Applying real options analysis to assess cleaner energy development strategies

Cheng, Ching-Tsung; Lo, Shang‐Lien; Lin, Tyrone T.

doi:10.1016/j.enpol.2011.06.048

Cited by 18 publications

(14 citation statements)

References 20 publications

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“…In addition to the Teisberg (1993) study, ROA is employed to evaluate solar-and wind-energy projects (Lee and Shih, 2010;Lima et al, 2013;Monjas-Barroso and Balibrea-Inlasta, 2013;Muñoz et al, 2009), paper mill cogeneration (Costantino et al, 2012), conversion of cropland for energy crops (Gazheli and Di Corato, 2013;Song et al, 2011), investment decisions among combined-cycle (steam and gas) power plants, coal-fired, and nuclear plants (Bednyagin and Gnansounou, 2011;Zambujal-Oliveira, 2013), clean-energy mix policy (Cheng et al, 2011), staged commercialization of alternative energy technologies (Siddiqui and Fleten, 2010), and investment strategies of energy-saving equipment Huang, 2010, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Co-firing coal with wood pellets for U.S. electricity generation: A real options analysis

et al. 2015

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Section: Literature Reviewmentioning

confidence: 99%

Co-firing coal with wood pellets for U.S. electricity generation: A real options analysis

et al. 2015

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“…Let r denote the risk-adjusted discounted rate (Lin 2009;Lin and Huang 2011), complying with the natural constraints of u > 1 + r > d. The possible growth path of risk-adjusted probability is p = (e n×r − d) ÷ (u − d) (Copeland and Antikarov 2001); the decline path of risk-adjusted probability is 1 − p (0 ≤ p ≤ 1). This paper shows the GDP change path, the relevant path ratio distribution, and the corresponding GDP nodes of each time frame as shown in Figure 1 (Copeland and Antikarov 2001;Cheng et al 2011):…”

Section: Assumptionsmentioning

confidence: 99%

“…This study utilizes the compound binomial options model (Copeland and Antikarov 2001;Cheng et al 2011) and the three stages of the product life cycle characteristics: introductory, growth, and maturity. For the sustainable operation of the product, each stage requires innovation cost investments: product innovation, manufacturing innovation, and business innovation.…”

Section: Compound Binomial Optionsmentioning

confidence: 99%

“…This study reported that phase-specific volatilities can be estimated for project managers. Cheng et al (2011) used the binomial model approach, which was modified from sequential compound options, to analyze future GDP changes based on past historical data, their resulting impact on electricity demand, and their influences on the development path of clean energy investment strategies. Liu et al (2018) adopted the pricing of n-fold compound options with barriers.…”

Section: Introductionmentioning

confidence: 99%

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Optimum Technology Product Life Cycle Technology Innovation Investment-Using Compound Binomial Options

Lin

Zeng

2018

Risks

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The study considers the product life cycle in the stages of technological innovation, and focuses on how to evaluate the optimal investment strategy and the project value. It applies different product stages (three stages including production innovation, manufacture innovation, and business innovation) factors to different risks to build a technology innovation strategy model. This study of option premiums aims for the best strategy timing for each innovation stage. It shows that the variation of business cycle will affect the purchasing power under the uncertainty of Gross Domestic Product (GDP). In application, the compound binomial options for the manufacture innovation will only be considered after the execution of the production innovation, whereas the operation innovation will only be considered after the execution of the manufacture innovation. Thus, this paper constructs the dynamic investment sequential decision model, assesses the feasibility of an investment strategy, and makes a decision on the appropriate project value and option premiums for each stage under the possible change of GDP. Numerically, the result shows the equity value of the investment is greater than 0. Therefore, this paper recommends the case firm to invest in its innovation project known as one-time passwords. Sensitivity analysis shows when the risk-adjusted discounted rate r increases, the risk of the investment market increases accordingly, hence the equity value must also be higher in order to attract the case firm’s investment interest. Also, the average GDP growth rate u sensitivity analysis results in different phenomena. The equity value gradually decreases when the average GDP growth rate rises. When the average GDP growth rate u rises to a certain extent, however, its equity value is gradually growing. The study investigates the product life cycle innovation investment topic by using the compound binomial options method and therefore provide a more flexible strategy decision compared with other trend forecast criteria.

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“…Siddiqui et al (2006) describe an approach to determine the option value of research, development, demonstration and deployment programmes on renewable energy technology. Cheng et al (2011) present a modified binomial lattice model to apply compound options to create a flexible management approach to decide clean energy strategies that are embedded with a lead time. Locatelli et al (2016b) apply compound options to energy storage plants.…”

Section: Ros In the Energy Sectormentioning

confidence: 99%

Appraisal of small modular nuclear reactors with ‘real options’ valuation

Locatelli

Pecoraro

Meroni³

et al. 2017

Proceedings of the Institution of Civil Engineers - Energy

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2 3 4Small modular nuclear reactors have the advantage of flexibility in deployment and shorter construction time compared with large reactors. Investment appraisals in the energy sector are traditionally based on discounted cash flow, but this tends to underestimate the value of management flexibility during the decision-making process. The 'real options' valuation method can better support an investment appraisal. This paper, leveraging the real options approach, gives an account of two key strategic aspects to support the decision-making process in building small modular reactors: the time to market with the relative stage-gate process and the effect of a new plant on the existing portfolio. This paper assesses small modular reactors against other base-load power plants and, once applied to the UK scenario, it shows the superior performance of small modular reactors.differential coefficient' of a linear exercise threshold dp differential price dz differential Wiener process e Euler's number E expected ECTC t expected cost to complete the construction at time t ECTC threshold expected cost to complete the construction threshold ECTD t expected cost to complete the design at time t ECTD threshold expected cost to complete the design threshold G* gas price triggering the investment G 0 gas price at the time now G t gas price at time t I is the investment rate K remaining cost,'multiplication factor' of a linear exercise threshold P* price triggering the investment P 0 price at the time now P LB lower bound price P lim price limit P SR sharpe ratio price

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Applying real options analysis to assess cleaner energy development strategies

Cited by 18 publications

References 20 publications

Co-firing coal with wood pellets for U.S. electricity generation: A real options analysis

Co-firing coal with wood pellets for U.S. electricity generation: A real options analysis

Optimum Technology Product Life Cycle Technology Innovation Investment-Using Compound Binomial Options

Appraisal of small modular nuclear reactors with ‘real options’ valuation

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