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This paper aims to examine the applicability of real options methodology with respect to developing internal transfer pricing mechanisms. A pervasive theme in existing models is their inability to handle the dynamic and volatile nature of today’s business environment, as well as their lack of objective managerial flexibility. The authors address these and other issues and develop a transfer pricing mechanism based on Black–Scholes and the binomial options pricing methodology, which is better suited in today’s dynamic business environment.

The authors use a conceptual approach in developing theoretical justifications and show, practically, how a transfer price can be developed using two different real options pricing models.

The authors find that real options transfer price mechanism (real options framework [ROF]) can effectively deal with many of the issues that permeate a modern organization with complex multi-dimensional operations. The authors argue that uncertainty and behavioral issues commonly associated with setting transfer prices are better handled using a transfer pricing mechanism that preserves flexibility at the business unit level, the managerial level and the firm level. The approach allows for different managerial styles in both centralized and decentralized sub-units within the same organization. The authors argue that an open multi-dimensional framework using real options is suitable under conditions of uncertainty and managerial opportunism.

ROF-based transfer pricing may be significant in that firms can use it as a tool to manage an organization by setting the prices centrally and at the same time allowing managers to select the transfer price that best suits their specific situation and operating conditions. This may result in a more efficient and more profitable organization.

The contribution of the paper is the melding of the ROF from the finance literature with the accounting problem of setting a transfer price for items lacking a competitive market price. The authors also contribute to existing research by explicitly developing a framework that values managerial flexibility, takes into account uncertainty and considers the behavioral aspects of the transfer pricing process. The authors establish the conditions under which a generic real options model is a feasible alternative in determining a transfer price.

The purpose of this paper is to test the pricing performance of Black-Scholes (B-S) model, with the volatility of the underlying estimated with the two-scale realised volatility measure (TSRV) proposed by Zhang et al. (2005).

The ex post TSRV is used as the volatility estimator to ensure efficient volatility estimation, without forecasting error. The B-S option prices, thus obtained, are compared with the market prices using four performance measures, for the options on NIFTY index, and three of its constituent stocks. The tick-by-tick data are used in this study for price comparisons.

The B-S model shows significantly negative pricing bias for all the options, which is dependent on the moneyness of the option and the volatility of the underlying.

The negative pricing bias of B-S model, despite the use of the more efficient TSRV estimate, and post facto volatility values, confirms its inadequacy. It also points towards the possible existence of volatility risk premium in the Indian options market.

The use of tick-by-tick data obviates the nonsynchronous error. TSRV, used for estimating the volatility, is a significantly improved estimate (in terms of efficiency and bias), as compared to the estimates based on closing data. The use of ex post realised volatility ensures that the forecasting error does not vitiate the test results. The sample is selected to be large and varied to ensure the robustness of the results.

Recent developments in accounting for stock options have increased interest in the analytical techniques used to value them. Techniques used to value the options of publicly traded companies have been extensively discussed. In contrast, there has been almost no discussion of the valuation procedures of the options for non‐publicly traded companies. This paper addresses this gap. The paper suggests that a straightforward income capitalization model can be used to develop reasonable surrogates for the variables of the Black‐Scholes option pricing model. The paper also discusses how to adjust the income apitalization model for both lack of marketability and lack of control discounts.

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 aims to study a preemption proposition for the compliance costs associated with stock option expensing under SFAS 123(R) by examining whether early adopters used their discretion over option pricing model inputs to mitigate the adoption effect.

The paper uses a matched sample approach of firms that voluntarily adopted stock option expensing during the 2002-2004 period and similar firms that waited until the mandatory expensing. The paper empirically examines some determinants of voluntary adoption, and the changes in option pricing model inputs during the period leading to mandatory expensing.

The paper reports evidence that voluntary adopters of stock option expensing during the 2002-2004 period have used the period leading to mandatory expensing to preempt its compliance cost effect. The authors exercised their discretion by decreasing estimates for stock price volatility and time-to-maturity to preempt or minimize the reduction in earnings before mandatory adoption date.

