Option Model Research Articles

“They gave us the right to choose.” A qualitative study of preferences for differentiated service delivery location among recipients of antiretroviral therapy at Lighthouse Trust in Lilongwe Malawi

Some differentiated service delivery (DSD) models for antiretroviral therapy (ART) allow stable recipients of care (RoC) to receive multi-month ART drug refills and complete rapid reviews in community sites. As DSD options expand across sub-Saharan Africa, RoC’s preferences and perspectives on community-based DSD versus clinic-based care models warrants attention. Lighthouse Trust (LT) implements DSD services for the Ministry of Health in Lilongwe, Malawi, including a community-based ART service delivery model that complements it traditional, clinic-based care. In this qualitative study, we explore reasons why RoC enrolled in LT clinics and eligible for DSD chose clinic-based ART services or a Nurse-led Community-based ART Program (NCAP) that reaches clients in established community peer support groups. We conducted eight focus group discussions (FGDs) among LT RoC: four FGDs among NCAP groups and four clinic-based FGDs (2 per setting) to explore opinions, preferences, and perceptions about ART service delivery. FGDs were recorded in Chichewa, translated and transcribed into English for thematic analysis. Findings were discussed with LT and NCAP teams to ensure results resonated with their personal experiences. Sixty-three participants took part in FGDs. Many findings were similar across care model. Across both NCAP and clinic FGDs, RoC were pleased with the care quality and appreciated the convenience of integrating their appointment visits at their chosen care model into their daily lives. Across FGDs, RoC also appreciated the quality of care, the respectful provider-to-patient interactions, and the attention to privacy at community and clinic sites. RoC in both clinic and NCAP care models expressed satisfaction with their chosen care model and preferred that choice over alternative options and locations, some noting their willingness to travel far to access LT’s high quality of clinic-based care. Privacy protection was an important consideration for choosing care models. At LT clinics, RoC highlighted the importance of physical separation between LT’s HIV-specific service site and other care services. In NCAP, RoC expressed that their choice of care model was reinforced by the sense of mutual support they received through NCAP peer support. These findings suggest the importance of offering personal choice to RoC on care model and selection of DSD options to support their ongoing engagement in care.

Осесимметричная задача фильтрации газа в пороупругой среде

The formulation and solution of the problem of burying carbon dioxide (carbon dioxide) in a poroelastic medium are considered. The model is based on the equations describing the filtration of liquids or gases in deformable porous media, which are a generalization of Muskett Leverett's models of poroelastic media. The assumption that the speed of movement of the solid skeleton of the medium is small made it possible to reduce the system of constitutive equations to two equations so that the effective pressure and porosity can be found. The gas filtration area refers to a rock formation in which an injection well is located at depth, and, on the sides, the formation is confined by impermeable rocks. The top of the formation coincides with the Earth surface and is permeable. The migration of carbon dioxide and its release to the surface occurs due to an increase in porosity at the top of the formation. Based on these assumptions, boundary conditions for the velocities of the gas and solid phases are set and then rewritten in terms of the desired function of the effective pressure of the medium. The resulting initial boundary value problem is solved numerically using a scheme of alternating directions and the fourth-order Runge-Kutta method. A difference scheme and an algorithm for solving the problem are given. The orders of uniform convergence in spatial and temporal variables were determined, and an approximate estimate for the rate of convergence of the numerical solution was obtained. Numerical modeling of several options for injecting carbon dioxide into the formation at different well depths and with different injection rates was carried out. Optimal gas injection conditions for its long-term geological storage were determined.

Solving the Black–Scholes European options model using the reduced differential transform method with powered modified log-payoff function

Solving the Black–Scholes European options model using the reduced differential transform method with powered modified log-payoff function

A Research on the Application of Option Pricing Strategy Framework Based on BS Model

This paper first reviews the development history of option modeling and its application in corporate strategy, providing a comprehensive background for understanding its evolution. It introduces the European option pricing model studied by scholars in the past, particularly focusing on the Black-Scholes (BS) model, a foundational tool in financial modeling. After establishing the research significance, this paper discusses several basic properties and influencing factors of the BS model while introducing real options as a dynamic framework for strategic decision-making. The core focus of this paper lies in the modification and adaptation of the BS model at the corporate strategy level. Specifically, it develops a combined model that integrates the BS real option method to address the limitations of traditional models, enhancing their applicability to complex business scenarios. Xinhua Wenxuan Company is employed as a case study to validate the feasibility of this refined model, providing a practical evaluation of its results. Lastly, this paper highlights the future research direction of this model, underlining its adaptability and potential for broader applications in corporate strategic management, particularly in industries characterized by high uncertainty and innovation.

