obtained from image visualization and text description mining. Existing neural network-based entity linking methods ignore the semantic gap between the context of sequential entity denotative items and the context of graph-structured entities, thus affecting the accuracy of entity linking. It is observed that the importance of words in the context of entity denotative items is different, and the importance of content in the entity context is also different. To solve the above problems, this paper proposes an entity linking method that combines a common attention mechanism with a graph convolutional neural network. Secondly, based on the basic theory of value assessment, the characteristics of classical asset valuation methods and their inapplicability to the valuation of carbon assets are analyzed, and thus the real option valuation method and its two classical models are introduced; after demonstrating the real option characteristics of carbon assets of power enterprise projects, a real option model-based carbon asset valuation model for power enterprise projects is constructed and its applicability is verified with case studies. Through analyzing the current situation and problems of carbon asset valuation work in power enterprises, targeted practical suggestions are put forward to further strengthen and enhance the carbon asset valuation work in power enterprises in the future.

Valuation of Growth START-up: A New Approach By Drawing Analogies and Variations Among Existing Methods

The valuation of a budding start-up is a complex task for researchers, academicians, and practitioners because of its inherent nature of high growth potential and high risk, uncertainty. These characteristics of the startup make traditional valuation methods inappropriate for startup valuation. Without comprehensive assimilation of business models and underlying value drivers at every stage, the process of valuation can become an unrealistic and difficult task. In this context, the current study elucidates various valuation methods and their appropriateness in start-ups with the help of a literature review. Different types of valuation methods of growing start-ups were compiled from established research literature and focus was given to valuation methods like DCF method, Venture Capital Method, Revenue multiple methods, Real options valuation method, binomial tree structure, and First Chicago method. Secondly, the possible methods of modifying the assumptions of these models are proposed in this study to improve the accuracy of valuation. Finally, this study also identifies the significance of the supplementary role of non-financial information in the valuation process.

Income approach to technology valuation for innovations

Until now, technology valuation has been dominated by the income approach, a forward-looking methodology that discounts future cash flow. To account for risk in technology valuation of innovations, a typical net present value (NPV) method is complemented with real option valuation method. Even though real option techniques account for risk changes in practice, such models are subject to criticism for reasons of mathematical complexity. We propose a modified income approach we refer to as 'Innotech' that incorporates innovation characteristics and industry characteristics into the valuation model. Our modified approach for the valuation of innovative technology reduces challenges related to mathematical modelling and dependency on factors such as risk premium, expected cash flows and contributory charge.

Inventory strategy development under supply disruption risk

This paper proposes a multi-period decision-making framework that enables procurement managers to develop an optimal supply inventory strategy under uncertain supply conditions. The framework draws on financial options valuation techniques by adopting the view of a procurement manager facing several uncertainties, while seeking to maximise its profit by exercising its flexibility to procure supplies and use inventories. Given the multitude of uncertain variables influencing inventory management decision in practice, the model is developed to remain robust to the inclusion of several underlying stochastic variables; it uses an American options valuation method and a least squares Monte Carlo simulation technique to solve the underlying dynamic programming problem. To demonstrate the application of the developed framework, a case study is presented based on data from a dairy supply chain. The case study explores the decision problem in several scenarios, showing how a decision-maker’s perception of product demand and supply price uncertainties, expectations over the timing of a supply disruption, discount rate, price shocks and disruption duration can be suitably incorporated into the decision-making framework.

Value Maximizing Decisions in the Real Estate Market: Real Options Valuation Approach

The real estate market of EU countries has undergone a severe global financial crisis 2008–2009, recovered successfully later, and now experiencing significant uncertainty due to the COVID-19 pandemic event. Significant volatility of the real estate business is once again evident, just as it was following the global financial crisis. The paper aims to provide a case study of a real estate project by giving insight into the Latvian real estate project that had been experiencing similar economic uncertainty, to demonstrate hybrid real options valuation (ROV) method to adapt real estate investments to changing circumstances and to develop the decision-making solution to similar EU real estate problems during the pandemic. The paper provides the “step-by-step” ROV application’s methodology in real estate development projects. The presented methodology is a powerful managerial risk management tool for the executives of similar real estate development projects in the EU countries struggling to make investment decisions in the pandemic and post-pandemic period. Since any estimation includes assumptions, ROV results should be interpreted and perceived as approximations only. The future works can provide robust ROV analyses and interpretations regarding the demand for real estate, showing quantitatively how competition can impact strategic investment decisions.

Intellectual property valuation: developing a model for patent valuation

With the growing knowledge of economics, the role of intellectual property in the development of international businesses and the boom of the national economy has become increasingly pronounced. There are many items on the intellectual property list, but the patent may be the most important intellectual property. Patent rights that bring patent owner immunity are very valuable. These licenses have been tradable in certain markets, like many other economic markets, and one of the concerns of technology researchers has always been to calculate the value of patents and to decide whether or not to buy them. The present study has developed a system for patent valuation. In the first step, the decision to invest or not invest in intellectual property (policy making) is examined using Ohlsen's model. In the second step, the patent valuation is done by using the real option valuation methods. Implementation of Ohlsen's model in companies listed on the Tehran Stock Exchange has highlighted the importance of advertising as one of the customer-centric intellectual property of the share price. in second step, a patent is valued in terms of the option to assign and simulate future patent cash flows using the average return process.

