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The purpose of this paper is to explore the adoption, use, and performance of e-trade systems in South Korean businesses.

The authors developed a modified Technology Acceptance Model extended through resourced-based view theory, to address the performance aspect, hitherto neglected in previous studies. Using the new model, 114 businesses were surveyed, measuring relationships between perceived usefulness, perceived ease of use, e-system usage, and business performance. Latent mean analysis was performed to examine the moderating effects of high and low e-trading system usage.

Through latent mean analysis, the authors determined that the influence of variables varies depending on the level of e-trading system usage. In both the high and low usage groups, perceived convenience influenced reuse of e-trading systems and reuse also had effects on business performance.

The authors only examined Korean enterprises, so it would be useful to also examine the foreign counterparts in international e-trade transactions. Follow-up studies could examine how the dynamics of the sector change over time. Qualitative case study approaches could better understand the perspectives of firms in relation to management strategy formulation and decision making.

The results provide important insight for managers and policymakers concerned with developing electronic trading system strategies, and e-trading system contexts.

Although many studies have explored relationships among perceived advantages, such as usefulness and convenience and use and performance, none have investigated the relationship between usage and business performance targeting e-trading systems.

Big Bang, the deregulation of the London Stock Exchange in October of 1986, was accompanied by changed industry structure, altered regulatory environment, and new trading practices. In particular, trading was automated, and the floor of the Exchange was rapidly abandoned. Such massive discontinuities have produced opportunities in other industries. Although they may prove temporary, opportunities are arising to seek competitive advantage in London. Given the information‐intensive nature of securities trading, and the great differences in resources and experience with technology enjoyed by different firms, many of these advantages will entail the use of information technology.

At one level, the function of a marketplace is to enable sellers and buyers to meet, to agree to terms and conditions, and effect contracts. At another level, however, a marketplace is a mechanism for ensuring that information which might affect the terms and conditions is readily available to all participants, so that the pricing for sales will not be unduly influenced by participants with special information or other advantages, but rather will approach the theoretical price at which the market will settle. Information technology is increasingly being applied to support the exchange of goods and services. It may be used simply to automate existing practices. Alternatively, the introduction of technology into the market may provide an opportunity to rationalize the arrangements. In some instances, however, the implementation of IT may be grasped as a strategic weapon, by a buyer, a seller, or by an organization which provides marketplace services to buyers and sellers. Considers another kind of strategic use of IT in relation to marketplaces. This is the enforcement of fairness in the setting of prices, by drawing participants into a marketplace in which key differences in market power are equalized. Evaluates the outcomes of an electronic exchange supporting trading in chilled and frozen meat.

The purpose of this paper is to examine the effectiveness of UK investment firms’ implementation of the requirements in Commission Delegated Regulation 2017/589 (more commonly known as “Regulatory Technical Standard 6” or “RTS 6”) that govern the conduct of algorithmic trading activities.

A qualitative examination of 19 semi-structured interviews with practitioners working for, or with, UK investment firms engaged in algorithmic trading activities.

The paper finds that practitioners generally have a good understanding of the requirements in RTS 6. Some lack knowledge of algorithms, coding and algorithmic strategies but have used best efforts to implement RTS 6. However, regulatory fatigue, complacency, cost pressures, governance in international groups, overreliance on external knowledge and generous risk parameter calibration threaten to undermine these efforts.

The study’s findings are limited to the participants’ insights. Some areas of the RTS 6 regime attracted little comment from participants.

The paper proposes the introduction of mandatory algorithmic trading qualification requirements for key staff; the lessening of the requirements in RTS 6 for automated executors; and the introduction of a recognised software vendor regime to reduce duplication and improve coordination between market participants that deploy algorithmic trading systems.

To the best of the author’s knowledge, the study represents the first qualitative examination of firms’ implementation of the algorithmic trading regime in the second Markets in Financial Instruments Directive 2014/65/EU.

The Trade‐through rule (TTR) was established in 1975; it was designed to ensure that investors got the best price available for a stock trade. Under the Trade‐through rule, a customer’s order must be routed to the exchange or order market system where the best current price exists at any given moment. For example, if the best price quote for an order is listed by a specialist market maker at the NYSE, a customer order must be routed to the NYSE floor; it may not “trade through” to another exchange. The TTR is really an anti‐trade‐through rule; i.e. it prevents the trading through of orders. In fact, to reflect this reality, the SEC has given the TTR a new name: The Order Protection Rule. In concept, the TTR is a good idea to ensure that investors get the best price possible when trading stocks. At the time the TTR was adopted, it was designed to address a fragmented marketplace for stock trading. However, the financial markets have changed radically since the rule was first adopted. The dramatic increase in the use of personal computers in the early 1980s as well as the advent of electronic communication networks (ECNs) in the 1990s changed the trading landscape.

This paper aims to apply blockchains (BCs) for trade clearing and settlement in a realistic clearinghouse. The purpose is to demonstrate the feasibility and scalability of this approach.

The study uses account BCs and trading BCs as building blocks for trade clearing and settlement. Careful design is made to ensure that this approach is feasible and scalable.

A design has been proposed that can process hundreds of thousands of trades for a clearinghouse and it addresses performance, privacy and scalability of realistic trade clearing and settlement. The design has been implemented and experimented in a clearinghouse for over two months and processes over 3B real transactions from an exchange. The first month was to experiment with the system with historical data, the second month was to experiment with real-time data during market trading hours. The system performed as designed and intended.

