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The paper aims to investigate order-based manipulation that consists of order-placing strategies.

Using the bid and ask record provided by Hong Kong Exchanges and Clearing Limited, a Level II dataset, the paper develops a methodology to obtain cancelled orders during regular trading hours. The paper examines the cancelled orders and potential order-based manipulation activities, as well as the corresponding behavior of different groups of stocks.

Empirical results show that the relationship between order cancellation and order-based manipulation is strong and deserves more attention.

The methodology can also be used by regulators and authorities to monitor suspicious activities in the market. This paper also suggests that analysis on high-frequency data does improve the understanding of trading activities in the stock market.

This paper aims to show that market power exists in financial markets and analyze how spoofing is used by a high-frequency trader to build market power by taking advantage of both behavioral weaknesses of individual investors and microstructural loopholes of trading venues.

After showing that market power exists in the financial market, this paper centers around the question of how market power is constructed in the financial market. To sharpen the answer to the question, the paper compares the conditions needed for market power construction in the financial market with those needed in the goods market. The paper selects spoofing, the frequently used order-based tactic in high-frequency trading strategies, to analyze in detail how spoof orders can ignite herding with market power building as the essence. The Flash Crash that occurred in the New York Stock Exchange on May 6, 2010 provides an excellent case of market power construction exhibited in spoofing.

The behavioral mechanism of market power construction in the case of spoofing is perception alignment. It becomes effective when two necessary conditions are met: the spoof trader takes advantage of the incomplete order display set up by the exchange; and the behavioral weaknesses exhibited by numerous individual investors. In addition to these key conditions, this paper finds other ones for market power to be created in the financial market. They are easier, quicker, more secret, more flexible and less risky relative to the conditions for market power building in the goods market.

The detailed analysis points to the behavioral mechanism, i.e. perception alignment, and microstructural mechanism, i.e. incomplete order display, that could be responsive to regulation.

The originality of the findings is to uncover the mechanism of spoofing in taking advantage of behavioral biases of individual investors. The value is to gain more complete understanding of the essence of herding caused by spoofing.

The purpose of this study is to empirically test the role of heterogeneous investor’s, i.e. institutional investors, individuals and insiders in deteriorating market integrity.

The research is conducted by examining the participants of 244 market manipulation cases of East Asian emerging and developed financial markets for the period of 2001–2016. The empirical analysis is conducted using panel logistic regression.

The results show that firms with higher institutional ownership are most likely to be manipulated in both markets. Insiders are potential manipulators in developed markets and deteriorate market integrity. In contrast, individual investors behave differently in both markets. In developed markets, firms with high individual ownership are less likely to be manipulated while in emerging markets, firms with individual ownership are more prone to manipulation because of substantial participation by individual investors which invites manipulative practices. Additionally, the authors found that firms with a higher proportion of passive institutional investors are less likely to be manipulated in emerging markets.

This study contributes to the existing literature by identifying the potential manipulators in the financial markets who deteriorate market integrity with the additional focus of subdivision of institutional investors as active institutional investors and passive institutional investor. The findings are helpful for regulators in designing policies to ensure market integrity and to enforce the role of institutional investors and insiders.

This article aims to contribute to the accounting knowledge literature by presenting the framework of creative accounting factors and evaluating their identified factors through an argumentation-based total interpretive structural modeling (TISM) approach.

This study adopted mixed, inductive and deductive approaches to develop an integrated framework, validate its practicability and verify its effectiveness in selected manufacturing firms listed on the Tehran Stock Exchange (TSE), respectively. In developing the framework and implementation procedure, the study employed an exploratory data collection (qualitative) approach to review the phenomenon of creative accounting factors. Then, in this study’s second phase, TISM is used to develop the framework of creative accounting design. This study used two types of theoretical sampling in the qualitative part, including theoretical and snowball sampling. Also, the participants in the TISM process in this study were specialized analysts of the TSE.

Based on the mixed method of this study, the result in the qualitative part provides the creative accounting framework of the existence of three categories. There are 6 components and 35 themes during 12 interviews. In the quantitative section, it was determined that two factors, namely the type of ownership firms and intrinsic objectivity, are the most effective drivers for the formation of creative accounting in TSE firms.

So far, it is rare to find preceding studies that have proposed, validated and practically tested an integrated creative accounting framework within the context of financial markets. Thus, the authors understand that this is the very first research focused on the development of a framework for capital market companies to continuously be competitive and could help financial decision-makers, practitioners and academicians in their perception of knowing more about the financial functions of firms.

