The thesis introduces a framework for analysing market monitoring and surveillance systems in order to provide a common foundation for researchers and practitioners to specify, design, implement, compare and evaluate such systems. The proposed framework serves as a reference map for researchers and practitioners to position their work in the context of market monitoring and surveillance, resulting in a useful instrument for the analysis, testing and management of such systems. More specifically, the thesis examines the new requirements for the operation of financial markets, the role of technologies, the recent consultations on the structure and governance of EU and US markets, as well as, future usage scenarios and emerging technologies. It examines the context in which market monitoring and market surveillance systems are currently been used. It reports on their processes, performance, and on the organisational and regulatory environments in which they exist. Furthermore, it develops a set of taxonomies which cover the majority of the concepts of market manipulation, market monitoring, market surveillance, entities, technologies and actors that are relevant for the work in this thesis. Building on the gaps and limitations of the current systems, it proposes a new framework following the Design Science methodology. The usefulness of the framework is evaluated through four critical case studies, which not only help to understand with practical exercises the way how markets monitoring and surveillance systems work, but also to investigate their weaknesses, potential evolution and ways to improve them. For each case study, the thesis develops a fully working prototype tested using a sample prosecution case and evaluated in terms of the appropriateness and suitability of the proposed framework. Finally, implications relating to policies, procedures and future market structures are discussed followed by suggestions for future research.

In recent years, financial trading has become more available. This has led to more market participants and more trades taking place each day. The increased activity also implies an increasing number of abusive trades. To detect the abusive trades, market surveillance systems are developed and used. In this thesis, two different methods were tested to detect these abusive trades on high-dimensional data. One was based on empirical quantiles, and the other was based on an unsupervised machine learning technique called isolation forest. The empirical quantile method uses empirical quantiles on dimensionally reduced data to determine if a datapoint is an outlier or not. Principal Component Analysis (PCA) is used to reduce the dimensionality of the data and handle the correlation between features.Isolation forest is a machine learning method that detects outliers by sorting each datapoint in a tree structure. If a datapoint is close to the root, it is more likely to be an outlier. Isolation forest have been proven to detect outliers in high-dimensional datasets successfully, but have not been tested before for market surveillance. The performance of both the quantile method and isolation forest was tested by using recall and run-time.  The conclusion was that the empirical quantile method did not detect outliers accurately when all dimensions of the data were used. The method most likely suffered from the curse of dimensionality and could not handle high dimensional data. However, the performance increased when the dimensionality was reduced. Isolation forest performed better than the empirical quantile method and detected 99% of all outliers by classifying 226 datapoints as outliers out of a dataset with 184 true outliers and 1882 datapoints. / Under de senaste åren har finansiell handel blivit mer tillgänglig för allmänheten. Detta har lett till fler deltagare på marknaderna och att fler affärer sker varje dag. Den ökade aktiviteten innebär också att de missbruk som förekommer ökar. För att upptäcka otillåtna affärer utvecklas och används marknadsövervakningssystem. I den här avhandlingen testades två olika metoder för att upptäcka dessa missbruk utifrån högdimensionell data. Den ena baserades på empiriska kvantiler och den andra baserades på en oövervakad maskininlärningsteknik som kallas isolationsskog. Den empiriska kvantilmetoden använder empiriska kvantiler på dimensionellt reducerad data för att avgöra om en datapunkt är ett extremvärde eller inte. För att reducera dimensionen av datan, och för att hantera korrelationen mellan variabler, används huvudkomponent analys (HKA).Isolationsskog är en maskininlärnings metod som upptäcker extremvärden genom att sortera varje datapunkt i en trädstruktur. Om en datapunkt är nära roten är det mer sannolikt att det är en extremvärde. Isolationsskog har visat sig framgångsrikt upptäcka extremvärden i högdimensionella datauppsättningar, men har inte testats för marknadsövervakning tidigare. För att mäta prestanda för båda metoderna användes recall och körtid. Slutsatsen är att den empiriska kvantilmetoden inte hittade extremvärden när alla dimensioner av datan användes. Metoden led med största sannolikhet av dimensionalitetens förbannelse och kunde inte hantera högdimensionell data, men när dimensionaliteten reducerades ökade prestandan. Isolationsskog presterade bättre än den empiriska kvantilmetoden och lyckades detektera 99% av alla extremvärden genom att klassificera 226 datapunkter som extremvärden ur ett dataset med 184 verkliga extremvärden och 1882 datapunkter.

