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This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

The purpose of this article is to propose a detailed methodology to estimate, model and incorporate the non-constant volatility onto a numerical tree scheme, to evaluate a real option, using a quadrinomial multiplicative recombination.

This article uses the multiplicative quadrinomial tree numerical method with non-constant volatility, based on stochastic differential equations of the GARCH-diffusion type to value real options when the volatility is stochastic.

Findings showed that in the proposed method with volatility tends to zero, the multiplicative binomial traditional method is a particular case, and results are comparable between these methodologies, as well as to the exact solution offered by the Black–Scholes model.

The originality of this paper lies in try to model the implicit (conditional) market volatility to assess, based on that, a real option using a quadrinomial tree, including into this valuation the stochastic volatility of the underlying asset. The main contribution is the formal derivation of a risk-neutral valuation as well as the market risk premium associated with volatility, verifying this condition via numerical test on simulated and real data, showing that our proposal is consistent with Black and Scholes formula and multiplicative binomial trees method.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

Much debate was brought forth during the South Korean credit card companies' liquidity crisis in 2003. This paper is an in-depth analysis of those credit card issuers' option embedded commercial paper (mentioned as ‘option CP’ henceforth). The main purpose of this paper is in evaluating the ‘option CP's fair value, with the decomposition and analysis on ‘option CP’.

Option CP is stipulated as a CP joined by an OTC credit derivative product. The structure is set so that anyone of the two options, put options and call options, will be executed.

Therefore, the price of option CP excluding the credit option portion will be equal to that of the standard coupon bond at the same maturity.

However, empirical evidence shows otherwise. The evidence clearly states that the option CP yield rates were generally quoted lower than the fair-value rates, even if option premium of credit option portion was included in calculating the value. This evidence has an implication that ‘option CP’s rates are generally issued and traded with unfair value. This paper has significance that it made valuation model of ‘option CP’ and evaluated its fairness, by way of the in-depth analysis of option CP which has not been before.

The authors combine options logic with transaction cost economics to explain why firms maintain, divest or buy out their international joint ventures (IJVs). It is suggested that a decline in environmental risk and higher partner-related risk makes a firm more likely to acquire an IJV but less likely to divest an IJV. The study also investigates how IJV age moderates the effects of a decline in environmental risk and higher partner-related risk.

The study employs competing risks analyses to examine the drivers of different termination outcomes using a dataset consisting of 459 IJVs in the People's Republic of China, of which 110 were either acquired or divested by their foreign parent.

The study finds that changes in environmental risk and partner-related risk affect how firms terminate their IJVs in the People's Republic of China. Specifically, the authors find that the effect of exogenous and endogenous risk are more pronounced for the acquisition of IJVs than for the divestment of IJVs.

The study contributes to international marketing research by complementing options logic with transaction cost economics to provide a theoretical explanation of the different ways in which IJVs in the People's Republic of China are terminated.

IJVs continue to be an important yet often unstable method to serve international markets. Our findings increase managers' awareness of the effect that two important sources of risk may have on the termination of IJVs in the People's Republic of China.

The study provides novel insights into the effect that changes in exogenous and endogenous risk have on a firm's choice of termination mode drawing on novel data on the different ways in which foreign firms have terminated their IJVs in the Peoples' Republic of China.

With the accelerated technological advancement, innovation has become a critical factor, which affects the core competitiveness of a company. However, studies about the relationship between internal stock option mechanisms and innovation productivity remain limited. Therefore, this paper aims to examine the impact of stock options and their elements design on innovation output from an internal mechanism perspective.

Using a sample of 302 stock option incentive plans announced and implemented between 2006 and 2016, this study uses the propensity score matching and difference-in-difference model to find out whether the implementation of stock options improves the innovation outputs of enterprises.

Based on the statistical analysis, it is concluded that: stock options can stimulate corporate innovation; a stock option may drive innovation outputs through two ways, performance-based incentives and risk-taking incentives, with the latter one playing a more dominant role and the risk-taking incentives of stock options, could be optimised when the non-executives granting proportion is larger, the granting range is limited, the incentive period is longer, the exercisable proportion is increasing, the price-to-strike ratio is lower and relatively loose performance assessment criteria are applied.

The conclusion reached in the study may provide valuable information to listed firms in designing and implementing the stock option plans.

This paper start from the question that value of right which is arose from real asset trade. First, organizing option portfolio using this right, then we investigate the correlation about real assets and contracted prices. The results are as follows. When a market is in equilibrium, the call-option value which is owned by seller is greater than the put-option value which is owned by buyer. As a result, present value of contract price is lower than the true value of the asset. Furthermore, this phenomenon is getting deepen when volatility of real estate is greater, expiration date is longer and interest rate is higher.

The purpose of this paper is to illustrate a profitable and original index options trading strategy.

The methodology is based on auto regressive integrated moving average (ARIMA) forecasting of the S&P 500 index and the strategy is tested on a large database of S&P 500 Composite index options and benchmarked to the generalized auto regressive conditional heteroscedastic (GARCH) model. The forecasts validate a set of criteria as follows: the first criterion checks if the forecasted index is greater or lower than the option strike price and the second criterion if the option premium is underpriced or overpriced. A buy or sell and hold strategy is finally implemented.

The paper demonstrates the valuable contribution of this option trading strategy when trading call and put index options. It especially demonstrates that the ARIMA forecasting method is a valid method for forecasting the S&P 500 Composite index and is superior to the GARCH model in the context of an application to index options trading.

The strategy was applied in the aftermath of the 2008 credit crisis over 60 months when the volatility index (VIX) was experiencing a downtrend. The strategy was successful with puts and calls traded on the USA market. The strategy may have a different outcome in a different economic and regional context.

This paper measures different market risk impacts on options portfolios under the new Fundamental Review of the Trading Book (FRTB) regulation, issued in Basel and coming into effect in 2023.

This paper first suggests an algorithm for implementing the FRTB standardised approach via the sensitivities-based method to estimate a portfolio's risk capital and presents an illustration applied to an option position. Second, it proposes a methodology to estimate the expected shortfall in options portfolios from the FRTB internal models approach. In this regard, an application is developed to measure expected shortfall (ES) and value at risk (VaR) impacts under FRTB versus conventional VaR in a currency option position by considering stress scenarios from the 2007–9 and 2020–1 crises and back-testing procedures.

The suggested algorithm satisfactorily captures impacts via the sensitivities-based method, and higher risk capital demands are expected for emerging economies. Also, the planned FRTB methodology to measure ES and VaR is appropriate; in particular, historical metrics perform well. Astonishingly, their revealed impacts are more significant under the 2020–1 pandemic crisis than the 2007–9 financial crisis.

The proposals developed weave a communication bridge between the standardised and internal approaches of FRTB regulation, which can be scaled up technologically and institutionally.