Survive the economic downturn: Operating flexibility, productivity, and stock crash

AbstractOperating flexibility supports a firm's resilience strategy during challenging times by enabling them to promptly cut down operating costs associated with unproductive resources. We employ a real options model to formalize this insight. Our empirically grounding analytics motivate a firm‐level proxy for downscale operating flexibility (FLEX), which effectively captures the adjustment frictions across different contexts of firms' operations. Using U.S. data between 1961 and 2020, we show that operating flexibility mitigates the risk of stock price crashes, especially during periods of economic recession. Consistent with the loss‐curtailment mechanism, the operating flexibility effect is more pronounced for firms with lower productivity/profitability or higher operating leverage and is further amplified during longer and more severe recessions. Managers may avail themselves of our well‐tested empirical measure of operating flexibility to guide their efforts in building a more resilient operations structure.

An Option Pricing Formula for Active Hedging Under Logarithmic Investment Strategy

Classic options can no longer meet the diversified needs of investors; thus, it is of great significance to construct and price new options for enriching the financial market. This paper proposes a new option pricing model that integrates the logarithmic investment strategy with the classic Black–Scholes theory. Specifically, this paper focus on put options, introducing a threshold-based strategy whereby investors sell stocks when prices fall to a certain value. This approach mitigates losses from adverse price movements, enhancing risk management capabilities. After deriving an analytical solution, we utilized mathematical software to visualize the factors influencing new option prices in three-dimensional space. The findings suggest that the pricing of these new options is influenced not only by standard factors such as the underlying asset price, volatility, risk-free rate of interest, and time to expiration, but also by investment strategy parameters such as the investment strategy index, investment sensitivity, and holding ratios. Most importantly, the pricing of new put options is generally lower than that of classic options, with numerical simulations demonstrating that under optimal parameters the new options can achieve similar hedging effectiveness at approximately three-quarters the cost of standard options. These findings highlight the potential of logarithmic investment strategies as effective tools for risk management in volatile markets. To validate our theoretical model, numerical simulations using data from Shanghai 50 ETF options were used to confirm its accuracy, aligning well with theoretical predictions. The new option model proposed in this paper contributes to enhancing the efficiency of resource allocation in capital markets at a macro level, while at a micro level, it helps investors to apply investment strategies more flexibly and reduce decision-making errors.

The impact of tracking costs on real options

This article presents a real options model that explicitly takes into account the tracking costs required to follow the evolution of an investment opportunity. We find the impacts of tracking costs on investment timing are far from negligible. For typical parameter configurations, tracking costs lead to consequential corrections to the standard solution. In addition, the option to discard the investment opportunity becomes relevant. The impact of tracking costs on investments is more evident for low levels of volatility. In some cases, the optimal policy is similar to the Net Present Value rule.

Simulation of a New Well SAGD Configuration based on the example of an Oil Field in Kazakhstan

Steam-Assisted Gravity Drainage (SAGD) method is recognized as one of the most effective methods for the recovery of heavy oil and natural bitumen. This technology has received several modifications throughout its history designed to improve it. One of the promising modifications is the Single Well-SAGD (SW-SAGD), which allows significantly reducing the CAPEX for drilling a well. However, this method has several disadvantages such as steam breakthrough into the production part and the uneven development of the steam chamber along the well. This article presents the concept of a Single-Well Cyclic SAGD (SWC-SAGD), which allows preventing the breakthrough of the injected steam into the production section and the uniform development of the steam chamber along the well. The comparison analysis of the developed modification of SWC-SAGD was carried out using the classical method of 3D hydrodynamic modeling of both options using the example of one of the fields of the Republic of Kazakhstan. The results of the work show the efficiency of the proposed technology in terms of field oil total production.

Identifying the Relationship between Earnings and Prices

ABSTRACT The relationships between accounting earnings and stock prices, as well as between unexpected earnings and returns, have received substantial attention in the empirical literature. Several theoretical models predict the shapes of these relationships. However, a comprehensive empirical description that could be used to evaluate these predictions is lacking. By integrating recent advances in statistics and machine learning with findings in the accounting literature, we develop an empirical method to identify the relationships, which is consistent with the firm-specific and nonlinear features of the theoretical models. Our approach provides a clear description of stylized and robust patterns in the relationships that are relevant to distinguish between existing models and to aid future theory development. The findings are consistent with recently proposed dynamic option models for both the earnings-price and unexpected earnings-returns relationships. Data availability: Data are available from the public sources cited in the text. A summary of the R code used in the article is available in Starica and Marton (2024). JEL Classifications: G10; G30; M41.

