Recombining Trinomial Tree for Real Option Valuation with Changing Volatility

Haahtela, Tero

doi:10.2139/ssrn.1932411

Cited by 25 publications

(25 citation statements)

References 30 publications

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“…This problem results mainly -but not only -from volatility, which is, therefore, the most important parameter in flexibility and real options valuation (Haahtela 2010).…”

Section: Discussionmentioning

confidence: 99%

Hard coal project valuation based on real options approach: multiplicative vs. arithmetic stochastic process

Saługa¹,

Kamiński²

2016

Gospodarka Surowcami Mineralnymi

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Precise valuation of the economic efficiency of risky investment projects in the mineral sector has a direct impact on the range of future investments. Since the mid-90s, a number of enterprises have also been giving increased attention to the valuation of managerial flexibility that cannot normally be estimated with classical discounted cash flow (DCF) analysis. This has been the result of a development in the real options analysis (ROA) and the simplification of its algorithms, most of which have been achieved through: ♦ incorporating lattice models, ♦ introducing a single uncertain project parameter (gross present value, PV) as an underlying instrument, ♦ assuming that the underlying asset follows the multiplicative stochastic process, ♦ introducing the ‘marketed asset disclaimer’ (MAD) assumption. Unfortunately, in most cases, models constructed on the abovementioned assumptions and modifications are not consistent with real projects. Some analysts recognize that project PVs might not follow the multiplicative process, which could have a direct impact on the project’s value. In order to improve the MAD approach, the paper proposes a modified model where the multiplicative tree is replaced with an additive one. In addition, methods of ‘additive volatility’ calculation and ‘dividend’ adjustments were suggested.

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“…This problem results mainly -but not only -from volatility, which is, therefore, the most important parameter in flexibility and real options valuation (Haahtela 2010).…”

Section: Discussionmentioning

confidence: 99%

Hard coal project valuation based on real options approach: multiplicative vs. arithmetic stochastic process

Saługa¹,

Kamiński²

2016

Gospodarka Surowcami Mineralnymi

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“…The magnitude of u will be set to

σ_{UB} \sqrt{normalΔ t}

. (A similar scheme appears in Haahtela, albeit in a different context.) In summary,

u = σ_{UB} \sqrt{normalΔ t},

m = 0,

d = - σ_{UB} \sqrt{normalΔ t} .

Note that u is the grid spacing between adjacent horizontal grid lines.…”

Section: Trinomial LV Treementioning

confidence: 99%

Efficient trinomial trees for local‐volatility models in pricing double‐barrier options

Lok

Lyuu

2019

Journal of Futures Markets

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A local‐volatility (LV) model captures the volatility smile while retaining the preference freedom of the Black–Scholes model. Past attempts to construct a smile‐consistent tree for the LV surface do not guarantee validity. This paper presents an efficient and valid smile‐consistent tree for the LV model. The only assumption is that the LV surface be upper‐ and lower‐bounded. With this tree, double‐barrier options can be priced with fast convergence even in the presence of volatility smile. This is confirmed numerically. An implied tree is also presented. It recovers the LV surface reasonably well.

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“…We assume that the logarithm of the peak sales changes by σ √ ∆t during the time interval ∆t, which is applied to all regimes. Haahtela [37] suggested that σ should be between σ max and √ 1.5σ max , where…”

Section: Mean-reverting Binomial Lattice Model Under Markov Regime Swmentioning

confidence: 99%

R&D Project Valuation Considering Changes of Economic Environment: A Case of a Pharmaceutical R&D Project

Park

Shin

2018

Sustainability

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R&D project valuation is important for effective R&D portfolio management through decision making, related to the firm's R&D productivity, sustainable management. In particular, scholars have emphasized the necessities of capturing option value in R&D and developed methods of real option valuation. However, despite suggesting various real option models, there are few studies on simultaneously employing mean-reverting stochastic process and Markov regime switching to describe the evolution of cash flow and to reflect time-varying parameters resulting from changes of economic environment. Therefore, we suggest a mean-reverting binomial lattice model under Markov regime switching and apply it to evaluate clinical development with project cases of the pharmaceutical industry. This study finds that decision making can be different according to the regime condition, thus the suggested model can capture risks caused by the uncertainty of the economic environment, represented by regime switching. Further, this study simulates the model according to rate parameter from 0.00 to 1.00 and risk-free interest rates for regimes 1 and 2 from (r 1 = 4%, r 2 = 2%) to (r 1 = 7%, r 2 = 5%), and confirms the rigidity of the model. Therefore, in practice, the mean-reverting binomial lattice model under Markov regime switching proposed in this study for R&D project valuation contributes to assisting company R&D project managers make effective decision making considering current economic environment and future changes.

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Recombining Trinomial Tree for Real Option Valuation with Changing Volatility

Cited by 25 publications

References 30 publications

Hard coal project valuation based on real options approach: multiplicative vs. arithmetic stochastic process

Hard coal project valuation based on real options approach: multiplicative vs. arithmetic stochastic process

Efficient trinomial trees for local‐volatility models in pricing double‐barrier options

R&D Project Valuation Considering Changes of Economic Environment: A Case of a Pharmaceutical R&D Project

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