Real option valuation methods: application in the football sector

Real option valuation methods: application in the football sector

Real option valuation methods: application in the football sector

Real option valuation methods: application in the football sector

The value of flexibility in mitigating supply chain transportation risks

This paper investigates the value of the flexibility created by the transportation options in mitigating supply chain transportation risks. We accomplish this aim by developing an innovative computational model which uses the Real Option Valuation method to model the inner flexibility mechanism of the transportation options to choose between the Safety Net carrier and the spot market carrier on the basis of the actual conditions of the spot market (price, service level, and required transportation capacity), which is the foundation of the mitigation capability of transportation options. Through the case of a real supply chain of a large Fortune 100 multinational leader in the Fast Mover Consumer Goods (FMCG) industry, we also investigate the implications of a transportation options response in case of several sources of uncertainties, namely transportation capacity shortage, price volatility and service level reliability. Findings of the application support the understanding of which conditions increase the value of flexibility of the transportation options and how much flexibility is attractive given the initial sunk cost to acquire it.

Possibilistic fuzzy pay-off method for real option valuation with application to research and development investment analysis

This paper presents the first fully possibilistic method for real option valuation of investment projects, a new possibilistic variant of the fuzzy pay-off method for real option valuation. The new variant is derived by using the Luukka-Stoklasa-Collan transformation and is proven to be consistent with financial theory. The new variant is comparatively analyzed with the original method and the previously presented probabilistic variant. Fast computation formulae for the new variant in all use-cases in the triangular context are presented and complete fast computation formulae also for the previously presented probabilistic variant of the method are presented for the first time. The use of the new variant is illustrated with a set of numerical examples including examples of Research and Development investment analysis.

Construction material supply risk management using Asian option contracts: the case of a pipeline project

PurposeSteel price uncertainty exposes pipeline projects that are inherently capital intensive to the risk of cost overruns. The current study proposes a hedging methodology for tackling steel pipeline price risk by deploying Asian option contracts that address the shortcomings of current risk mitigation strategies.Design/methodology/approachA stepwise methodology is introduced, which uses a closed-form formula as an Asian option valuation method for calculating this total expenditure. The scenario analysis of three price trends examines whether or not the approach is beneficial to users. The sensitivity analysis then has been conducted using the financial option Greeks to assess the effects of changes in volatility in the total price of the option contracts. The total price of the Asian options was then compared with those of the European and American options.FindingsThe results demonstrate that the Asian option expenditure was about 1.87% of the total cost of the case study project. The scenario analysis revealed that, except for when the price followed a continuous downward pattern, the use of this type of financial instrument is a practical approach for steel pipeline price risk management.Practical implicationsThis approach is founded on a well-established financial options theory and elucidates how pipeline project participants can deploy Asian option contracts to safeguard against steel price fluctuations in practice.Originality/valueAlthough the literature exists about the theory and application of financial derivative instruments for risk management in other sectors, their application to the construction industry is infrequent. In the proposed methodology, all participants involved in fixed price pipeline projects readily surmount the risk of exposure to material price fluctuations.

Stochastic-dynamic modelling of farm-level investments under uncertainty

In the light of uncertainties, high initial costs, and temporal managerial flexibility, the real options approach has gained interest as a valuation tool for different types of natural resources management problems. Yet, neither real options valuation method excels under consideration of variability of resource endowments, returns-to-scale and predefined sizes of options. We fill the methodological gap by developing a method based on Monte Carlo simulation, scenario tree reduction, and stochastic programming that is advantageous for valuing real options where timing, scale and interactions among constraints and alternatives matter. The method advances in straightforward conversion of deterministic programming applications based on the classical net present value approach into a real options framework, and in introducing complexity into existing real options models. We illustrate the method with a case study featuring investment options regarding the adoption, coppicing, and conversion of perennial biomass energy production systems.

Valuation of defer and relocation options in photovoltaic generation investments by a stochastic simulation-based method

Risk management is crucial when committing investments in electricity markets. Investment projects for the generation of electricity are capital-intensive, in large part irreversible and future performance is subject to high uncertainty. Fortunately, most power generation projects have strategic flexibility for handling uncertainty and for mitigating risks under unfavorable scenarios. Modern corporate finance recognizes Real Option analysis (ROA) as the correct way to value investment projects with these characteristics. Due to both, environmental concerns and escalation of fuel prices, electricity generation from renewable sources has grown dramatically worldwide over the last decade. Renewable investment projects share many of the features mentioned. As such, option valuation methods should be applied to estimate the monetary value of flexibility in renewable energy investments. This work presents an appropriate methodology for assessing the economic value of a photovoltaic power plant under uncertainties. ROA is applied to determine the value of delaying the investment decision while waiting for better market information that would reduce acquisition costs due to progress in solar technology. The flexibility of relocating the solar facility in the future upon the appearance of a more attractive site in terms of cost, network accessibility or regulatory policies is also valued. The problem of option valuation is solved through stochastic simulation combined with recursive approximate dynamic programming techniques. The methodology developed might be used by investors for more efficient decision-making and by regulatory agencies for designing adequate support policies that encourage investment in renewable energy generation.

