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This study aims to examine the cross-market efficiency of the FTSE/MIB index options contracts traded on the Italian derivatives market (IDEM) during a period including the financial crisis between 1st October 2007 and 31st December 2012 using daily option prices.

Two fundamental no-arbitrage conditions were tested: the lower boundary condition (LBC) and the put–call parity (PCP) condition while taking into account the role of transaction costs in mitigating the number of violations reported. Ex post tests of LBC and PCP revealed a low incidence of mispricing in this market. Furthermore, to check the robustness of the results obtained by the ex post tests, ex ante tests were applied to PCP violations occurring within a one-day lag.

The results showed a significant drop in the number of profitable arbitrage strategies. The findings obtained from all these tests generally support the cross-market efficiency of the Italian index options market during the sample period, though some violations were occasionally reported. Overall, the number and monetary value of the violations reported declined during the post-financial crisis period compared to those during the financial crisis period.

This study can be extended to test the relationships between arbitrage profitability and other factors such as the moneyness (in the money, out of the money, at the money) of options and the maturity of options. Options market efficiency tests can be conducted such as call and put spreads, box spreads and put/call convexities (butterfly spreads).

There are several factors that influenced the decision to test the Italian index options market. First, the limited number of studies conducted on this market. Second, the fact that the two main studies on this market are relatively old, which makes it interesting to test the efficiency of this market with respect to a new set of data, taking into account the introduction of the Euro and the impact of the recent financial crisis on this market and whether the market efficiency hypothesis holds during the period of crisis. Third, it is important to consider the effect of the new rules applied to this market.

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.

This paper attempts to develop a hybrid model using advanced data mining techniques for the detection of Stock Price Manipulation. The hybrid model detailed in this article elucidates the application of a Genetic Algorithm based Artificial Neural Network to classify stocks witnessing activities that are suggestive of potential manipulation.

Price, volume and volatility are used as the variables for this model to capture the characteristics of stocks. An empirical analysis of this model is carried out to evaluate its ability to predict stock price manipulation in one of the largest emerging markets – India, which has a large number of securities and significant trading volumes. Further, the article compares the performance of this hybrid model with a conventional standalone model based on Quadratic Discreminant Function (QDF).

Based on the results obtained, the superiority of the hybrid model over the conventional model in its ability to predict manipulation in stock prices has been established.

The classification by the proposed model is agnostic of the type of manipulation – action‐based, information‐based or trade‐based.

The market regulators can use these techniques to ensure that sufficient deterrents are in place to identify a manipulator in their market. This helps them carry out their primary function, namely, investor protection. These models will help effective monitoring for abnormal market activities and detect market manipulation.

Implementing this model at a regulator or SRO helps in strengthening the integrity and safety of the market. This strengthens investor confidence and hence participation, as the investors are made aware that the regulators implementing market manipulation detection techniques ensure that the markets they monitor are secure and protects investor interest.

This is the first time a hybrid model has been used to detect market manipulation.

The purpose of this paper is to establish a decision‐making governance framework for transferring a product/service from one EU host market to another.

Prior research concerning the relation between marketing decision governance (centralised versus decentralised) and standardisation strategy/performance tends to focus on the home‐host scenario. This study has utilised the experience of 70 firms operating in the cross‐market scenario in the EU region – i.e. transferring a product/service from one EU host market to another – in order to establish its decision‐making governance framework. The respondents were operating in both the manufacturing and service sectors.

It was found that firms with large size and a high level of business experience, operating in a similar cross‐market environment, or in a country pair that has a difference in market potential, are more likely to pursue a decentralised governance. Firms operating in a highly different market environment and in host markets with a high variation in market potential are likely to adopt an adaptation strategy. Marketing decision governance is not suggested to be related to standardisation strategy. Decentralised governance is found to be related to profitability, while adaptation was associated with market share. Market share is related to profitability.

The research findings suggest that firms can utilise their decision‐making and standardisation strategy separately to achieve their performance objectives when operating across the EU region. The outcomes established in the study have provided a new guidance on the research concerning structure, strategy and performance.

This study aims to systematically review the literature in the fields of liquidity, informational efficiency and default risk. The authors outline the key research streams and provide possible pathways for future research.

The study adopts bibliographic mapping to identify the most influential studies in the research fields of liquidity, informational efficiency and default risk from 1984 to 2021.

The study identifies four key research themes that include efficiency and transparency of markets; corporate yield spreads; market interactions: bonds, stocks and cryptocurrencies; and corporate governance. By assessing publications published from 2018 to 2021, the authors also document seven key emerging research trends: cross markets, managerial learning and corporate governance, state ownership and government subsidies, international evidence, machine learning (FinTech approaches), environmental themes and financial crisis. Drawing on these emerging trends, the authors highlight the opportunities for future research.

Keyword searches have limitations since some studies might be overlooked if they do not match the specified search criteria, even though their relevance to the topic is under investigation. Adopt the R project to expand this review by incorporating more literature from other databases, such as the Scopus database could be a possible solution.

