GEM: A global electronic market system

The emergence and growing popularity of electronic commerce in general and Internet auctions in particular, has raised the challenge to explore scalable global electronic markets, involving both human and automated traders. While centralized auctions are believed to provide better economic results in conventional markets, a single auction server over the public Internet is not scalable and not reliable, due to the potential for very high load and because of the unpredictable and generally low network bandwidth, and it may not be feasible due to local autonomy constraints, which demand some degree of control over local trading policies. GEM is a Java based generic framework for decentralized Internet-based markets. It strives to balance the single-market abstraction, which is important for economic efficiency, with a geographically distributed physical market, which is essential for system efficiency, scalability and autonomy. This is done through the introduction of wide-area-oriented yet consistent distributed trading methods, and a scalable distributed architecture. The second main contribution of GEM is in the design of an individual (local) auction market. GEM provides a flexible architecture that delineates the abstract components of a generic market and specifies control and dataflow constraints between them, but allows variations in the concrete implementation of components with minimal or no impact on the implementation of other components. In addition, GEM provides dynamic (re)configuration and pluggability of policy components at runtime, which enables to adapt market policies to variations in trading patterns or system behavior, adding another level of flexibility to market designers and administrators.     

Law-abiding and integrity on the Internet: A case for agents

Software agents extend the current, information-based Internet to include autonomous mobile processing. In most countries such processes, i.e., software agents are, however, without an explicit legal status. Many of the legal implications of their actions (e.g., gathering information, negotiating terms, performing transactions) are not well understood. One important characteristic of mobile software agents is that they roam the Internet: they often run on agent platforms of others. There often is no pre-existing relation between the “owner” of a running agent’s process and the owner of the agent platform on which an agent process runs. When conflicts arise, the position of the agent platform administrator is not clear: is he or she allowed to slow down the process or possibly remove it from the system? Can the interests of the user of the agent be protected? This article explores legal and technical perspectives in protecting the integrity and availability of software agents and agent platforms.     

Using rough set to support investment strategies of real-time trading in futures market

Finding proper investment strategies in futures market has been a hot issue to everyone involved in major financial markets around the world. However, it is a very difficult problem because of intrinsic unpredictability of the market. What makes things more complicated is the advent of real-time trading due to recent striking advancement of electronic communication technology. The real-time data imposes many difficult tasks to futures market analyst since it provides too much information to be analyzed for an instant. Thus it is inevitable for an analyst to resort to a rule-based trading system for making profits, which is usually done by the help of diverse technical indicators. In this study, we propose using rough set to develop an efficient real-time rule-based trading system (RRTS). In fact, we propose a procedure for building RRTS which is based on rough set analysis of technical indicators. We examine its profitability through an empirical study.     

Toward a Programming Model for Building Reliable Systems with Distributed State

We present the preliminary design of a programming model for building reliable systems with distributed state from collections of potentially unreliable components. Our transactor model provides constructs for maintaining consistency among the states of distributed components. Our intention is that transactors should support key aspects of both traditional distributed transactions, e.g., for electronic commerce, and systems with weaker consistency requirements, e.g., peer-to-peer file- and process-sharing systems. In this paper, we motivate the need for language support for maintenance of distributed state, describe the design goals for the transactor model, provide an operational semantics for a simple transactor calculus, and provide several examples of applications of the transactor model in a higher-level language.The authors would like to thank James Leifer for detailed comments on previous drafts of this paper, and the anonymous FOCLASA referees for helpful feedback.     

数字货币交易匿名性与监管的博弈分析

By using technologies such as blockchain, digital currency, as a new type of monetary asset, has been promoting the development of digital economy. Digital currency trading platform plays an important role in the use of private digital currency by digital currency users. Existing digital currency trading platforms may expose users’ privacy and provide illegal elements with the conditions to participate in various abnormal trading behaviors such as “air dropping” events, extortion, fraud, etc. The strong anonymity protection of users by digital currency trading platforms also make it more difficult for regulatory authorities to supervise digital currency transactions. Therefore, the strength of the anonymity protection of users by digital currency trading platforms need to consider not only the privacy protection of users, but also meet the regulatory requirements. For this reason, based on the analysis of the relationship between the digital currency trading platforms and the supervisory departments, an evolutionary game model was established, the digital currency trading platform and the supervisory game model were defined and con-structed, and the replication dynamic equation was solved and the balanced solution was obtained according to the income matrix between the digital currency trading platform and the supervisory department. By building a Jacobian matrix, the stability of the evolutionary system under different parameters was analyzed. Besides, the evolutionary stable selection and strategy of the digital currency trading platform and the regulatory authority under different conditions were also analyzed. With Matlab, different strategies of anonymity protection of the digital currency trading platform and different strategies of supervision strategy of the regulatory department were simulated to veri-fy the accuracy of the game model. Based on the results of the simulations, some suggestions on the supervision of digital currency trading platforms are put forward, which provides a theoretical basis for the future supervision of digital currency trading platforms in China. © 2022, Beijing Xintong Media Co., Ltd.. All rights reserved.     