This is the first large research paper that applied BCs for clearing in the world. The authors applied the system to a clearinghouse and processed over 3 billion transactions, equivalent to 13 years of London Stock Exchange transaction volume, demonstrating that BCs can handle a large number of transactions.

The design can be duplicated to many clearinghouses in the world, and this also paves the way BCs can be used in large financial institutions.

An implication is that other trading firms, clearinghouses and banks can apply the same technology for trade clearing, ushering the way BCs can be used in institutions. As clearing is a core function in business transactions, this has significant implications. The design can be discussed and improved in various communities.

As this is the first application of BCs to large clearinghouses that uses unique BC designs. This has significant value. Many studies have been performed but few have been reported in the scientific community. The system has been implemented, experimented and demonstrated in public for months.

Lists eight criteria for designing a general trading system for investment, explains how the five steps of genetic (computer) programming work in practice and shows how they can be applied to identify trading rules for a particular stock and stock screening rules for portfolio formation. Warns of some potential problems but believes the system described meets the eight criteria set and is easy to implement.

The purpose of the paper is to analyze the effect on centralized dispatching generation cost under the condition where the single‐buyer electric supply industry (ESI) with independent power producer (IPP) scheme (the ESI structure that is widely implemented in developing countries) is opened for bilateral trading. The analysis is based on the Thai power system.

The analysis considers the average generation cost (B/kWh) derived from unit commitment of power generation under three cases – single‐buyer model with must‐run IPP scheme, unconstrained operation case, and the case where bilateral trading is introduced. The analysis is performed for different demand levels.

The results indicate that the operational constraint from the virtual must‐run power purchase agreement under IPP scheme leads to higher generation cost. The choice of allowing IPP to trade through bilateral trading and removal of the must‐run contract shows potential to lessen the operational constraint and lower generation cost can be achieved under some conditions – depending on the plant type and the share of bilateral market in the system. The planning and policy should take into consideration these conditions especially during the transitional period of ESI reform.

The main limitation of the analysis is the availability to recent data. The load factor of the demand curve is taken from the peak day of the year, resulting in higher load factor than the average of Thailand. With lower load factor, the must‐run constraints might be more obvious during the lighter load day and more expensive generation cost can be observed. However, the cases are compared at same demand curve. Therefore, the trend of result will lead to the same conclusion.

Uneconomic operation of the single‐buyer ESI with IPP scheme which has been implemented in many developing countries was clearly determined. The literature shows that the ESI operation can be more efficient when the sector moves towards higher degree of competition, either fully competitive market or bilateral trading. The potential for better operating conditions for bilateral trading has been suggested. The simulation based on the power system of Thailand can be an example for other developing countries operating under the similar ESI structure.

This paper aims to present a methodology for constructing cointegrated portfolios consisting of different cryptocurrencies and examines the performance of a number of trading strategies for the cryptocurrency portfolios.

The authors apply a series of statistical methods, including the Johansen test and Engle–Granger test, to derive a linear combination of cryptocurrencies that form a mean-reverting portfolio. Trading systems are designed and different trading strategies with stop-loss constraints are tested and compared according to a set of performance metrics.

The paper finds cointegrated portfolios involving four cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH) and Litecoin (LTC), and the corresponding trading strategies are shown to be profitable under different configurations.

The main contributions of the study are the use of multiple altcoins in addition to bitcoin to construct a cointegrated portfolio, and the detailed comparison of the performance of different trading strategies with and without stop-loss constraints.

The present study seeks to investigate the relative edge between the market microstructure of the two leading stock exchanges of the Indian capital market, that is BSE and NSE with a focus on analysing their trading mechanism, efficiency, liquidity and volatility.

We analyse the microstructure of BSE and NSE on the basis of: (1) trading mechanism – ownership structure, listing of securities, trading system and settlement and clearing process; (2) information efficiency using unit root test, serial correlation, runs test, variance ratio and the ARIMA model; (3) liquidity using trading statistics no. of listed Companies, market capitalisation, no. of trades etc. and (4) volatility using standard deviation and GARCH(1,1) model.

A comprehensive scrutiny on microstructure of BSE and NSE makes it evident that the two leading stock exchanges of India are mostly similar and leave no scope to choose between them. Both the exchanges are demutualised corporate entities with a fully automated trading system in an order-driven market, informationally inefficient as evidenced by the predictability of returns, have shown tremendously growing trading statistics and by and large a declining trend in volatility over the years.

Understanding the components of the microstructure black-box will provide the regulatory bodies with an intellectual framework to strengthen the market architecture. Both the exchanges will get aware of the dynamics of trading, can grow to be more competitive and attract more firms for listing and investors for trading of securities. Also, investors, portfolio managers and equity analysts will be able to make better investment strategies by understanding how the market works.

Research in the area of market microstructure has been severely neglected, especially in the context of the Indian market. India is the world's fastest growing economies and we have witnessed tremendous reforms in the capital market. The past two and a half decades have brought about several innovations via demutualisation, screen-based trading, emergence of clearing corporations, innovative financial products and intense use of IT in the Indian stock market. A spurt of reforms and the emerging environment make it crucial to deeply analyse the market structure and design of two premier stock exchanges of India – BSE and NSE.