Real options valuation of photovoltaic power investments in existing buildings

Renewable power generation based on solar energy is deemed to be a key instrument to reduce the carbon footprint of modern economies. Collectively, buildings are an energy-intensive consumption sector. Therefore, existing building rooftops are seen as a target for massively deploying photovoltaic (PV) distributed generation. Nevertheless, estimating the benefits and risks of investing in rooftop PV systems is indeed a challenging task due to the large uncertainties that affect tariffs, technology costs, and regulatory policy. After reviewing the literature and identifying the current gaps, this article develops a method based on Real Options theory for appraising investments in PV generation systems to be installed on the rooftop of existing buildings. The option value of differing the investment decision and the problem of the optimal time to invest in irreversible PV assets are addressed by an advanced valuation method based on stochastic simulation, linear regression, and backward dynamic programming. In this work, returns of self-generation PV investments are subjected to uncertainties upon declining investment costs and fluctuating electricity tariffs, which are represented by appropriate exogenous stochastic processes. In order to test the practicability of the proposed decision-making framework, the valuation of an exemplary rooftop PV-system in a government building is considered. Results show that while standard appraisal methods wrongly reject the rooftop PV project now and in the future, the option valuation method finds optimal to hold the opportunity open in order to reconsider to invest later. In addition, the method provides an objective value of the opportunity cost of using the building rooftop for another purpose. The proposed valuation approach would result in better investment allocation and faster development of distributed PV power capacity contributing thereby to enhance the sustainability of current energy systems.

Investment valuation of natural tourist attractions under the uncertainty of multiple unexpected events: an ROV method

ABSTRACT This study applies the real options valuation (ROV) method with a jump process to consider the uncertainty of multiple unexpected events (UEs) when building investment valuation models for natural tourist attractions (NTAs). Unlike previous studies, this investigation considers multiple UEs from a pre-events, micro-level perspective. In considering both homogeneous and heterogeneous UE scenarios, certain conclusions can be drawn, so long as the project value of an NTA is known. In assessing diverse scenarios, it can be generally predicted that the greater the UE effects, the higher the degree of uncertainty; also, the more extensive the damage caused by UEs and the more frequent their occurrence, the greater the expense of an investment opportunity, and the longer the wait until the optimal time for investment. In assessing both homogeneous and heterogeneous UE scenarios, this study finds that investments should be valued differently under each type of scenario. In determining the optimal time to invest in NTAs that face differing types of UEs, strategic delay is found to be advantageous in many cases.

Model risk in real option valuation

We introduce a general decision-tree framework to value an option to invest/divest in a project, focusing on the model risk inherent in the assumptions made by standard real option valuation methods. We examine how real option values depend on the dynamics of project value and investment costs, the frequency of exercise opportunities, the size of the project relative to initial wealth, the investor’s risk tolerance (and how it changes with wealth) and several other choices about model structure. For instance, contrary to stylised facts from previous literature, real option values can actually decrease with the volatility of the underlying project value and increase with investment costs. And large projects can be more or less attractive than small projects (ceteris paribus) depending on the risk tolerance of the investor, how this changes with wealth, and the structure of costs to invest in the project.

A real option application for emission control measures

Real Option analyses are broadly discussed in economics and finance and different analytic and numeric calculation methods for option values have been presented and successfully implemented in theoretical case studies and practical applications. However, real option analysis has not yet been applied for mandatory investments without monetary revenues, e.g. investments in pollution reduction and emission control installations in large industrial plants enforced by political regulation. The assessment of the timing of the investment, i.e. whether to invest immediately or to delay the investment in the future, is the main scope of this work. A difficulty of the underlying type of investments with regard to option valuation is that not to invest is not an option. Therefore, the frequently applied optimal stopping approaches based on investment thresholds are not applicable to this work. In the first part of the paper, specific features and characteristics of the regarded investments are analyzed and translated into financial terms of option valuation, accompanied by an overview of several relevant option valuation methods. The most appropriate methodology for the application, the Monte-Carlo-Analysis, will be assessed in more detail. Based on a two perspectives approach that analyzes possible savings and losses of a delayed investment, a case study displays the calculations and results of the developed methodology in several scenarios. The case study reveals possible influences of policy schemes and the impact of the degree of uncertainty on mandatory investments. The work has a strong methodological focus and the calculation methodology provided can be of use for investors and policy-makers, particularly with regard to investment decision-making in the real options framework and the design of political instruments such as funding schemes.