Switching from oil to gas production in a depleting field

Støre, Kristian; Fleten, Stein–Erik; Hagspiel, Verena; Nunes, Cláudia

doi:10.1016/j.ejor.2018.05.043

Cited by 19 publications

(9 citation statements)

References 23 publications

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“…We set the production cost of EVs

c

to 85000, and due to the maturity of traditional FV production technology, we assume that the production cost of FVs

c_{0}

is 50,000. Following Comincioli et al (2021), we take into account that

r = 0.03

, and consistent with Støre et al (2018), we set

α_{1}, α_{2}, σ_{1}

, and

σ_{2}

to 0.004, 0.005, 0.338, and 0.267, respectively. For the parameters of the dual credit policy, according to the statistics of MIIT (2022), we consider that the credit value obtained for each new energy vehicle is 3, and the average negative fuel consumption credit

δ

is 2.…”

Section: Numerical Simulationmentioning

confidence: 97%

“…Based on the previous research and in conjunction with the theorem 1 ofStøre et al (2018), The option value in the postponed region can be derived by finding min be used to calculate the option value for a given FV demand and credit price (x 1 ,p v1 ) in the postponed region: (1) Substituting the provided (x 1 ,p v1 ) into Equation (26) and solving this equation with a numerical technique to determine the threshold p v1 * . (2) Determine A,β, and η using the solution for p v1 * in Equations (A2), (A4) and (25).…”

mentioning

confidence: 99%

“…examined the influence of oil and gas price uncertainty on investment and concluded that the option value in the postpone zone is determined by the switching threshold and the provided oil and gas price. Based on theorem 1 ofStøre et al (2018), the value function V x 1 , p v1 ð Þmust hold:…”

mentioning

confidence: 99%

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When to invest in electric vehicles under dual credit policy: A real options approach

et al. 2023

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This research aims to investigate traditional vehicle manufacturers' green technology investment theory under dual credit policy from the perspective of real options, overcoming earlier investigations of this issue that considered it only from a stability or single uncertainty perspective. An analytical real options model was first provided for traditional automaker investment. Then we solved the analytical solution for the electric vehicle investment threshold based on the uncertainty of credit price and fuel vehicle market scenarios. The optimal electric vehicle investment timing is demonstrated using numerical simulation. Results show that (1) when the fuel vehicle market demand falls to a certain level, automakers will choose to make electric vehicle investments regardless of how the credit price changes in the market; (2) the effect of volatility on the investment threshold depends on the covariance or correlation coefficient; (3) the numerical simulation results revealed that the credit price drift rate, risk‐free rate, correlation parameters, and electric vehicle production cost all have a positive impact on the electric vehicle investment region, whereas the drift rate of fuel vehicle and electric vehicle production cost have a negative impact. These results can be used to make theoretical conclusions about electric vehicle investments.

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“…We set the production cost of EVs

c

to 85000, and due to the maturity of traditional FV production technology, we assume that the production cost of FVs

c_{0}

is 50,000. Following Comincioli et al (2021), we take into account that

r = 0.03

, and consistent with Støre et al (2018), we set

α_{1}, α_{2}, σ_{1}

, and

σ_{2}

δ

is 2.…”

Section: Numerical Simulationmentioning

confidence: 97%

mentioning

confidence: 99%

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When to invest in electric vehicles under dual credit policy: A real options approach

et al. 2023

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“…Using the approach presented in Støre et al (2018) to solve this system, we found the explicit solution for the boundary 3 : b…”

Section: The Quasi-analytical Approachmentioning

confidence: 99%

“…Adkins and Paxson (2016) consider the optimal investment policy for an energy facility with price and quantity uncertainty under different subsidy schemes. Støre et al (2018) determine the optimal timing to switch from oil to gas production in the tail production phase, with the price of oil and gas following (correlated) Geometric Brownian motions. Finally, we refer to Heydari et al (2012), who extend the quasi-analytical approach proposed in Adkins and Paxson (2011b) to a three-factor model, which is employed to value the choice between two emission reduction technologies, assuming that the value of each option depends on fuel, electricity and CO 2 prices, all following (correlated) Geometric Brownian motions.…”

Section: Introductionmentioning

confidence: 99%

Investment Decisions with Two-Factor Uncertainty

Compernolle

Huisman

Kort

et al. 2021

JRFM

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This paper considers investment problems in real options with non-homogeneous two-factor uncertainty. We derive some analytical properties of the resulting optimal stopping problem and present a finite difference algorithm to approximate the firm’s value function and optimal exercise boundary. An important message in our paper is that the frequently applied quasi-analytical approach underestimates the impact of uncertainty. This is caused by the fact that the quasi-analytical solution does not satisfy the partial differential equation that governs the value function. As a result, the quasi-analytical approach may wrongly advise to invest in a substantial part of the state space.

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