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The purpose of this paper is to consider competition’s issues between European market firms, such as Euronext, and multilateral trading facilities, following Markets in Financial Instruments Directive’s enforcement. This new domestic competition is adding to the existing international competition among financial centers. While diversification of local trading services can improve the international competitiveness of a financial center, the fragmentation of order flows can harm its attractiveness.

The theoretical setting analyzes the interaction between heterogeneous who experiment network externalities, and heterogeneous local trading services providers (alternative platforms and incumbent) in an international context. The authors compare two forms of organizations of the market: a consolidated market, and a fragmented market with alternative platforms – in both cases, in competition with a foreign universe.

The results of this study point out the importance of the trade-off between diversification and externalities. With alternative platforms entry, enhanced competition decreases fees and redistributes informed investors between the foreign market and the domestic one. The increase of domestic platforms’ number then has more complex effects on externalities (of information and liquidity). When the liquidity externalities are low, the diversification of financial platforms increases the number of investors on domestic centers. When liquidity externalities are not negligible, despite the decrease of fees, this same diversification orientates more informed investors to the foreign center.

This model is the first to analyze jointly the internal and international competition of trading platforms with heterogeneous investors.

Social trading platforms are considered to be amongst the major innovations in online trading. The purpose of this article is to analyze the trading activity of traders on social trading networks by taking a behavioral approach. Additionally, the authors investigate the factors that influence the irrational part of trading activity derived from the key characteristics of these platforms, i.e. those dealing with social interaction.

The investigation utilizes an extensive set of trading data from two major platforms in Germany to study the trading behavior. The authors apply a fixed effects two-stage least squares (2SLS) approach to quantify the relationship between trading activity and performance and define overconfidence as the part of trading activity that is irrationally motivated and results in negative returns.

The results provide evidence for the negative relationship between overconfidence and return on social trading platforms. The authors find that the number of followers and some platform-specific features significantly affect the trading behavior of the traders.

The authors contribute to the existing literature by exploring how the novel social interaction characteristics of online trading impact trading activity by giving rise to a new dimension of overconfidence. In addition, the authors evidence that the different frameworks of the platforms motivate heterogenous behavioral responses by the signalers. Finally, the authors refine existing studies by applying a distinct methodology for modeling overconfidence.

This paper aims to study the pricing strategies of an online trading platform with indirect network externalities by considering heterogeneous trading behavior in the downstream market and the long tail.

The game theory, optimization and comparative static are used in this research. The equilibria are derived from the game theory, and with them, the authors optimize the platform’s profit function. Comparative static is used to study pricing strategies.

It is found that with heterogeneous trading behavior, the transaction-based model is more profitable than the subscription-based model by reason of the feasibility of “price discrimination”. However, with certain advantages of subscription fees such as avoiding offline transactions, the subscription-based model is better with a concentrated distribution of sellers’ revenues (the Gini coefficient is small). With a lucrative long tail, the platform should set a low price to attract small sellers in the long tail. Besides, if the Gini coefficient is large, the effects of the market entry barrier of sellers on the optimal price in each model may be opposite.

It implies that the choice of revenue models and pricing strategies are influenced by the Gini coefficient or the long tail. The exogenous setting in which buyers can use the platform for free needs further extension.

The authors provide insights on how to choose revenue models and how to price the sellers with the long tail phenomenon.

This paper emphasizes the role of the long tail on pricing strategies and the effect of heterogeneous trading behavior on model selection.

The purpose of this paper is to design a sustainable development platform for water and energy peer-to-peer trading that is financially and economically feasible. Water and other resources are becoming scarcer every day, and developing countries are the neediest for an immediate intervention. Water, as a national need, is considered to be one of the most precious commodities, but it is also one of the main causes for conflicts in the 21st century. Rainwater harvesting and peer-to-peer trading of the harvested water is one of the most convenient, scalable and sustainable solutions but faces organization challenges such as the absence of suitable business models motivating normal users to sell their generated resources (such as water and energy), currency and financial settlement complexities and single utility markets.

This paper proposes a multi-utility trading platform based on the blockchain technology which can address the challenges faced by peer-to-peer trading for resources such as energy and water.

This paper presents a peer-to-peer multi-utility trading platform that solves the shortcomings of existing utility frameworks reported in the current literature.

This proposed platform meets the needs of developing countries as well as rural areas of developed countries. The open nature of the proposed design makes it suitable for adoption and use by various stakeholders.

The purpose of this paper is to provide a theoretical framework for the legal classification of trading venues in financial markets. Currently, there is no clear definition of when a trading platform should be classified as multilateral or bilateral. This paper builds a theoretical framework that will allow regulators to define the border (with its regulatory implications) between multilateral and bilateral trading venues.

