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This paper aims to consolidate and review the literature in the field of market-calibrated option pricing analysis. By doing so, the paper brings out the gaps in the extant literature and makes suggestions for future researchers in the field.

The methodology used in this research is inspired by the works of Ferreira et al. (2016), Jabbour (2013), Lage Junior and Godinho Filho (2010), Seuring (2013) and Sharma et al. (2018). A total of 1,500 papers written on the pricing of options globally are collated from the Web of Science ranging across 2010-2018.

Most of the research papers present mathematical proposals to value options; without calibrating it with real market data points. The authors bring out five important gaps in the extant literature.

This is arguably the first study that consolidates the literature in the field of market calibrated option pricing analysis with a view to suggest directions for future researchers.

Option pricing theory enables computation of the price of an option using different variables associated with the underlying security and options contract. The purpose of this study is to assess research trends that emerged in the field of option pricing. This study reviews existing literature of the option pricing domain, both qualitatively and quantitatively, and identifies potential themes for future research.

This study adopts bibliometric analysis method to explore literature published in the option pricing domain. As part of bibliometric analysis, this study considers both descriptive and network analysis to assess publication trends. For descriptive analysis, the “bibliometrix” package proposed by Aria and Cuccurullo (2017) is used and for network analysis, VOS viewer (Van Eck and Waltman, 2017) and Gephi (Bastian et al., 2009) are used.

This study identifies research trends, top researchers, articles, journals and contributions from institutions and countries in the option pricing domain. It identifies four clusters that show different directions and also focuses on past studies on the same subject. It explores research gaps by performing an in-depth analysis of existing literature on option pricing and suggests the way forward for research in this area.

To the best of the authors’ knowledge, no previous studies have attempted to analyze the literature published in the option pricing domain. This study fulfils this research gap by conducting a comprehensive analysis of studies in the option pricing area. This study identifies quality research work published in the domain, research trends, contribution by most relevant researchers, contributions across geographies and institutions and the connections among these aspects. This study also identifies important themes and provides directions for future research.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

Typically, international capital budgeting is carried out using the adjusted net present value (NPV) approach. In this article, we present an alternate method for valuing international investments; one that is based on the option pricing theory developed by Black and Scholes (1973). We show that when (a) the decision being valued involves an irreversible investment, (b) the investment decision can be postponed, and (c) uncertainty is resolved gradually over time, using the option pricing approach may be more appropriate than the NPV approach. Applying the traditional NPV approach to value investments such as the decision to enter a new market, expand production, suspend operations temporarily or liquidate operations, may lead one to underestimate their value. This is because the naive NPV criteria is a static valuation method that ignores a firm's flexibility to postpone projects, to abandon them, or to shut down operations temporarily.

Accounting for stock options is a controversial issue. The FASB recognized that the “intrinsic value” method, which had been used for years, failed to adequately account for the costs involved. To rectify the problem they suggested the use of a “fair value” method. Their proposal met with strong objections from companies, which were concerned with the impact of the proposed standard on their reported profits. Consequently, the board relented and allowed the use of either method. Unfortunately, both the intrinsic value and fair value approaches have deficiencies, particularly in regard to how they measure compensation expense and gains and losses over time. This paper addresses these shortcomings by developing two alternative cost measurement approaches that apply an option‐pricing model on an iterative basis over the life of the option. Both approaches represent specific ways to implement exercise‐date measurement techniques for stock options. The paper argues that both approaches provide more relevant and reliable measures of an option’s cost than either intrinsic or fair value methods.

Owing to the fact that the over-the-counter (OTC) market has no organized exchange, the options traded in the OTC market are more likely to be exposed to credit risk, Asian options being one of them. In this chapter we first discuss the pricing of geometric Asian options and the Black–Scholes options model subject to credit risk. We then combine the two models to derive a closed-form formula for pricing a geometric Asian option subject to the credit risk. The numerical analysis reveals that other pricing formulae existing in the literature can cause serious pricing errors when there is a possibility of default in reality.

This paper proposes a discrete time real options model with time‐dependent and serial correlated return process for a real estate development problem with waiting options. Based on a Martingale condition, the paper claims to be able to relax many unrealistic assumptions made in the typical real option pricing methodology. Our real option model is a new one without assuming the return process as “Ito Process”, specifically, without assuming a geometric Brownian motion. We apply the model to the condominium market in Tokyo metropolitan area in the period 1971‐1997 and estimate the value of waiting to invest in 1998‐2007. The results partly provide realistic estimates of the parameters and show the applicability of our model.

Retail properties are a perfect example of a property class where revenues determine the rent for the property owners. Estimating the value of new retail developments is challenging, as the initial revenues can have a significant variance from the long-term revenue levels. Owners and tenants try to manage this problem by introducing different kind of options, such as overage rent and extension rights, to the lease contracts. The purpose of this paper is to value these options through time for different types of retailers, using real-life data with a method that can be easily applied in practice.

This paper builds upon the existing papers on real option studies but has a strong practical focus, which has been identified as a challenge in the field. The paper presents simple mathematical equations for valuing overage rent and extension options. The equations capture the value related to uncertainty (volatility) that is missed by standard valuation practices.

The results indicate that overage and extension options can represent a significant proportion of retail lease contract’s value and their value is heavily time-dependent. The option values differ greatly between tenants, as the volatilities can have a large spread across tenants. The paper suggests that the applicability of option pricing theory and calculus should not be considered as an insurmountable barrier any more, rather a greater challenge for the practical adaptability of the method can be the availability of real-life data that is a common problem in real option analysis.

The value of extension and overage options varies greatly between tenants. In general, the property owner can try balance the positive effects from the overage rents to the negative effects of tenant extensions. However, this study tries to highlight that, as usual, using the “law of averages” can result into poor valuation in this context as well. Even the data used in this study provide valuable findings for the property owner as an analytical deduction can be made that certain types of tenants have higher volatilities and this should be acknowledged when valuing options within lease contracts.

Previous literature in this topic often takes the input data for the option valuation as granted rather than trying to identify the real-life data available for the calculation. This is a common problem in real options valuation and it seems to be one of the reasons why option valuation has not been used widely in practice. This study has used real-life data to assess the problem and more importantly assessed the data across different types of tenants. The volatility spread between different types of tenants has not been discussed previously, even though it has a significant importance when using option pricing in practice.