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The impact of volatility crush can be devastating to an option buyer and results in a substantial capital loss, even with a directionally correct strategy. As a result, most volatility plays are for option sellers, but the profit they can achieve is limited and the sellers carry unlimited risk. This paper aims to demonstrate the dynamics of implied volatility (IV) as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the exploratory factor analysis (EFA), they extract four constructs and the results from the confirmatory factor analysis (CFA) indicated a good model fit for the constructs.

This section describes the methodology used for conducting the study. This includes the study area, study approach, sources of data, sampling technique and the method of data analysis.

Although there is extensive literature on methods for estimating IV dynamics during earnings announcement, few researchers have looked at the impact of expected market maker move, IV differential and IV Rank on the IV path after the earnings announcement. One reason for this research gap is because of the recent introduction of weekly options for equities by the Chicago Board of Options Exchange (CBOE) back in late 2010. Even then, the CBOE only released weekly options four individual equities – Bank of America (BAC.N), Apple (AAPL.O), Citigroup (C.N) and US-listed shares of BP (BP.L) (BP.N). The introduction of weekly options provided more trading flexibility and precision timing from shorter durations. This automatically expanded expiration choices, which in turned offered greater access and flexibility from the perspective of trading volatility during earnings announcement. This study has demonstrated the impact of including market sentiment and liquidity into the forecasting model for IV during earnings. This understanding in turn helps traders to formulate strategies that can circumvent the undefined risk associated with trading options strategies such as writing strangles.

The first limitation of the study is that the firms included in the study are relatively large, and the results of the study can therefore not be generalized to medium sized and small firms. The second limitation lies in the current sample size, which in many cases was not enough to be able to draw reliable conclusions on. Scaling the sample size up is only a function of time and effort. This is easily overcome and should not be a limitation in the future. The third limitation concerns the measurement of the variables. Under the assumption of a normal distribution of returns (i.e. stock prices follow a random walk process), which means that the distribution of returns is symmetrical, one can estimate the probabilities of potential gains or losses associated with each amount. This means the standard deviation of securities returns, which is called historical volatility and is usually calculated as a moving average, can be used as a risk indicator. The prices used for the calculations are usually the closing prices, but Parkinson (1980) suggests that the day’s high and low prices would provide a better estimate of real volatility. One can also refine the analysis with high-frequency data. Such data enable the avoidance of the bias stemming from the use of closing (or opening) prices, but they have only been available for a relatively short time. The length of the observation period is another topic that is still under debate. There are no criteria that enable one to conclude that volatility calculated in relation to mean returns over 20 trading days (or one month) and then annualized is any more or less representative than volatility calculated over 130 trading days (or six months) and then annualized, or even than volatility measured directly over 260 trading days (one year). Nonetheless, the guidelines adopted in this study represent the best practices of researchers thus far.

This study has indicated that an earnings announcement can provide a volatility mispricing opportunity to allow an investor to profit from a sudden, sharp drop in IV. More specifically, the methodology developed by Tan and Bing is now well supported both empirically and theoretically in terms of qualifying opportunities that can be profitable because of the volatility crush. Conventionally, the option strategy of shorting strangles carries unlimited theoretical risk; however, the methodology has demonstrated that this risk can be substantially reduced if followed judiciously. This profitable strategy relies on a set of qualifying parameters including liquidity, premium collection, volatility differential, expected market move and market sentiment. Building upon this framework, the understanding of the effects of persistence and leverage resulted in further reducing the risk associated with trading options during earnings announcements. As a guideline, the sentiment and liquidity variables help to qualify a trade and the effects of persistence and leverage help to close the qualified trade.

The authors find a positive association between the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement. These findings substantiate further the four factors that influence IV dynamics during earnings announcement and conclude that just looking at persistence and leverage alone will not generate profitable trading opportunities.

The impact of volatility crush can be devastating to the option buyer with substantial capital loss, even for a directionally correct strategy. As a result, most volatility plays are for option sellers; however, the profit is limited and the sellers carry unlimited risk. The authors demonstrate the dynamics of IV as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the EFA, they extracted four constructs and the results from the CFA indicated a good model fit for the constructs. Using EFA, CFA and Bayesian analysis, how this model can help investors formulate the right strategy to achieve the best risk/reward mix is demonstrated. Using Bayesian estimation and IV differential to proxy for differences of opinion about term structures in option pricing, the authors find a positive association among the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement.

This study aims to explore co-learning classes, a novel approach to leveraging universities’ capacity to contribute to the local sustainable development agenda whilst enhancing students’ learning. These participatory classes were piloted within a UK university masters’ module focussed on action for sustainability. The classes sought to combine knowledge exchange, reflection and social network development by bringing together students and community stakeholders.