The four key research streams contribute to a comprehensive understanding of liquidity, informational efficiency and default risk. The emerging trends integrate existing knowledge and leave the chance for innovative research to expand the research frontier.

This study fulfills the systematic literature review streams in the fields of liquidity, informational efficiency and default risk, and provides fruitful opportunities for future research.

The purpose of this paper is to propose an empirical procedure for examining the time‐varying features of cross‐market correlations in selected Gulf stock markets.

The paper directly infers the cross‐market linkages from the stock data using a multivariate dynamic conditional correlation GARCH model (DCC‐GARCH). The paper attempts to date the structural breaks in the time‐paths of the conditional correlation indices to investigate whether the cross‐market comovement encompasses significant changes in nature or not.

Conditional cross‐market correlations between studied markets are shown to be time‐varying, past‐dependent and subject to structural breaks. However, the comovements are still small within the Gulf region and insignificant between the Gulf stock markets and the world market.

Even though the paper attempted to relate the observed changes in market linkages to major economic and political events that the Gulf region experienced during the sample period, a more careful, in‐depth analysis is needed since the primary objectives of this paper consist only of measuring stock market comovements and detecting their possible structure changes.

For global investors, there is still room for international and regional diversification in Gulf markets, given the low degree of comovements documented in the study.

The application of the DCC‐GARCH model and structural change test in a linear framework appears to be suitable for studying the time‐varying properties of cross‐market linkages between markets in the Gulf region. It also provides information about the degree of financial integration of the studied markets with the world stock market through an analysis of the conditional correlation coefficients.

This paper aims to investigate the volatility transmission and dynamics in China Securities Index (CSI) 300 index futures market.

This paper applies the bivariate Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation (DCC) Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models using high frequency data. Estimates for the bivariate GARCH models are obtained by maximising the log-likelihood of the probability density function of a conditional Student’s t distribution.

This empirical analysis yields a few interesting results: there is a one-way feedback of volatility transmission from the CSI 300 index futures to spot returns, suggesting index futures market leads the spot market; volatility response to past bad news is asymmetric for both markets; volatility can be intensified by the disequilibrium between spot and futures prices; and trading volume has significant impact on volatility for both markets. These results reveal new evidence on the informational efficiency of the CSI 300 index futures market compared to earlier studies.

This paper shows that the CSI 300 index futures market has improved in terms of price discovery one year after its existence compared to its early days. This is an important finding for market participants and regulators. Further, this study considers the volatility response to news, market disequilibrium and trading volume. The findings are thus useful for financial risk management.

The aim of this paper is to examine the effect of information disclosure by unlisted bond issuers on the stock price informativeness of listed firms in the same industry.

This paper takes advantage of information disclosure during the bond issuance and examines the spillover effect of unlisted bond issuers' information disclosure on listed firms in the stock market. The sample is composed of A-share firms listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2018. All the data are obtained from the China Stock Market and Accounting Research and WIND databases. The impact of bond market information disclosure on price informativeness of listed firms in the same industry is identified through multivariate regression analyses.

Empirical results show that price informativeness of listed firms has a significantly positive association with the information disclosure of same-industry unlisted bond issuers. Further analyses show that the above finding is more significant when information disclosure of bond issuers is a more important channel for acquiring industry information (i.e. when industry is more concentrated, when economic uncertainty is high, and when industry information is less transparent) and understanding the industry competitive landscape (i.e. when bond issuers are relatively large, when bond issuers and listed firms have more direct product competition, when bond issuance firms are large-scale state-owned business groups), and when there are more cross-market information intermediaries (i.e. more cross-market institutional investors and more sell-side analysts). This paper indicates that information disclosure of bond issuers has a positive spillover effect on the stock market.

The novelty of the research is that the authors examine industry information spillover from unlisted firms to listed firms leveraging on unlisted firms' information disclosure in bond markets.

The purpose of this paper is to examine herding in four frontier markets in the Balkan region, namely, Bulgaria, Croatia, Romania and Slovenia, from October 2000 to December 2016.

The author employs Chang et al.’s (2000) cross-sectional dispersion approach to capture herding, while also testing for the global financial crisis’ effects and the European Union (EU)/Euro zone accession effects over herding. Potential asymmetric herding effects conditional on market performance, domestic volatility, German and US investor sentiment are also examined. Finally, the cross-market herding dynamics of the region are also explored.

Overall, Romania exhibits the most extensive evidence of herding across various estimations. The empirical results indicate that cross-market herding dynamics within the region generate stronger herding (compared to the herding observed within each stock market individually), suggesting that Balkan stock exchanges’ growing financial integration leads their herding to be “imported”, rather than domestically motivated.

The findings provide useful insights for regulators in frontier markets, considering the destabilising potential of herding; they are also of particular interest to the investment community for reasons of international asset allocation, diversification and hedging strategies.

This study contributes to the limited herding literature regarding frontier markets and provides novel findings regarding the herding dynamics in the Balkan region, the EU/Euro zone accession’s effect and global factors’ impact on herding estimations.