Collusion set detection using graph clustering

Many mal-practices in stock market trading—e.g., circular trading and price manipulation—use the modus operandi of collusion. Informally, a set of traders is a candidate collusion set when they have “heavy trading” among themselves, as compared to their trading with others. We formalize the problem of detection of collusion sets, if any, in the given trading database. We show that naïve approaches are inefficient for real-life situations. We adapt and apply two well-known graph clustering algorithms for this problem. We also propose a new graph clustering algorithm, specifically tailored for detecting collusion sets. A novel feature of our approach is the use of Dempster–Schafer theory of evidence to combine the candidate collusion sets detected by individual algorithms. Treating individual experiments as evidence, this approach allows us to quantify the confidence (or belief) in the candidate collusion sets. We present detailed simulation experiments to demonstrate effectiveness of the proposed algorithms.     

TRUST AS A TRADABLE COMMODITY: A FOUNDATION FOR SAFE ELECTRONIC MARKETPLACES

In large electronic marketplaces populated by buying and selling agents, it is difficult to judge trustworthiness. A variety of systems have been proposed to help traders to find trustworthy partners by learning to discount or disregard disreputable parties. In this article, we present a novel model for providing safe electronic marketplaces: Commodity Trunits, a system that considers trust as a tradable commodity. In this system, sellers require units of trust (trunits) to participate in transactions, and risk losing trunits if they act dishonestly. Sellers can purchase trunits when needed, and sell excess quantities. We demonstrate that under Commodity Trunits, rational sellers will choose to be honest, since this is the profit maximizing strategy. We also show that Commodity Trunits provides protection from a number of vulnerabilities common in existing trust and reputation systems, e.g., the important exit problem, where sellers can cheat without fear of repercussions if they intend to leave the market. We then present a simulation that validates the system by demonstrating that a market operator can manage the trunit marketplace to ensure sustainability. We conclude with a discussion of the value of Commodity Trunits as a method for promoting trust in electronic marketplaces.     

The role of algorithmic trading systems on stock market efficiency

The rapid development of information technology has changed the dynamics of financial markets. The main purpose of this study is laid on examining the role of IT based stock trading on financial market efficiency. This research specifically focused on algorithmic trading. Algorithmic trading enables investors to trade stocks through a computer program without the need for human interventions. Based on an empirical analysis of the Korean stock market, this study discovered the positive impact of algorithmic trading on stock market efficiency at three-fold. First, the study results indicate that algorithmic trading contributes to the reduction in asymmetric volatility, which causes inefficiency of information in a stock market. Second, an algorithmic trading also increases the operation efficiency of a stock market. Arbitrage trading contributes on the equilibrium between the spot market and futures market as well as on the price discovery. Third, algorithmic trading provides liquidity for market participants contributing to friction free transactions. The research results indicate that stock exchanges based on electronic communications networks (ECNs) without human intervention could augment a financial market quality by increasing trading share volumes and market efficiency so that it can eventually contribute to the welfare of market investors.     

An ontology for causal relationships between news and financial instruments

In recent years, people have begun to pay more and more attention to the effect of news on financial instrument markets (i.e., the markets for trading financial instruments). Researchers in the financial domain have conducted many studies demonstrating the effect of different types of news on trade activities in financial instrument markets such as volatility in trade price, trade volume, trading frequency, and so on. In this paper, an ontology for knowledge about news regarding financial instruments is provided. The ontology contains two parts: the first part presents a hierarchy framework for the domain knowledge that primarily includes classes of news, classes of financial instrument markets participants, classes of financial instruments, and primary relations between these classes. In the second part, a causal map is used to demonstrate how classes of news are causally related with classes of financial instruments. Finally, a case concerning the “9/11 American terror attack” is analyzed. On the basis of the ontology, it is first comprehensive to understand the knowledge about news in financial instrument markets; second, it helps building trading models based on news in the financial instrument markets; third, systems (e.g., systems for prediction of stock price based on news, systems for supporting financial market participants to search relevant news) design and development in this domain are facilitated and supported by this ontology.     