Results of this paper are useful to accounting regulators in understanding the reaction of financial statement preparers to deliberations, effective dates and voluntary early adoption terms of the accounting standards setting process.

The purpose of this paper is to develop a loan insurance pricing model allowing for the skewness and kurtosis existing in underlying asset returns.

Using the theory of Gram-Charlier option, the authors first derive a closed-form solution of the Gram-Charlier pricing model. To address the difficulties in implementing the pricing model, the authors subsequently propose an iterative method to estimate skewness and kurtosis in practical application, which shows a relatively fast convergence rate in the empirical test.

Not only the theoretical analysis but also the empirical evidence shows that the effects of skewness and kurtosis on loan insurance premium tend to be negative and positive, respectively. Furthermore, the actual values of skewness and kurtosis are usually negative and positive, respectively, which leads to the empirical result that the pricing model ignoring skewness and kurtosis substantially underestimates loan insurance premium.

This paper proposes a loan insurance pricing model considering the skewness and kurtosis of asset returns, in which the authors use the theory of Gram-Charlier option. More importantly, the authors further propose a novel iterative method to estimate skewness and kurtosis in practical application. The empirical evidence suggests that the Gram-Charlier pricing model captures the information content of skewness and kurtosis.

This exercise exposes students to the accounting for stock option modifications and option service and performance conditions, requiring research in the Financial Accounting Standards Board (FASB) Accounting Standards Codification and the use of the Black-Scholes option pricing model.

Students identify and apply accounting standards to account for stock option plans, stock option modifications, acquired stock option plans, and service and performance conditions that relate to stock option plans. Indirect student feedback suggests that students view the exercise as valuable. Comments include that the exercise reinforces and expands their knowledge of real-world stock compensation plans. Direct assessment data using grading rubrics finds that most students meet instructor expectations.

The exercise enhances critical thinking skills, increases professional research practice, and improves written skills. It introduces students to common real-world events and reinforces their learning related to stock compensation.

The Black Scholes option pricing model has been put to extensive application both in research and in actual market place. However, the inputs for the model are generally obtained from the stock market which is considered less efficient than the options market. This leads to a difference in calculated price and observed price. This paper studies the bias empirically.

Motivated by recent congressional interest in eradicating government sponsored enterprises (GSE), the purpose of this paper is to develop a framework to price the implicit government guarantee embedded in the bonds issued by the Farm Credit System.

The paper uses the Black‐Scholes model to extract the implied volatilities of the guarantee and then substitute into the model the volatility in historical land prices. The model is developed along the lines of Merton's bond pricing formulation of implicit calls and puts on bond yield risk and default.

Bottom line results show that the average bond yield for a 3M Farm Credit bond from January 13th 2009 to February 10th 2011 would be 0.3744 percent if the Farm Credit System had no GSE status, which is 13.62 bps higher than the actual bond yield. The difference between the hypothetical yield and the actual yield increases with increasing maturity and reaches its peak with 10Y bond where the difference between the hypothetical yield and the actual yield is 68.81 bps. The paper concludes that given the current state of the agricultural credit market in the USA that loss of GSE status and the implied guarantee of Farm Credit bonds would have a minimal effect on short term notes, with a more substantive increase in longer term yields.

The GSE status of the Farm Credit System is an important political issue. This paper provides first estimates of what impact might result from its loss of GSE status. The methods employed are consistent with current models of bond pricing and the results are of direct relevance to Farm Credit System regulators and congressional discussions.

Farm credit is important, if the Farm Credit System loses its GSE status this might affect the competitive balance between commercial and system lenders.

This paper uses option price theory based upon the spread between farm credit bonds and treasury. The approach used requires daily data, but not all attributes of bonds are known. Nonetheless, the results show remarkable consistency for a problem that is largely understudied. There is a need for policy makers, including the US congress to understand the value of government guarantees whether implicit or explicit.

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.