Pricing blue carbon to promote the protection and restoration of the marine environment: A real option model

Pricing blue carbon will allow the monetization of the implicit carbon sequestration value of socioeconomic activities in marine ecosystems. This will empower those engaged in marine environment protection and restoration to reap economic benefits while imposing costs on those who harm the marine environment or carbon-emitting enterprises. This can significantly increase the enthusiasm of local governments, enterprises, and others for protecting and restoring the marine environment. However, owing to the characteristics of public goods and the externalities of blue carbon, it is difficult to price them through the supply and demand relationship of the traditional market. This paper focuses on how to price blue carbon under government policies and market uncertainties to encourage investors to engage in blue carbon projects involving the ecological protection and restoration of coastal wetlands. First, a universal blue carbon pricing model is established via the real option approach. The mangrove blue carbon project in Zhanjiang, Guangdong, was used as a case study to evaluate the price of mangrove blue carbon. This research provides technical support for the formation of blue carbon prices, and this method can be used not only to promote the protection and restoration of the marine environment but also to optimize the supply of blue carbon, fully leveraging its role in addressing climate change.

Evaluation of production line expansion efficiency using computer simulation

Abstract The article discusses the application of computer simulation in the optimization of production processes, particularly in the context of analyzing scenarios related to the addition of new production lines. The conducted research and simulations have shown that computer simulation is a key tool for precise modeling and analysis of various options, allowing for better understanding and optimization of production activities. The article presents the theoretical foundations of simulation along with practical examples of its application, focusing on assessing the impact of different production line configurations on the overall system’s efficiency. The analysis of benefits includes shortening the production cycle time, increasing flexibility, and improving operational efficiency. The challenges associated with implementing computer simulation, such as the need for specialized knowledge and the necessity for continuous updates of simulation models, are also discussed. Based on the research and analyses conducted, the article demonstrates that computer simulation is an effective tool supporting strategic and operational decision-making in production management, particularly in the context of expanding production infrastructure.

Insurer green financing for a supply chain under cap-and-trade regulation: a capped call contingent claim analysis

This paper introduces a contingent claim analysis to examine sustainable insurance practices. It investigates how life insurers participate in sustainable lending by financing borrowing firms committed to environmentally friendly practices for cleaner production. We establish a capped call option model, where the capped function explicitly considers credit risks associated with borrowing firms in a supply chain engaged in the cap-and-trade mechanism regulated by environmental policies. Our findings reveal that tightening the cap within the cap-and-trade system and reducing green loans can enhance insurer’s interest margins. Conversely, an escalation in the green input ratio across the supply chain may reduce these margins for the insurer. However, reducing low-margin insurance offerings could jeopardize the stability of insurance. The insurer faces financial challenges while supporting borrowing firms in their efforts toward carbon reduction and sustainable production. Notably, the substantial impact of climate change fueled by carbon emissions significantly influences the underwriting of life insurance policies related to human health. Policymakers need to navigate these intricacies to establish a careful balance between environmental objectives and the financial stability of sustainable insurance.

Identifying immunohistochemical biomarkers panel for non-small cell lung cancer in optimizing treatment and forecasting efficacy

BackgroundChemotherapy and immunotherapy for non-small-cell lung cancer (NSCLC) are gaining momentum. However, its long-term efficacy remains limited to only a small fraction of patients. Hence, it is crucial to identify reliable immunohistochemical biomarkers to facilitate the formulation of optimal treatment strategies and to predict therapeutic outcomes.MethodsWe retrospectively analyzed a cohort of 140 patients diagnosed with NSCLC who received chemotherapy or immunotherapy. Using bioinformatics analysis and machine learning techniques, we assessed the role of immunohistochemical biomarkers and clinical characteristics in developing a predictive model for treatment options and outcomes in this population.ResultsOur research has found that immunohistochemical biomarkers can accurately predict treatment regimens and progression-free survival in NSCLC patients with an accuracy rate of 82.1%. We identified an exclusive detection panel for the six vital biomarkers. Of particular note is the role of programmed cell death protein 1 ligand 1 (PD-L1) expression in guiding treatment selection, with high expression predicting better outcomes in the immunotherapy group at a cut-off value of 50%. Non-squamous patients who tested positive for thyroid transcription factor 1 had a longer median progression-free survival, while squamous patients who tested positive for p63 protein or cytokeratin 5/6 expression had a longer median progression-free survival.ConclusionsThe results of our study are highly encouraging, as they revealed a significant correlation between immunohistochemical biomarkers, therapeutic regimens, and prognosis. These findings indicate that our immunohistochemical detection panel has great potential for facilitating customization of therapeutic regimens to improve patient care. The insights gained from this study could help clinicians optimize treatment protocols and ultimately enhance clinical outcomes.

