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The purpose of this study is to examine the nonlinear relationship between financial constraints and the chief executive officer (CEO) stock options compensation and to analyze whether the impact of financial constraints on the CEO stock options compensation changes at certain level of financial constraints or not.

This study is based on a sample of 90 French firms for the period extending from 2008 to 2019. To deal with the non-linearity, the authors use a panel threshold method.

Using different measures of financial constraints [KZ index (Baker et al., 2003), SA index (Hadlock and Pierce, 2010) and FCP index (Schauer et al., 2019)], the results reveal that the impact of the financial constraints (SA index and FCP index) is positive below the threshold value and it becomes negative above.

The non-linearity between financial constraints and CEO stock options shows that the level of financial constraints can be a major determinant of the CEO compensation structure. More specifically, this study sheds light on the key role played by the level of financial constraints and how this latter influence management decisions.

This paper is the first to the best of the authors' knowledge to examine the nonlinear relationship between financial constraints and the CEO stock options compensation using a panel threshold model.

Employee Stock Options [ESOs] have been used widely as a component of employees' compensation. To maximise the incentive effect of these options it is very important to understand the exercise decision of the employees. This is an important financial decision that is dependent on both rational and psychological factors. This paper aims to study the mediating role of Herding Bias on Personality Traits and the employees' decision to exercise ESOs.

The data were collected through a self-structured questionnaire from 210 employees of Banks and NBFCs [Non-Banking Financial Companies] who have received and exercised the ESOs. SPSS MACRO version 25 was used to understand the mediational effect of Herding Bias on Personality Traits and Employees' decision to exercise their ESOs.

The results showed that Personality Traits affect the employees' decision to exercise their ESOs. The study also shows a partial negative mediating effect of Herding Bias on Personality Traits and employees' decision to exercise ESOs.

Limited study has been conducted on how the employees make their decision to exercise ESOs. Although extant studies have touched upon the importance of including behavioural biases in ascertaining the exercise decision of the employees, the predictors of the behavioural biases have not been studied under this context. To the best of the author's knowledge, this study is the first in itself to study the inter-linkage between Personality Traits, Herding Bias and employees' decision to exercise ESOs.

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.

Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures.

The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation.

Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects.

To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products.

This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors.

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.

This study aims to examine the influence of stock liquidity on the trade credit of publicly listed companies in Saudi Arabia.

In this study various econometric models were used to test the data of 900 firms listed in Saudi Arabia during the period of 2010–2019.

The robust results of the various econometric models indicate that firms are more willing to offer trade credit to customers when stock liquidity is greater; however, they are less likely to rely on obtaining more payables from suppliers. The findings further indicate that payables and receivables are indeed related, but not exclusively, in the sense that more payables lead to more receivables. The study also reveals a pattern of persistence in payables and receivables during the period of study.

The sample of the present study is only made up of Saudi listed companies. Future research could extend the sample of this study taking into account listed firms in the Middle East and North Africa (MENA) region as a whole so as to gain more insights from the entire region including oil-producing and non–oil-producing countries. More studies are needed to further examine the impact of alternative options for credit access and their linkage to stock liquidity. Finally the difference in difference (DiD) method of analysis as quasi experimental method can be another extension of this research.

The findings would provide implications for managers and investors by recognizing the potential role of stock liquidity in affecting trade credit and understanding the association between the stock liquidity and trade credit. Management of the firms should look for the ways to enhance the stock liquidity of the firms so as to help in reducing the extreme debts usage and therefore, alternative source of funds can be available accordingly. Once the advantage of stock market is identified, firms' managers should search for chances and policies that can promote stock liquidity and hence make use of the advantages of being liquid.

This paper provides new evidence from the emerging market, particularly the Saudi Arabia. The attempt is one of the first in the region to broaden the knowledge about the effects of stock liquidity on trade credit. It provides market participants with insights on the role of stock liquidity in financial flexibility.

This study aims to explore the underlying issues of behavioural biases in relation to stock market participation and the challenges of individual investors in Bangladesh. The study identifies behavioural biases affecting individuals’ stock market participation, their circumvention strategies and the importance of financial knowledge in encouraging the participation of individuals in the stock market.

Semi-structured interviews were used in this study to gather information from industry researchers, individual investors, brokers and institutional advisors. Twenty-two experts were contacted, and 13 agreed to participate in the interviews. The study then uses the thematic analysis method to report its findings.

