Alić, Irina

[["dc.bibliographiccitation.firstpage","16"],["dc.bibliographiccitation.journal","BLED Proceedings"],["dc.bibliographiccitation.lastpage","31"],["dc.bibliographiccitation.volume","36"],["dc.contributor.author","Alić, Irina"],["dc.date.accessioned","2020-03-03T11:27:01Z"],["dc.date.available","2020-03-03T11:27:01Z"],["dc.date.issued","2015"],["dc.description.abstract","In this paper, an IT artifact instantiation (i.e. software prototype) to support decision making in the field of financial market surveillance, is presented and evaluated. This artifact utilizes a qualitative multi-attribute model to identify situations in which prices of single stocks are affected by fraudsters who aggressively advertise the stock. A quantitative evaluation of the instantiated IT artifact, based on voluminous and heterogeneous data including data from social media, is provided. The empirical results indicate that the developed IT artifact instantiation can provide support for identifying such malicious situations. Given this evidence, it can be shown that the developed solution is able to utilize massive and heterogeneous data, including user-generated content from financial blogs and news platforms, to provide practical decision support in the field of market surveillance."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63076"],["dc.language.iso","en"],["dc.publisher","AIS Electronic Library (AISeL)"],["dc.relation.conference","28th Bled eConference"],["dc.relation.eventend","2015-06-10"],["dc.relation.eventlocation","Bled, Slovenia"],["dc.relation.eventstart","2015-06-07"],["dc.title","Supporting Financial Market Surveillance: An ITArtifact Evaluation"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Alić, Irina"],["dc.date.accessioned","2020-03-03T14:22:31Z"],["dc.date.available","2020-03-03T14:22:31Z"],["dc.date.issued","2013"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63084"],["dc.language.iso","en"],["dc.relation.conference","twelfth Annual Pre-ICIS HCI/MIS Research Workshop"],["dc.relation.eventend","2013-12-15"],["dc.relation.eventlocation","Milano, Italy"],["dc.relation.eventstart","2013-12-15"],["dc.relation.ispartof","Proceedings of the Pre-ICIS SIGDSS Research Workshop"],["dc.title","Market Surveillance DSS: Towards an Explanatory Design Theory"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","127"],["dc.bibliographiccitation.journal","BLED Proceedings"],["dc.bibliographiccitation.lastpage","139"],["dc.contributor.author","Alic, Irina"],["dc.date.accessioned","2020-02-25T14:59:24Z"],["dc.date.available","2020-02-25T14:59:24Z"],["dc.date.issued","2015"],["dc.description.abstract","In this paper, an explanatory design theory for Financial Market Surveillance Systems is presented, which addresses both user requirements and regulatory demands. The identified general requirements and generated general components of the proposed design theory provides a theoretical foundation for design of implementation of highly flexible and real-time surveillance systems for capital markets."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63021"],["dc.language.iso","en"],["dc.relation.conference","28 th Bled eConference"],["dc.relation.eventend","2015"],["dc.relation.eventlocation","Bled, Slovenia"],["dc.relation.eventstart","2015"],["dc.title","Financial Market Surveillance Decision Support: An Explanatory Design Theory"],["dc.title.subtitle","Financial Market Surveillance Decision Support:An Explanatory Design Theory"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","257"],["dc.bibliographiccitation.journal","Americas Conference on Information Systems"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Zülch, Mirko Jan"],["dc.contributor.author","Alić, Irina"],["dc.contributor.author","Muntermann, Jan"],["dc.date.accessioned","2020-02-05T13:42:27Z"],["dc.date.available","2020-02-05T13:42:27Z"],["dc.date.issued","2011"],["dc.description.abstract","To satisfy legal requirements, listed companies are required to continuously publish a wide range of disclosures and reports.Regulatory authorities such as the SEC in the US or the FSA in the UK have developed a complex set of rules andregulations that aim at expanding transparency of capital markets. Therefore, corporations hire professional editorial teams,often being supported by financial service communication consultancies. While the regulatory objective is to increasetransparency, the management has an inherent motivation to give the reports a positive spin. We aim to explore this conflictby analyzing the sentiment of corporate disclosures and to compare this tone with the price reactions following thedisclosures’ publication. On the basis of an empirical analysis of intraday stock price reactions and word lists which providemeans to assess the tone of documents, our results provide evidence that corporates follow a strategy to positively adjust theirexternal reporting."