Wealth maximisation and residential energy-efficiency retrofits: Insights from a real options model

The slow adoption of residential energy-efficiency retrofits continues to hamper the energy transition. We study incentives for adoption by proposing a model of optimal investment under uncertainty where the wealth-maximising agent has the option to delay. Stochastic portfolio returns and energy prices are taken into account. An extension of the model where the energy carrier is switched, e.g. from gas to electricity, is also considered. Exercise boundaries for the optimal stopping problem are estimated numerically for recent case studies of German buildings. Investment is generally not optimal at current energy prices and market conditions. Increasing correlation between gas and electricity prices erodes the value of technology switching. Comparative statics reveal that energy-efficiency investments become optimal at relatively lower energy prices as wealth, income, and savings behaviour increase, and portfolio drift and volatility decrease. Consequently, incentive to invest in retrofits is far more heterogeneous along wealth dimensions than standard discounted cash flow analyses suggest. An examination of retrofit subsidies demonstrates how free-riding by wealthier agents occurs when subsidies are not appropriately targeted. We show that the pursuit of economic efficiency in subsidy design might have regressive effects on the wealth distribution.

Aligning common prosperity with sustainable development goals 3 and 7 through sustainable insurance

This paper develops a capped-call option model to evaluate sustainable insurance for achieving common prosperity. It integrates policyholder protection (Sustainable Development Goal 3 (SDG 3)) and the cap-and-trade mechanism (SDG 7) in modeling the Gini coefficient, thereby connecting SDGs 3 and 7 with common prosperity. The main findings are as follows. Life insurance policies that prioritize saving features enhance policyholder protection (SDG 3) but can detract from common prosperity. This impact is magnified when the regulatory cap within the cap-and-trade scheme for carbon-intensive manufacturers becomes stricter. High investment risks for carbon-intensive manufacturers reduce policyholder protection but support common prosperity. A stricter cap-and-trade scheme (SDG 7) also reduces policyholder protection and contradicts common prosperity. This paper avoids concluding any inherent inconsistency between the SDGs and common prosperity, as our analysis is based on the structure-conduct-performance paradigm rather than a macro perspective. Policymakers should carefully balance objectives between SDG 3 and common prosperity to ensure that policies promoting individual security do not compromise broader societal well-being and economic equality, as outlined by the SDGs.

Domestic and foreign cap-and-trade regulations, carbon tariffs, and product tariffs during international trade conflicts: A multiproduct cost-efficiency analysis

This paper develops a down-and-out call option model with structural breaks to examine the effects of domestic environmental policies on carbon-intensive firms amid international trade conflicts. The findings reveal that stricter cap-and-trade regulations, carbon tariffs, and product tariffs exacerbate pollutant-specific diseconomies of scale, limit economies of scope, and reduce firm equity. The positive impact on pollutant-specific diseconomies of scale leads to higher pollution, hindering progress toward Sustainable Development Goal 7 (SDG 7: Affordable and Clean Energy) from a multiproduct cost-efficiency perspective. Meanwhile, the negative impact on economies of scope results in fewer products and pollutants, aligning with SDG 7 but conflicting with Sustainable Development Goal 8 (SDG 8: Decent Work and Economic Growth), as the scope measure accounts for efficiency in both products and pollutants. Additionally, the negative impact on firm equity discourages progress toward both SDGs, especially during trade conflicts. In summary, environmental policies distinctly affect firm multiproduct cost efficiency and equity, particularly under varying trade conflict conditions.