This research shows that investors’ behavioural biases (such as loss aversion, herding, trust, gambler’s fallacy and risk tolerance) are among Bangladesh’s primary drivers of stock market participation. Circumvention strategies (such as poor corporate governance and agency costs) also play a part in individuals’ participation. These influences are in addition to the obvious factors of investment risks, poor infrastructure, poor regulation enforcement and the need for more sufficient investment products.

This study conducted 13 interviews with expert subjects, which is a small sample size. However, the findings achieved saturation and cannot be ignored. Future research should use quantitative or experimental methods with a large sample size to validate the current findings.

This study is pioneering in the Bangladesh stock market, exploring the behavioural biases of investors’ participation in the market. This paper provides valuable insights into investor participation by discovering the underlying behavioural biases that have been continually ignored; these insights may also be relevant in frontier markets in Asian countries.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

Warehouse receipt-based financing (WRF), an innovative instrument with its structure embedded in the agricultural value chain can potentially address farmers' concerns about timely credit access and accessible remunerative markets. However, studies indicate farmers' exclusion from currently practiced WRF mechanisms across developing countries. Transaction cost and lack of assured remunerative markets post storage are the challenges thwarting farmers' participation. The study explores how these challenges can be addressed by analyzing a case study. The finding will help in coming up with a farmer-inclusive WRF mechanism.

The study uses a case study as an analysis tool. Primary data is gathered through farmers. Descriptive statistics and partial least squares (PLS) approach to structural equation modeling methodology has been adopted for empirical testing of the hypothesis of the study. The study uses SMART PLS 3.0 for analysis of data.

Single window offering of multiple value chain operations and technological intervention in physical handling substantially reduces transaction costs for farmers. Sustained farmers' participation in the case supports this finding. The presence of an assured market (PAM) is found to have a positive and significant relationship with WRF in the case of beneficiary farmers. The PAM is found to have a negative yet significant relationship with WRF in the case of nonbeneficiary farmers. Critical success factors of the entity KisanMitra stated in the case substantiates a farmer-inclusive WRF mechanism.

The study analyzes a case study of specific geography. However, similarities enlisted across developing countries in the introduction section provide a scope of generalization of findings across developing countries. The identified factors for a farmer-inclusive WRF mechanism will enable the governments, policymakers and development institutions to ascertain and align their WRF implementation measures to inculcate and upgrade these factors to the prospective WRF agents. Future studies can explore the replication of farmer-inclusive WRF mechanisms across other geographies. The studies also explores the role of technological interventions in further reducing the transaction cost and suitable policy modifications to encourage replication of the study in other geopgraphical context.

The study on WRF and the methodology adopted is first of its kind to identify factors for a farmer-inclusive WRF mechanism.

Stock markets are highly sensitive to foreign and domestic events. Stock exchange markets react promptly to news and are known as an indicator of good and bad trading conditions. Terrorist attacks leave adverse effects on the economy and cause stock price volatility and, consequently, stock return volatility. Therefore, this paper aims to analyze the spatial effects of terrorism on stock market returns in the Middle East from 2008 to 2019.

This paper uses analytical research design and estimates spatial model. Before estimating the spatial model, the spillover effects were confirmed for the spatial autoregressive model using Moran’s diagnostic test for spatial dependence, Geary’s C test and Akaike statistic.

The results of this study on spatial panel data and based on spatial autoregressive estimator indicated that terrorism and associated neighborhood effects had a negative impact on stock returns in Middle East countries. Also, the corruption index and oil price negatively affected stock market return in these countries, while the democracy index had a positive effect on stock market returns. According to the results, to achieve a high and stable stock market return, it is recommended that high-level consultation is pursued with leaders of involved countries to reduce the devastating effects of terrorist activities, increase political and economic stability, attract stockholders to stock markets and spend corresponding incomes developing the infrastructures in this sector in countries of this region.

Most of the studies have investigated the impact of terrorism on the stock market returns at the national or provincial level. However, the effect of terrorism on the stock market index in the tense region of the Middle East, which is the center of terrorist attacks in the world, has not been dealt with by considering the spatial econometric effects. Thus, to the best of the authors’ knowledge, this research is a first attempt to study the impact of terrorism on the stock market returns in Middle East countries using the spatial econometric approach.