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62946"],["dc.language.iso","en"],["dc.relation.conference","Seventeenth Americas Conference on Information Systems"],["dc.relation.eventend","2011-08-07"],["dc.relation.eventlocation","Detroit, Michigan"],["dc.relation.eventstart","2011-08-04"],["dc.relation.ispartof","Proceedings of the Seventeenth Americas Conference on Information Systems"],["dc.title","How \"good\" is bad News? Exploring Sentiments of Corporate Disclosures"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.lastpage","12"],["dc.contributor.author","Alić, Irina"],["dc.date.accessioned","2020-03-03T13:05:23Z"],["dc.date.available","2020-03-03T13:05:23Z"],["dc.date.issued","2014"],["dc.description.abstract","In this paper, an IT artifact instantiation to support decision making in the field of financial market surveillance, is presented. This artifact utilizes a qualitative multi-attribute decision model to identify situations in which prices of single stocks are affected by fraudsters who aggressively advertise the stock. A quantitative evaluation of the implemented system prototype, based on voluminous and heterogeneous data including data from social media, is provided. The empirical results indicate that that the developed IT artifact can provide support for identifying such malicious situations. Given this evidence, it can be shown that the developed solution is able to utilize massive and heterogeneous data, especially usergenerated content from financial blogs and news platforms, to provide practical decision support in the field of market surveillance."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63080"],["dc.language.iso","en"],["dc.notes.preprint","yes"],["dc.relation.conference","20th Americas Conference on Information Systems, AMCIS 2014"],["dc.relation.eventend","2014-08-09"],["dc.relation.eventlocation","Savannah, Georgia, USA"],["dc.relation.eventstart","2014-08-07"],["dc.relation.iserratumof","yes"],["dc.title","Don’t Jump on Hype or You Will be Dumped! Using User-Generated Content to Support Financial Market Surveillance"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","1"],["dc.bibliographiccitation.firstpage","280"],["dc.bibliographiccitation.journal","BLED Proceedings"],["dc.bibliographiccitation.lastpage","293"],["dc.bibliographiccitation.volume","2012"],["dc.contributor.author","Alić, Irina"],["dc.contributor.author","Muntermann, Jan"],["dc.contributor.author","Gregory, Robert W."],["dc.date.accessioned","2020-02-05T08:48:38Z"],["dc.date.available","2020-02-05T08:48:38Z"],["dc.date.issued","2012"],["dc.description.abstract","Financial decision support has become an important information systems research topic and is also of highest interest to practitioners. Two rapidly emerging trends, the increasing amount of available data and the evolution of data mining methods, pose challenges for researchers. Thus, a review of existing research with the goal to guide future research efforts in this domain is timely. To structure our literature review and future research in this area, we propose a framework in the paper that integrates elements of decision support systems, design theory, and information mining. The framework is then applied in the paper. Our analysis reveals that the focus of existing research can be grouped into three major domain categories. More research is needed in two of the categories for which we found only very few IS studies, despite the high relevance of these topics due to increased turbulences in worldwide financial markets. Furthermore, we discuss the opportunities to make stronger use of heterogeneous data and of combined data mining techniques and to build upon the rich set of available evaluation methods."