Although considerable evidence shows that online product reviews (OPRs) can greatly affect consumers, how interface designs of OPR systems (i.e. websites where consumers read and write OPRs) impact online buying behavior has not yet been well investigated. Using research on confidence in judgment and the Stimulus-Organism-Response (SOR) framework, this study aims to develop a model of the effects of OPR system design on consumer purchase behavior.

A study using a two by two by two factorial experimental design was conducted. The structural model with AMOS 23 based on 319 useable data points was tested.

Findings are very interesting. First, designs that manipulate positions of reviews impact perceived value but surprisingly have no effects on confidence in judgment. Second, designs using default display order based on helpfulness votes rather than on recency of reviews increase confidence to a higher level. Third, although unstructured organization methods are used by many major OPR systems, they are inferior in enhancing consumers’ emotional reactions to structured ones.

This paper highlights the need for more academic research on how interface designs of online product review systems impact purchase behavior. Additionally, this study emphasizes the need for examining how confidence in judgment is impacted in the online environment.

For practitioners, this research provides them with design implications on how to increase consumer purchase behavior.

This research enhances the understanding of the effects of OPR system interface design on purchase behavior. In addition, the current paper sheds light on how confidence in judgment, given its importance in reducing online consumer’s hesitance to buy, is impacted by various interface designs of OPR systems. Furthermore, this study applies the SOR framework to the context of OPR system designs.

The purpose of this paper is to introduce an expressive query language, called relational XML query language (RXQL), capable of dealing with heterogeneous Extensible Markup Language (XML) documents in data‐centric applications. In RXQL, data harmonization (i.e. the removal of heterogeneous factors from XML data) is integrated with typical data‐centric features (e.g. grouping, ordering, and aggregation).

RXQL is based on the XML relation representation, developed in the authors' previous work. This is a novel approach to unambiguously represent semistructured data relationally, which makes it possible in RXQL to manipulate XML data in a tuple‐oriented way, while XML data are typically manipulated in a path‐oriented way.

The user is able to describe the result of an RXQL query straightforwardly based on non‐XML syntax. The analysis of this description, through the mechanism developed in this paper, affords the automatic construction of the query result. This feature increases significantly the declarativeness of RXQL compared to the path‐oriented XML languages where the user needs to control the construction of the result extensively.

The authors' formal specification of the construction of the query result can be considered as an abstract implementation of RXQL.

RXQL is a declarative query language capable of integrating data harmonization seamlessly with other data‐centric features in the manipulation of heterogeneous XML data. So far, these kinds of XML query languages have been missing. Obviously, the expressive power of RXQL can be achieved by computationally complete XML languages, such as XQuery. However, these are not actual query languages, and the query formulation in them usually presupposes programming skills that are beyond the ordinary end‐user.

Estimating the sizes of query results and intermediate results is crucial to many aspects of query processing. All database systems rely on the use of cardinality estimates to choose the cheapest execution plan. In principle, the problem of cardinality estimation is more complicated in the Extensible Markup Language (XML) domain than the relational domain. The purpose of this paper is to present a novel framework for estimating the cardinality of XQuery expressions as well as their sub‐expressions. Additionally, this paper proposes a novel XQuery cardinality estimation benchmark. The main aim of this benchmark is to establish the basis of comparison between the different estimation approaches in the XQuery domain.

As a major innovation, the paper exploits the relational algebraic infrastructure to provide accurate estimation in the context of XML and XQuery domains. In the proposed framework, XQuery expressions are translated into an equivalent relational algebraic plans and then using a well defined set of inference rules and a set of special properties of the algebraic plan, this framework is able to provide high‐accurate estimation for XQuery expressions.

This paper is believed to be the first which provides a uniform framework to estimate the cardinality of more powerful XML querying capabilities using XQuery expressions as well as their sub‐expressions. It exploits the relational algebraic infrastructure to provide accurate estimation in the context of XML and XQuery domains. Moreover, the proposed framework can act as a meta‐model through its ability to incorporate different summarized XML structures and different histogram techniques which allows the model designers to achieve their targets by focusing their effort on designing or selecting the adequate techniques for them. In addition, this paper proposes benchmark for XQuery cardinality estimation systems. The proposed benchmark distinguishes itself from the other existing XML benchmarks in its focus on establishing the basis for comparing the different estimation approaches in the XML domain in terms of their accuracy of the estimations and their completeness in handling different XML querying features.