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.

在各國政府部門為減輕財政負擔、提高行政效能，紛紛引進民間資源並與私部門建立夥伴關係之全球性風潮推波助瀾下，我國近年亦力倡政府瘦身、組織精簡、引用民力、公私協力。再者，運用民力參與公共任務之公私協力，寓有私部門自主規制成分，惟法學上自主規制與公私協力通常為分離探討之論題，兩者之關連性究為何；又兩者態樣眾多且無普世同意之定義，在多元分殊之學理及實務中，是否存在共通並行之法理脈絡與類型系譜，誠屬行政法總論上饒富逸趣之課題。另行政法各論上，為預防火災以維護公共安全並確保人民生命財產，各國莫不多方運用公私協力與自主規制，建構建築物之消防安全管理制度，惟綜觀國內有關公私協力與自主規制之法學論著尤以前者可謂繁花錦簇，事涉公共安全之消防火災預防行政領域相關研究則付諸闕如猶待開拓。 本文爰透過中外文獻梳理公私協力與自主規制法學理論，並放眼國際取樣研究運用公私協力與自主規制之消防行政實務規範，以歐盟與英國為取法對象，就消防安全管理制度硬體層面及軟體層面分別探討歐盟產品（兼及建築產品［再兼及消防安全設備產品］）監管機制以及英國建築物防火安全管理機制。除解析法理基礎更探究實務規範架構於我國與先進國家之異同，期許回饋提供公私協力與自主規制所涉行政法理論若干啟示並促使本國相關消防行政規範更趨周全。 / In the wake of global trend of government department introducing private resources and establishing partnerships with private sectors to reduce financial burden and improve administrative efficacy, Taiwan authorities in recent years have also been advocating government downsizing, streamlining organizations, adopting private resources, and public private partnership. Furthermore, public private partnership contains private sector’s self-regulation element, but in jurisprudential circle, self-regulation and public private partnership are usually independently researched topics, what are the exact relationships between them; otherwise, each of both has great variety of types and has not universally consented definition, therefore, it seems to be an issue full of keen interest for General Administrative Law: whether there exists common legal context and typological pedigree in the pluralistic and divergent theories and practices of public private partnership and self-regulation. Besides, as regards Specific Administrative Law, in order to prevent fires for protecting public safety and people's lives and property, countries all over the world utilize various approaches to public private partnership and self-regulation, to construct fire protection management regime for buildings; the domestic juristic studies of public private partnership and self-regulation have overall fruitful achievements, especially the former, however, apparently none of them refers to fire protection administrative category that thus eagerly needs to be cultivated. This thesis wherefore sorted domestic and foreign juristic literature about public private partnership and self-regulation, and combed internationally relative fire protection administrative legislation. Focusing on legislation of European Union and United Kingdom, it separately explored hardware dimension and software dimension of fire protection management regimes, that is, EU’s product safety and market surveillance regime (involving that for construction product [further involving that for fixed fire fighting equipment]) and UK’s fire safety regime. In addition to analyzing the legal theories and exploring the similarities and differences of legislative framework between EU or UK and Taiwan, it expects to provide several revelations to the jurisprudence of public private partnership and self-regulation, and to actuate the relative domestic fire protection legislation more comprehensively.

The Ethiopia Commodity Exchange (ECX), like many other data intensive organizations, is having difficulties making full use of the vast amounts of data that it collects. This MSc thesis identifies areas within the organization where concepts from the academic fields of information visualization and visual analytics can be applied to address this issue.Software solutions are designed and implemented in two areas with the purpose of evaluating the approach and to demonstrate to potential users, developers and managers what can be achieved using this method. A number of presentation methods are proposed for the ECX website, which previously contained no graphing functionality for market data, to make it easier for users to find trends, patterns and outliers in prices and trade volumes of commodieties traded at the exchange. A software application is also developed to support the ECX market surveillance team by drastically improving its capabilities of investigating complex trader relationships.Finally, as ECX lacked previous experiences with visualization, one software developer was trained in computer graphics and involved in the work, to enable continued maintenance and future development of new visualization solutions within the organization.