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62943"],["dc.identifier.url","http://elibrary.aisnet.org/Default.aspx?url=https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1042&context=bled2012"],["dc.language.iso","en"],["dc.publisher","Association for Information Systems AIS Electronic Library (AISeL)"],["dc.relation.conference","25th Bled eConference eDependability: Reliable and Trustworthy eStructures, eProcesses, eOperations and eServices for the Future"],["dc.relation.eventend","2012-06-20"],["dc.relation.eventlocation","Bled, Slovenia"],["dc.relation.eventstart","2012-06-17"],["dc.title","State of the Art of Financial Decision Support Systems based on Problem, Requirement, Component and Evaluation Categories"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","64"],["dc.bibliographiccitation.journal","BLED Proceedings"],["dc.bibliographiccitation.lastpage","77"],["dc.bibliographiccitation.volume","2013"],["dc.contributor.author","Alić, Irina"],["dc.contributor.author","Siering, Michael"],["dc.contributor.author","Bohanec, Marko"],["dc.date.accessioned","2020-03-03T15:12:09Z"],["dc.date.available","2020-03-03T15:12:09Z"],["dc.date.issued","2013"],["dc.description.abstract","The emergence of online financial information channels, such as web portals and financial blogs, eases the challenge process for scammers of publishing fraudulent contents in order to manipulate share prices. To maintain market integrity, financial market surveillance authorities monitor these different information channels to detect suspicious behaviour. However, as the available amount of online information increases, analyses become more costly and time-consuming. In order to support related decisions, we have developed a model to identify fraudulent situations. Based on interviews with domain experts, we first identified the factors determining suspicious situations and then applied a qualitative multi-attribute modelling technique. Thereby, our resulting model builds upon valuable knowledge of domain experts and provides means to address the challenge of information based market manipulation."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63085"],["dc.language.iso","en"],["dc.relation.conference","26th Bled eConference eInnovations: Challenges and Impacts for Individuals, Organizations and Society"],["dc.relation.eventend","2013-06-13"],["dc.relation.eventlocation","Bled, Slovenia"],["dc.relation.eventstart","2013-06-09"],["dc.title","Hot Stock or Not? A Qualitative Multi-Attribute Model to Detect Financial Market Manipulation"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.contributor.advisorcorporation","Georg-August-Universität Göttingen"],["dc.contributor.author","Alić, Irina"],["dc.date.accessioned","2020-01-29T10:12:13Z"],["dc.date.available","2020-01-29T10:12:13Z"],["dc.date.issued","2017"],["dc.description.abstract","Financial decision support systems have become an important research topic and are also of great interest to practitioners. On one hand, the financial regulatory authorities are faced with tracking an increasing amount of online information published on financial blogs and news in order to maintain financial market surveillance. On the other hand, two rapidly emerging trends, the increasing amount of available data and the evolution of data mining methods, pose challenges for researchers. Financial decision support sys-tems can aid decision making by providing the authorities with relevant information in a timely fashion. This thesis presents IT artifacts that can support financial market surveil-lance decision making. Furthermore, an explanatory design theory is provided that ad-dresses the requirements posed by the regulatory authorities and compliance officers in financial institutions."],["dc.description.abstract","Entscheidungsunterstützungssysteme in der Finanzwirtschaft sind nicht nur für die Wis-senschaft, sondern auch für die Praxis von großem Interesse. Um die Finanzmarktüber-wachung zu gewährleisten, sehen sich die Finanzaufsichtsbehörden auf der einen Seite, mit der steigenden Anzahl von onlineverfügbaren Informationen, wie z.B. den Finanz-Blogs und -Nachrichten konfrontiert. Auf der anderen Seite stellen schnell aufkommen-de Trends, wie z.B. die stetig wachsende Menge an online verfügbaren Daten sowie die Entwicklung von Data-Mining-Methoden, Herausforderungen für die Wissenschaft dar. Entscheidungsunterstützungssysteme in der Finanzwirtschaft bieten die Möglichkeit rechtzeitig relevante Informationen für Finanzaufsichtsbehörden und Compliance-Beauftragte von Finanzinstituten zur Verfügung zu stellen. In dieser Arbeit werden IT-Artefakte vorgestellt, welche die Entscheidungsfindung der Finanzmarktüberwachung unterstützen. Darüber hinaus wird eine erklärende Designtheorie vorgestellt, welche die Anforderungen der Regulierungsbehörden und der Compliance-Beauftragten in Finan-zinstituten aufgreift."],["dc.format.extent","121"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62874"],["dc.language.iso","en"],["dc.publisher","eDISS"],["dc.publisher.place","Göttingen"],["dc.title","Decision Support Systems for Financial Market Surveillance"],["dc.type","thesis"],["dc.type.internalPublication","yes"],["dc.type.subtype","dissertation"],["dspace.entity.type","Publication"]]