The approach used for this paper focuses on looking at the different trading models available in financial markets and analyzing their key features in order to bring up recurrent aspects that have helped to build the theoretical framework.

Multilateral trading facilities would not only be systems bringing together multiple interests from third parties, but those systems bringing together multiple interests with “no discretion” (ex ante rules) vis‐à‐vis membership, admission of products to trading, and matching of interests. All trading venues that do not meet these three key requirements will be falling under the bilateral trading classification, which implies the application of fiduciary duties, such as conflicts of interest rules and best execution. The paper then advances a proposal to solve the legal classification issue in the revision of the Markets in Financial Instruments Directive in Europe (MiFID). In effect, despite the claim that the Organised Trading Facility (EU) and the Swap Execution Facility (USA) would be equivalent categories, EU and US regulators, respectively, have taken divergent paths on how these venues will ultimately look.

The value of the paper is in its ability to provide a theoretical framework to something that has not been assessed in these terms previously. Today, only the SEC is trying, for the first time, to have a definition of when a RFQ model can be defined “multilateral”. This topic has been rarely discussed before in financial regulation, while it is extensively discussed in market microstructure (but on the market structure implications, rather than its regulatory and policy implications).

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

The purpose of this paper is to give an overview of UAE Stock Exchange industry. In particular this paper aims to assess a potential merger between Dubai Financial Markets-Nasdaq-Dubai and Abu Dhabi Securities Exchange, evaluating risks, rewards, policy and business implications.

The paper presents a theoretical framework and a literature review of M & As in financial sector. It then carries out a case study on a potential merger between the UAE Stock Exchanges and a discussion on the implications for the actors involved.

The contraction both in market capitalization and in trading value in the three UAE Stock Exchanges caused by subprime financial crisis and market fragmentation could be a key factors in implementing a merger between them. Because of high-fixed costs and trading platform, a single consolidated stock exchange may benefit from significant economies of scale, particularly network effects, and economies of scope.

This paper could be useful to Security and Commodity Authority, in order to support a merger between Dubai and Abu Dhabi Stock Exchange. Given that UAE capital market regulator has tried to improve efficiency in UAE stock market over the last years, a merger between UAE Stock Exchanges could have positive effects on overall efficiency.

It is the first paper that analyze UAE Stock Exchange industry. It is the first study that focusses on a potential merger between emerging markets’ stock exchanges. It is one of the first contributions that relates stock exchanges belonging to emerging and developed countries.

This paper aims to introduce the current-state of the energy grid, to reviews new and enabling peer-to-peer and blockchain-based solutions and to propose a strategic go-to-market framework, populated with energy companies strategically positioned to capture the unique opportunities present across the energy industry.

Hundreds of use-cases worldwide have been reviewed, and 50 worldwide blockchain energy companies and initiatives were included in this study based on the publicly accessible information that indicates their go-to-market strategies. As a result, these initiatives were classified into three main types of go-to-market strategies. Each company and its portfolio of blockchain-based solutions was described under these three categories.

Based on the research conducted in this review paper, it is evident that the adoption of blockchain-based technologies, solutions and services is accelerating at a rapid pace within the global energy industry to meet the needs and challenges that exist within it. Given the companies outlined in this paper, the opportunity to leverage blockchain technology while aligning to a social driver like green energy is perceived to be the most promising go-to-market strategy within this sector.

This study explores the apparent business plans of different blockchain initiatives around the world. Although there are a few other review papers recently published, to the best of the authors’ knowledge, this approach has not been taken in other studies in terms of the categorization of available use-cases.

The aim of this paper is to examine the informational efficiency of prices of all exchange traded funds (ETFs) that are actively traded on the NYSE Arca, based on methodology developed by Chordia et al.

The authors estimate the speed of convergence to market efficiency based on short‐horizon return predictability from past order flows of 273 ETFs that were traded every day on the NYSE Arca during the first six months of 2008, and compare the resulting price formation process to that of shares traded on the NYSE and NYSE Arca.

Despite the significant differences in trading costs, volatility, and informational effects between ETFs and regular stocks, the paper documents that price adjustments to new information for ETFs occur in about 30 minutes, which is comparable to price adjustments for traditional stocks traded on Arca. In multivariate setting, the paper further shows that the speed of convergence to market efficiency of ETFs is not only significantly driven by volume, but also by the probability of informed trading.

The findings provide direct answers and insights to questions posed in a recent SEC concept release document. The analysis of the speed of convergence provides a feasible measure to assess how efficiently prices of ETFs respond to new information.

The authors are first to utilize the short‐horizon return predictability from historical order flow approach to evaluate the price formation process of ETFs and to provide evidence on the determinants of its efficiency.