Scheduling Parallel Task Graphs on (Almost) Homogeneous Multicluster Platforms

Applications structured as parallel task graphs exhibit both data and task parallelism and arise in many domains. Scheduling these applications efficiently on parallel platforms has been a long-standing challenge. In the case of a single homogeneous platform, such as a cluster, results have been obtained both in theory, i.e., guaranteed algorithms, and, in practice, i.e., pragmatic heuristics. Due to task parallelism, these applications are well suited for execution on distributed platforms that span multiple clusters possibly in multiple institutions. However, the only available results in this context are nonguaranteed heuristics. In this paper, we develop a scheduling algorithm, MCGAS, which is applicable to multicluster platforms that are almost homogeneous. Such platforms are often found as large subsets of multicluster platforms. Our novel contribution is that MCGAS computes task allocations so that a (tunable) performance guarantee is provided. Since a performance guarantee does not necessarily imply good average performance in practice, we also compare MCGAS with a recently proposed nonguaranteed algorithm. Using simulation over a wide range of experimental scenarios, we find that MCGAS leads to better average application makespans than its competitor.     

Building Scalable Electronic Market Places Using HyperQuery-Based Distributed Query Processing

Flexible distributed query processing capabilities are an important prerequisite for building scalable Internet applications, such as electronic Business-to-Business (B2B) market places. Architecting an electronic market place in a conventional data warehouse-like approach by integrating all the data from all participating enterprises in one centralized repository incurs severe problems: stale data, data security threats, administration overhead, inflexibility during query processing, etc. In this paper we present a new framework for dynamic distributed query processing based on so-called HyperQueries which are essentially query evaluation sub-plans sitting behind hyperlinks. Our approach facilitates the pre-materialization of static data at the market place whereas the dynamic data remains at the data sources. In contrast to traditional data integration systems, our approach executes essential (dynamic) parts of the data-integrating views at the data sources. The other, more static parts of the data are integrated à priori at the central portal, e.g., the market place. The portal serves as an intermediary between clients and data providers which execute their sub-queries referenced via hyperlinks. The hyperlinks are embedded as attribute values within data objects of the intermediarys database. Retrieving such a virtual object will execute the referenced HyperQuery in order to materialize the missing data. We illustrate the flexibility of this distributed query processing architecture in the context of B2B electronic market places with an example derived from the car manufacturing industry.Based on these HyperQueries, we propose a reference architecture for building scalable and dynamic electronic market places. All administrative tasks in such a distributed B2B market place are modeled as Web services and are initiated decentrally by the participants. Thus, sensitive data remains under the full control of the data providers. We describe optimization and implementation issues to obtain an efficient and highly flexible data integration platform for electronic market places. All proposed techniques have been fully implemented in our QueryFlow prototype system which served as the platform for our performance evaluation.     

An intelligent hybrid trading system for discovering trading rules for the futures market using rough sets and genetic algorithms

Discovering intelligent technical trading rules from nonlinear and complex stock market data, and then developing decision support trading systems, is an important challenge. The objective of this study is to develop an intelligent hybrid trading system for discovering technical trading rules using rough set analysis and a genetic algorithm (GA). In order to obtain better trading decisions, a novel rule discovery mechanism using a GA approach is proposed for solving optimization problems (i.e., data discretization and reducts) of rough set analysis when discovering technical trading rules for the futures market. Experiments are designed to test the proposed model against comparable approaches (i.e., random, correlation, and GA approaches). In addition, these comprehensive experiments cover most of the current trading system topics, including the use of a sliding window method (with or without validation dataset), the number of trading rules, and the size of training period. To evaluate an intelligent hybrid trading system, experiments were carried out on the historical data of the Korea Composite Stock Price Index 200 (KOSPI 200) futures market. In particular, trading performance is analyzed according to the number of sets of decision rules and the size of the training period for discovering trading rules for the testing period. The results show that the proposed model significantly outperforms the benchmark model in terms of the average return and as a risk-adjusted measure.     