The current status of this proposed XQuery cardinality estimations framework does not support the estimation of the queries over the order information of the source XML documents and does not support non‐numeric predicates.

The experiments of this XQuery cardinality estimation system demonstrate its effectiveness and show high‐accurate estimation results. Utilizing the cardinality estimation properties during the SQL translation of XQuery expression results in an average improvement of 20 percent on the performance of their execution times.

This paper presents a novel framework for estimating the cardinality of XQuery expressions as well as its sub‐expressions. A novel XQuery cardinality estimation benchmark is introduced to establish the basis of comparison between the different estimation approaches in the XQuery domain.

Post 9/11 events not only exposed the visible and invisible aspects of the often intertwined self‐interest of political, economic and especially religious elites, but also presented a practical and ideological vacuum susceptible to “once and for all” opportunistic fantasies of ultra and Neo‐conservative, cum religious, fanatics. The purpose of this paper is to counter balance the constant flow of Neo‐liberal and religious‐fundamentalist propaganda that is having a destructive effect on hard‐won civil ideals and democratic freedoms.

This paper presents a study of the relationship between visible and invisible power in the context of a historical study of the great age of tolerance and co‐existence between Jews, Muslims and Christians. The paper uses Benvenisti's “double history” methodology to recover what is visible on the surface and the “buried history” of what is invisible to discern the implications the Spanish Convivencia has for contemporary debates over political and religious “purity”.

This paper discovers dangerous signs of a continuing ahistorical hubris amongst elites and others that denies the historical evidence for the possibility of mutual accommodations between political and religious communities. This paper locates the need to recover lost, or discounted, multiple histories and (in)visible portents of a future other than the triumphalism of Western, especially “exceptionalist” US interests.

This paper demonstrates the need for more research into the use/misuse of historical evidence within (in)visible power mechanisms designed to serve ideological and hegemonic interests.

In our uncertain age, this paper is notable for developing a historically grounded vision of a real‐politic new world order based on mutual accommodation and respect.

The purpose of this paper is to assess the US Securities and Exchange Commission’s new regulation, Limit Up–Limit Down (LULD), against the background of manipulative high-frequency trading (HFT).

This paper examines the background of HFT and related manipulative tactics by reviewing 43 articles of empirical research. It also examines areas in which LULD is effective and those in which LULD fails. The assessment of LULD is completed with a comparison between computerized regulation and legal enforcement in the contemporary reality of electronic trading platforms.

The paper points out the effectiveness of LULD in regulating wild price volatility as well as its insufficiency when facing orderly but fast price momentum ignited by manipulative HFT such as “spoofing”.

The findings may provide assistance to lawmakers and regulators to improve LULD regulation.

This paper is the first attempt to assess LULD regulation against a comprehensive background of manipulative HFT. The paper is of value to other researchers concerned about the instability to the equity market that manipulative HFT can create. The paper is also of interest to policymakers in designing effective regulation in the high-frequency era.

The purpose of this paper is to explore the dark side of news community forums: the proliferation of opinion manipulation trolls. In particular, it explores the idea that a user who is called a troll by several people is likely to be one. It further demonstrates the utility of this idea for detecting accused and paid opinion manipulation trolls and their comments as well as for predicting the credibility of comments in news community forums.

The authors are aiming to build a classifier to distinguish trolls vs regular users. Unfortunately, it is not easy to get reliable training data. The authors solve this issue pragmatically: the authors assume that a user who is called a troll by several people is likely to be such, which are called accused trolls. Based on this assumption and on leaked reports about actual paid opinion manipulation trolls, the authors build a classifier to distinguish trolls vs regular users.

The authors compare the profiles of paid trolls vs accused trolls vs non-trolls, and show that a classifier trained to distinguish accused trolls from non-trolls does quite well also at telling apart paid trolls from non-trolls.

The troll detection works even for users with about 10 comments, but it achieves the best performance for users with a sizable number of comments in the forum, e.g. 100 or more. Yet, there is not such a limitation for troll comment detection.

The approach would help forum moderators in their work, by pointing them to the most suspicious users and comments. It would be also useful to investigative journalists who want to find paid opinion manipulation trolls.

The authors can offer a better experience to online users by filtering out opinion manipulation trolls and their comments.

The authors propose a novel approach for finding paid opinion manipulation trolls and their posts.