The classes were run as a series of five free events, each focussed on sustainability issues relevant for local practitioners. These were either regular timetabled sessions opened up to the public or additional on-campus public events. Attendance was either face-to-face or online. Evaluation was based upon participation data, written feedback and module leader’s post-event reflections.

The classes successfully secured participation from diverse community members, including local government staff, voluntary sector workers and interested individuals. Both students and community stakeholders valued the participatory format, linkages of theoretical and practical knowledge and diversity of attendees.

Findings are based upon a small-scale pilot study. Further research using a wider range of contexts is required to enhance understanding of the co-learning approach.

This paper highlights some key practical issues to consider if employing co-learning approaches in other contexts, including using inclusive language, aligning with students’ motivations and choosing appropriate focal event topics.

Opening up participatory university classes for the public to attend as co-learners is a rarely used approach and has little coverage in academic literature. This small-scale study therefore has value by highlighting some of the potential impacts, strengths and limitations of this approach.

The paper aims to measure the magnitude of the event-induced return anomaly around bonus issue announcement days in Turkey for recent years. Also, by describing the information content of these announcements with the current data, the study tries to find out the factors that cause return anomaly in Borsa Istanbul when firm boards release the bonus issue decision.

The paper conducts event study methodology for detecting market anomaly around bonus issue announcements. For the pairwise comparison purpose, t-test and one-way ANOVA methods are applied to examine if abnormal returns vary according to the information content of the announcements.

Announcement returns for bonus issues from internal resources outperform the issues that are distributed from last year's net income as bonus shares. Findings indicate different return behaviour among internal resources sub-groups. Findings also suggest that investors in Turkey welcome larger-sized issues, while cumulated returns for the initial offers significantly differ from the latter issues.

Findings are limited to the Turkish equity market. Also, the Public Disclosure Platform of Turkey, which is the main data source of the study, does not provide bonus issue announcements before 2010. Therefore, the previous year's data cannot be included in the analysis.

This paper is novel in terms of considering the main resources of the bonus issue in detail to measure the announcement's impact on stock returns.

This study proposes a literature review and, based on the findings, the authors develop a conceptual framework, attempting to explain how technology may influence visitor behavior and eventually trade show performance.

The present research explores the role of visitors in the trade show context. The analysis specifically focuses on the variables that influence visitors’ participation at business-to-business trade shows and how their satisfaction and perception can be related to exhibition performance. The authors also take into consideration technological trends that prior to COVID-19 pandemics were slowly emerging in the trade show industry.

The findings highlight a continuity between pre-, at and postexhibition phases. Visitors’ behavior represents a signal of how a trade show is perceived as postexhibition purchases and next visit emerge as signals of an exhibition evaluation in relation to visitors’ perception. Besides being urgent tools for the continuity of the sector due to the pandemics, emerging technological trends can be key elements in understanding visitors’ behavior and in boosting their interest and loyalty toward trade shows.

The paper proposes a conceptual model including top notch and innovative technological trends to improve the understandment of visitors’ behavior. Both practitioners in companies and academics might find the study useful, given the digital uplift generated by the pandemics.

Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).

The authors use an event study methodology to capture market reactions to MBE.

The authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.

The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.

The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.

The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

The aim of the paper is to investigate the associations between hedge fund activism and corporate internal control weaknesses.

In this paper, the authors identify hedge fund activism events using 13D filings and news search. After matching with internal control related information from Audit Analytics, the authors utilize ordinary least square (OLS) and propensity score matching (PSM) to analyze the data.

The authors find that after hedge fund activism, target firms report additional internal control weaknesses, and these identified internal control weaknesses are remediated in subsequent years, leading to better financial-reporting quality.

The findings indicate that both managers and activists have incentives to develop a stronger internal control environment after targeting.

Independent directors are important corporate decision participants and makers. Based on the Chinese cultural background, this paper interprets the listing order of independent directors as independent directors’ status, exploring their influence on the corporate research and development (R&D) behavior.

This paper studies A-share listed firms in China from 2008 to 2018 as the sample. The main method is ordinary least square (OLS) regression. We also use other methods to deal with endogenous problems, such as the firm fixed effect method, change model method, two-stage instrumental variable method, and Heckman two-stage method.

(1) Higher independent directors’ status attribute to more effective exertion of supervision and consultation function, and positively enhance the corporate R&D investment. The increase of the independent director’ status by one standard deviation will increase the R&D investment by 4.6%. (2) The above effect is more influential in firms with stronger traditional culture atmosphere, higher information opacity and higher performance volatility. (3) High-status independent directors promote R&D investment by improving the scientificity of R&D evaluation and reducing information asymmetry. (4) The enhancing effect of independent director’ status on R&D investment is positively associated with the firm’s patent output and market value.

This paper contributes to understanding the relationship between the independent directors’ status and their duty execution from an embedded cultural background perspective. The findings of the study enlighten the improvement of corporate governance efficiency and the healthy development of the capital market.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.