Optimal timing of phasing out producer subsidies towards carbon neutrality: Interaction between fossil energy extraction and environmental uncertainties

Since subsidies for fossil-fuel producers entail “carbon locked-in” risks, phasing out the subsidies is widely agreed to be critical for progress on climate change towards carbon neutrality. However, due to the uncertainties and irreversibilities associated with environmental degradation and economic losses, delaying removal efforts allows us to benefit from cheaper abatement options and less total abatements owning to self-regeneration of pollution stock. Therefore, whether the removal action should be taken currently or be delayed becomes vital for policy making. We develop a real option model of policy timing using a green social welfare as the objective, consisting of the standard Hotelling model of exhaustible resource extraction, and a stochastic state variable to capture uncertainties over the social costs of environmental damage. Analytic solutions are derived to show the implication of these uncertainties for policy adoption, and the results are presented: (i) a higher volatility of economic costs per emissions leads to a positive incentive for delaying removal in some bounds of uncertainties; (ii) amount of subsidies, pollution stocks, depletion of fossil fuel production and its marginal costs have negative impacts on the timing threshold, which implies that adopting currently is better than waiting; and (iii) discount rate increases the option value of delaying the policy. Our study provides a valuable framework to determine the energy and environmental policy timing with uncertainties for regulators.

Offshore carbon storage from power plants based on real option and multi‐period source‐sink matching: A case study in the eastern coastal China

Carbon capture utilization and storage (CCUS) emerges as a pivotal strategy for CO2 reduction in the power sector, particularly focusing on the overlooked domain of offshore storage along China's east coast. In spite of the potential high costs, irreversible investments, and lengthy development, offshore storage can still be prospective. Considering autonomous decision-making among emission sources, this study pioneers a CO2 offshore storage investment decision model tailored for coal-fired and gas-fired power plants. Innovating an offshore storage source-sink matching model with a real options model and introducing a pipeline network optimization model allows a realistic source-sink matching strategy to be explored under optimal investment timing. According to the results, among 154 large stationary emission sources in Zhejiang Province, offshore storage could reduce CO2 emissions by 4.59 Gt, utilizing the Qiantang, Minjiang, and Fuzhou depressions. It is economically feasible to implement offshore storage with a whole-process unit cost of 368.8 CNY/tCO2, mainly dominated by capture costs. A hybrid carbon tax-subsidy policy promotes carbon reduction and economic benefits, offering a more effective incentive for emission sources to invest in offshore storage than a single policy. At a hybrid policy price of 250 CNY/tCO2, all 27 selected emission sources are projected to invest in offshore storage by 2048, with a preference for the Qiantang depression as the storage site. Practically, this study provides important technical support and guidance for the large-scale deployment of offshore storage.

Price optimization in supply chain agreements: a comparative analysis of buyback and put option contracts for inventory risk management

AbstractThis paper aims to provide a model of a supply chain in the integrated system and obtain its optimal decision variables. The paper introduces buyback and put option contracts to reduce inventory risk. These contracts were compared in three different cases via a numerical analysis approach. In the first case, the holding cost (h) of a retailer for surplus orders in the buyback contract is equal to the option price (o) in the put option model. The relationship between exercise price (e) in the put option model and buyback price (b) in the buyback contract was obtained by comparing the optimal values in the models. This study found that the exercise price in the put option contract will be greater than the buyback price. Furthermore, it is more likely that the retailer gave more benefits under the buyback agreement than the time the retailer chooses the put option contract. Therefore, it can be concluded that if the retailer chooses the buyback agreement in this situation, can gain more benefits. The study provides essential managerial insights to compare agreements and presents recommendations to choose a suitable contract.

Opracowanie konstrukcji świdra wiertniczego do zwiercania skał o różnych właściwościach mechanicznych

This paper presents a description of a bit design with a combined cutter layout, aimed at increasing the efficiency of breaking rocks with different mechanical properties. The results from industrial testing of the manufactured bits are analyzed, revealing the need to improve their hydraulic flushing system. Computer modeling was conducted using the Flow Simulation CAD/CAM package of the Solid Works system, where various models of the design options for the bit, the borehole bottom, and a segment of the drill string were created. For each variant, numerical calculations of the fluid motion were carried out using the finite element method. Based on the simulation results, optimal angles of inclination for the jet nozzles relative to the bit axis and their distance from this axis were determined. Key factors influencing the stability of the bit cutters, which destroy the rock by cutting with axial vibrations, were identified, and analytical dependencies for their predictive stability were derived. The wear rate of the bit cutters was determined by instantaneous values of such physical parameters as: the degree of wear, rock cutting speed, temperature, axial loading force on the cutter, and the friction coefficient at the contact between the cutter and rock. Temperature is especially impactful, reaching levels exceeding 1000°C in the cutting zone; it is often regarded as the primary factor influencing bit cutter stability. To maximize the efficiency of rock-breaking in the process of drilling wells, it is necessary to set the following vibration parameters: frequency, amplitude, and vibration mode, which can be determined from the results of mathematical modeling.