Optimal exit strategies for investment projects

Chevalier, Etienne; Vath, Vathana Ly; Roch, Alexandre F.; Scotti, Simone

doi:10.1016/j.jmaa.2014.12.029

Cited by 9 publications

(6 citation statements)

References 23 publications

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“…Ensuring final payments of wages to staff, handing over obligations, assuming liabilities, and reconciling legal issues related to asset ownership are among the many considerations that must be considered (Engels ; Chevalier et al . ). An exit strategy requires a predetermined agreement that specifies the roles, responsibilities, and burden of each stakeholder during the termination phase, and that establishes safeguards for the continued sustainability of the project.…”

Section: Why Exit Strategies Are Essential In Conservationmentioning

confidence: 97%

Exit strategies for wildlife conservation: why they are rare and why every institution needs one

Ruiz‐Miranda

Vilchis

Swaisgood

2020

Frontiers in Ecol & Environ

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Exit strategies – plans to end involvement in a project once selected criteria have been reached – are rare in conservation planning but can play a vital role in the conservation planning process; such strategies also prepare the institution, its staff, its partners, and a wider group of stakeholders for eventual success or failure and signal when it is time to move on. Exit strategies may indicate that the project has been terminated but may also signal success, or that project leadership has transitioned to another, more appropriate entity. We address why exit strategies are uncommon in conservation, why they are essential, what determines when to transition or leave, and how to plan for circumstances afterwards. A good exit strategy addresses financial and legal liabilities to employees, publication of results, and ownership of data, among other things. A comprehensive, thoughtful strategy can lead to “beautiful exits” that minimize negative consequences to the project.

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Section: Why Exit Strategies Are Essential In Conservationmentioning

confidence: 97%

Exit strategies for wildlife conservation: why they are rare and why every institution needs one

Ruiz‐Miranda

Vilchis

Swaisgood

2020

Frontiers in Ecol & Environ

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“…The stopping time optimizes the action value, as expressed in Eq. (14). Because the action value needs to represent the actual amplitude value, the coefficient γ and the transition probability value are set to 1.…”

Section: Downhill U-turn Around T Wavementioning

confidence: 99%

“…An algorithmic decision utilizing the stopping time optimizes reward as an output among stopping time values [13]. Research works have been conducted by involving stopping time on financial applications [13][14][15][16]. Another research work incorporated the stopping time to schedule an advertisement on live social media [17].…”

Section: Introductionmentioning

confidence: 99%

Myocardial infarction evaluation from stopping time decision toward interoperable algorithmic states in reinforcement learning

Park

Hwang

Shin

et al. 2020

BMC Med Inform Decis Mak

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Background: The Elliot wave principle commonly characterizes the impulsive and corrective wave trends for both financial market trends and electrocardiograms. The impulsive wave trends of electrocardiograms can annotate several wave components of heartbeats including pathological heartbeat waveforms. The stopping time inquires which ordinal element satisfies the assumed mathematical condition within a numerical set. The proposed work constitutes several algorithmic states in reinforcement learning from the stopping time decision, which determines the impulsive wave trends. Each proposed algorithmic state is applicable to any relevant algorithmic state in reinforcement learning with fully numerical explanations. Because commercial electrocardiographs still misinterpret myocardial infarctions from extraordinary electrocardiograms, a novel algorithm needs to be developed to evaluate myocardial infarctions. Moreover, differential diagnosis for right ventricle infarction is required to contraindicate a medication such as nitroglycerin. Methods: The proposed work implements the stopping time theory to impulsive wave trend distribution. The searching process of the stopping time theory is equivalent to the actions toward algorithmic states in reinforcement learning. The state value from each algorithmic state represents the numerically deterministic annotated results from the impulsive wave trend distribution. The shape of the impulsive waveform is evaluated from the interoperable algorithmic states via least-firstpower approximation and approximate entropy. The annotated electrocardiograms from the impulsive wave trend distribution utilize a structure of neural networks to approximate the isoelectric baseline amplitude value of the electrocardiograms, and detect the conditions of myocardial infarction. The annotated results from the impulsive wave trend distribution consist of another reinforcement learning environment for the evaluation of impulsive waveform direction. Results: The accuracy to discern myocardial infarction was found to be 99.2754% for the data from the comma-separated value format files, and 99.3579% for those containing representative beats. The clinical dataset included 276 electrocardiograms from the comma-separated value files and 623 representative beats.

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“…where L is defined as in (6). Now, defining the vector w(t) = (u(t), u ′ (t)) T where the symbol T denotes the transpose, we may represent the ODE (26) as w ′ (t) = Aw(t) + b(t), where b :]0, ∞[→ R 2×1 is a vector function and A is a constant 2 × 2 matrix, defined as follows:…”

Section: Study Of the Odementioning

confidence: 99%

“…Since there are many other applitations of optimal stopping in financial mathematics, we refer to the alphabetically-ordered list of important contributions in this field: Arkin [3], Belomestny, Rüschendorf, and Urusov [4], Bronstein, Hughston, Pistorius and Zervos [5], Chevalier, Vath, Roch and Scotti [6], Dayanik [8], Dayanik and Egami [9], Dayanik and Karatzas [10], Décamps and Villeneuve [11], Johnson [21], Johnson…”

Section: Introductionmentioning

confidence: 99%

On a Class of Optimal Stopping Problems with Applications to Real Option Theory

Guerra¹,

Nunes²,

Oliveira³

2017

Preprint

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We consider an optimal stopping time problem related with many models found in real options problems. The main goal of this work is to bring for the field of real options, different and more realistic pay-off functions, and negative interest rates. Thus, we present analytical solutions for a wide class of pay-off functions, considering quite general assumptions over the model. Also, an extensive and general sensitivity analysis to the solutions, and an economic example which highlight the mathematical difficulties in the standard approaches, are provided.

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Optimal exit strategies for investment projects

Cited by 9 publications

References 23 publications

Exit strategies for wildlife conservation: why they are rare and why every institution needs one

Exit strategies for wildlife conservation: why they are rare and why every institution needs one

Myocardial infarction evaluation from stopping time decision toward interoperable algorithmic states in reinforcement learning

On a Class of Optimal Stopping Problems with Applications to Real Option Theory

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