Hungary's Electronic Signature Act: Enhancing economic development with Secure Electronic Commerce transactions

Hungary's Electronic Signature Act (ESA) became effective in 2001 and provides for legal recognition of electronic signatures (e-signatures) and electronic documents. Electronic documents and e-signatures are presumed to be admissible evidence in court and may not be challenged successfully based on the mere fact of their electronic form. An electronic document signed with an e-signature is deemed to be in compliance with a statutory requirement for a handwritten signature on a paper document. However, the ESA excludes family-related documents (e.g., marriage certificates and divorce decrees), and those documents must continue to be in paper form to have legal validity. Also, consumers are not obligated to accept the electronic form; if a consumer objects, a business firm must use paper documents. Hungarian government departments may elect to issue or accept electronic documents. Although all types of e-signatures are recognized, the digital signature enjoys most-favored status because it utilizes cryptographic methods resulting in a heightened degree of reliability and security. The ESA provides for the licensure of certification authorities (CAs). In order to get a CA license, an applicant applies to the Hungarian Communications Inspector (Authority) and must meet financial and knowledge requirements and not have a prior criminal record. The principal duties of CAs are to issue certificates to successful applicants and confirm the authenticity and integrity of e-signatures (and the electronic documents to which they are attached) to relying third parties. Before issuance of the certificate, the CA must confirm the identity of the applicant and ensure that all information received on the application is accurate. The CA is responsible for maintaining the security of all information that it receives from the applicant. For a CA to issue a 'qualified' certificate it must comply with higher security standards; the only type of e-signature that can meet these standards is the digital signature. When a qualified certificate is issued, the subscriber will be given the private key that will enable them to 'sign' electronic documents. CAs must maintain a publicly accessible repository of certificates and public keys that can be used to decrypt a subscriber's message. A CA may incur legal liability for publishing a certificate with inaccurate information or for issuing a private key that does not have an interactive relationship with its public key. The ESA provides for legal recognition of certificates issued by CAs in foreign countries if the foreign CA meets one of the five criteria.     

Towards User‐Centered Active Learning Algorithms

The labeling of data sets is a time‐consuming task, which is, however, an important prerequisite for machine learning and visual analytics. Visual‐interactive labeling (VIAL) provides users an active role in the process of labeling, with the goal to combine the potentials of humans and machines to make labeling more efficient. Recent experiments showed that users apply different strategies when selecting instances for labeling with visual‐interactive interfaces. In this paper, we contribute a systematic quantitative analysis of such user strategies. We identify computational building blocks of user strategies, formalize them, and investigate their potentials for different machine learning tasks in systematic experiments. The core insights of our experiments are as follows. First, we identified that particular user strategies can be used to considerably mitigate the bootstrap (cold start) problem in early labeling phases. Second, we observed that they have the potential to outperform existing active learning strategies in later phases. Third, we analyzed the identified core building blocks, which can serve as the basis for novel selection strategies. Overall, we observed that data‐based user strategies (clusters, dense areas) work considerably well in early phases, while model‐based user strategies (e.g., class separation) perform better during later phases. The insights gained from this work can be applied to develop novel active learning approaches as well as to better guide users in visual interactive labeling.     

Electronic multilateral trade of electricity

This paper presents a technical approach for electronic multilateral trade of electricity in competitive power industries. The trade involves strategic sharing of data among agents in an attempt to provide the opportunity to intelligently discover competitive behavior of peer suppliers. A trading logic is implemented as a specialized software module within the agent. The logic mimics intelligence of the human strategic trade. A time-bounded trade protocol has been introduced as a trading basis among rivalry trade agents in the market. The protocol limits the trade rounds in order to bind the trading process to specific deadlines. The protocol is coded as part of the automated trade server. The results of a generic 3-bus test system show that the electronic multilateral trade logic presented in this paper better distributes market sales, lowers prices and consequently provides higher social welfare compared to the standard Cournot economic model that may be used by the human decision-maker for market trading. Based on a set of test cases with different load profiles, it is noted that the electronic multilateral trade drives the market price closer to the marginal cost of generation supply and far away from the estimated Cournot price.     

Traditional and Online IPO Processes: Are there Differences in after-Market Trading and Market Making?

In this study we compare the after-market trading and market making activities of a sample of Nasdaq online initial public offerings (IPOs) to a matched sample of traditional IPOs. We find that online IPOs have significantly higher turnover in after-market trading, and more market makers, dealers, and electronic communications networks servicing their trading activities than traditional IPOs. We find no difference between the samples in after-market volumes, block trades, or the number of dealers actually engaged in trading. We believe this provides some support for the notion that distribution of IPOs to online customers facilitates liquidity in the after-market, at least for the smaller investor. We also believe that the evidence implies that control of the after-market trading is still in the hands of the institutional investor and that the advantages the Internet offers as a global communication network are at this point not being fully utilized.     

Performance modeling of distributed and replicated databases

The paper surveys performance models for distributed and replicated database systems. Over the last 20 years (1980-2000), a variety of such performance models have been developed and they differ in: (1) which aspects of a real system are or are not captured in the model (e.g., replication, communication, nonuniform data access, etc.); and (2) how these aspects are modeled. We classify the different alternatives and modeling assumptions and discuss their interdependencies and expressiveness for the representation of distributed databases. This leads to a set of building blocks for analytical performance models. To illustrate the work that is surveyed, we select a combination of these proven modeling concepts and give an example of how to compose a balanced analytical model of a replicated database. We use this example to show how to derive meaningful performance values and to discuss the applicability and expressiveness of performance models for distributed and replicated databases. Finally, we compare the analytical results to measurements in a distributed database system     

IBIZA: E-market Infrastructure for Custom-built Information Products

The merger of electronic commerce, intelligent agent and distributed computing technologies over TCP/IP-based platforms enables the creation of electronic markets in new types of products featuring both human and software agents as actors. One such example is a market in custom-built information products. These are information products that have been constructed to meet specific requirements provided by the consumer. Examples include custom research reports, analysis, and computational objects. How should these markets be designed? What are the market mechanisms that should be used to coordinate the interactions between the actors? What should be the decision strategies employed by the software agents that participate in the market? IBIZA is a computational workbench that enables designers to create and simulate electronic markets in information products. It provides a repository of software agents, bidding strategies, brokering strategies and market mechanisms. Using the repository, designers can instantiate particular designs of electronic markets and conduct experiments to study the impact of design decisions on desired objectives. In this paper, we focus on the key technical and economic issues encountered in the design of IBIZA. We illustrate using examples from our work on designing a software agent-based electronic market for automated model development.     

OBIWAN: design and implementation of a middleware platform

Programming distributed applications supporting data sharing is very hard. In most middleware platforms, programmers must deal with system-level issues for which they do not have the adequate knowledge, e.g., object replication, abusive resource consumption by mobile agents, and distributed garbage collection. As a result, programmers are diverted from their main task: the application logic. In addition, given that such system-level issues are extremely error-prone, programmers spend inumerous hours debugging. We designed, implemented, and evaluated a middleware platform called OBIWAN that releases the programmer from the above mentioned system-level issues. OBIWAN has the following distinctive characteristics: 1) allows the programmer to develop applications using either remote object invocation, object replication, or mobile agents, according to the specific needs of applications, 2) supports automatic object replication (e.g., incremental on-demand replication, transparent object faulting and serving, etc.), 3) supports distributed garbage collection of useless replicas, and 4) supports the specification and enforcement of history-based security policies well adapted to mobile agents needs (e.g., preventing abusive resource consumption).     

Designing Agent-Based Electronic Employment Markets

Two modes of matching people with jobs prevail at present: 1) hierarchical planning and 2) distributed markets. Each has strengths and limitations, but few systems have been designed to take advantage of strengths corresponding to both. With evolving information technology, however, the job-matching process could be accomplished far more equitably and efficiently using web-based markets within the firm, and intelligent agents offer excellent potential to help both potential employees and employers find one another in a distributed, electronic marketplace. But realizing this potential goes well beyond simply changing the rules of internal job matching or making agent technology available to job searchers. Rather, the corresponding markets and technologies must be designed, together, to mutually accomplish the desired results (e.g., efficient and effective matching) and conform to necessary properties (e.g., market clearing). Through the research described in this paper, we draw from Game Theory results to assess the feasibility of using two-sided matching algorithms to address this market-design problem. We also draw from current agent research to address the information technology dimension of the problem by implementing a proof-of-concept multi-agent system to enact, automate and support the corresponding market solution. This paper integrates the key economic and technological elements required to design robust electronic employment markets. And the corresponding research provides new knowledge and insight into co-development of the requisite economic markets and agent technologies.