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The activity of algorithmic trading is increasing steadily across capital markets due to technological developments. This thesis analyses the common algorithmic intraday trading strategies of momentum, mean reversion, and statistical arbitrage. Conclusions were drawn from a literature review of prior and current research. Algorithmic arbitrage was found to be the most profitable of the three evaluated strategies, because it typically takes place in high frequency trading. Furthermore, this thesis analyses the impact of algorithmic trading on market liquidity and volatility. While the literature mainly agrees that algorithmic trading has a positive effect on liquidity, its impact on volatility is subject to discussion. Algorithmic and high-frequency trading carry risks that will likely lead to new future regulations.:1 INTRODUCTION 1.1 Background 1.2 Problem description and goal of the research 1.3 Structure of the thesis and research questions 2 THEORETICAL FUNDAMENTALS 2.1 Intraday trading 2.1.1 Definition 2.1.2 Characteristics of intraday trading markets 2.1.3 Financial instruments of intraday trading 2.1.4 Goals and profit chances of individual intraday traders 2.2 Algorithmic trading 2.2.1 Algorithm definitions 2.2.2 Algorithmic trading definitions 2.2.3 High-frequency trading 2.2.4 Characteristics of algorithmic trading and high-frequency trading 2.2.5 Trading algorithm characteristics 3 METHODOLOGY 3.1 Data collection 3.2 Data analysis 4 ALGORITHM-BASED INTRADAY TRADING STRATEGIES AND THEIR PROFIT POTENTIAL 4.1 Momentum strategy 4.1.1 Definition and basic principle of the strategy 4.1.2 Underlying theories of the momentum strategy 4.1.3 Selected studies of an algorithmic intraday momentum strategy 4.2 Mean reversion strategy 4.2.1 Definition and basic principle of the strategy 4.2.2 Underlying theories of the mean reversion strategy 4.2.3 Relation of mean reversion and momentum 4.2.4 Selected studies of an algorithmic intraday mean reversion strategy 4.3 Arbitrage strategy 4.3.1 Definition and basic principle of the strategy 4.3.2 Types of Arbitrage 4.3.3 Underlying theories of the arbitrage strategy 4.3.4 Selected studies of an algorithmic intraday statistical arbitrage strategy 4.4 Further trading algorithms and strategy components 4.4.1 Speed Advantage algorithms 4.4.2 Accuracy Advantage Algorithms 5 IMPACT OF ALGORITHMIC TRADING ON MARKET LIQUIDITY AND VOLATILITY 5.1 Market liquidity 5.1.1 Definition 5.1.2 Bid-Ask Spread 5.1.3 Dimensions of liquidity 5.1.4 The impact of algorithmic trading on market liquidity 5.2 Market volatility 5.2.1 Definition and characteristics of volatility 5.2.2 The impact of algorithmic trading on market volatility 6 CONCLUSION AND FUTURE DEVELOPMENTS OF ALGORITHMIC TRADING PUBLICATION BIBLIOGRAPHY DECLARATION OF HONOR

Inovácia na finančných trhoch poskytuje nové príležitosti. Algoritmické obchodovanie je vhodný spôsob využitia týchto príležitostí. Táto práca sa zaoberá návrhom a implementáciou systému, ktorý by dovoľoval svojím uživateľom vytvárať vlastné obchodovacie stratégie, a pomocou nich obchodovať na burzách. Práca kladie dôraz na návrh distribuovaného systému, ktorý bude škálovatelný, pomocou technológií cloud computingu.

This essay aims to study the relationship between cosplay content creators and TikTok’s algorithm. To study this relationship the essay will conduct a qualitative semi-structured interviews with creators from the cosplay community on TikTok. Since the rise of digital plattforms the media and the role of producer as well as consumer has changed drastically. TikTok has been growing rapidly in popularity since its entry on the market, and by 2020 it had 500 million active users. Since many of today's digital platforms have consumer produced content, the consumer of today has taken on a mixed role between consuming and creating content, which creates a new relationship. The content consumers produce vary vastly on TikTok but one kind that has been present in much of TikTok’s existence is cosplay content. Cosplayers are creators who design costumes to already established characters or franchises. Since a discourse has started in the cosplay community on TikTok about the algorithm suppressing their content the study found it to be a good way to start examining content creators as individuals and how they behave towards an algorithm in their content creation process. The study aims to use algorithmic “folk” theory to examine what theories have been created in the community and how the theories affect the creators. The study also applies gatekeeping theory and social cognitive theory (SCT) to paint a clearer picture in how these creators view the algorithm. Seven interviews with cosplay content creators were conducted and with the help of a thematic analysis method the study found several themes in how the creators view and behave in relation to TikTok and its algorithm. The results of our study shows that there’s a definite present of “folk” theories created inside of the community. The most distinct behaviour relating to “folk” theory among the creators was that they can’t use the hashtag cosplay in the belief that the algorithm would suppress the content. This study concludes that the creators are more aware of the algorithm then they themself know and have different ways of working with and around it.

Tato disertační práce se zabývá biometrickým rozpoznáváním 3D obličejů. V úvodu práce jsou prezentovány současné metody a techniky pro rozpoznávání. Následně je navržen nový algoritmus, který využívá tzv. multialgoritmickou biometrickou fúzi. Vstupní snímek 3D obličeje je paralelně zpracování dílčími rozpoznávacími podalgoritmy a celkové rozhodnutí o identitě nebo verifikaci identity uživatele je výsledkem sloučení výstupu těchto podalgoritmů. Rozpoznávací algoritmus byl testován na veřejně přístupné databázi 3D obličejů FRGC v 2.0 i vlastních databázich, které byly pořízeny pomocí senzorů Microsoft Kinect a SoftKinetic DS325.

A set of elementary building blocks undergoes self-assembly if local interactions govern how this set forms intricate structures. Self-assembly has been widely observed in nature, ranging from the field of crystallography to the study of viruses and multicellular organisms. A natural question is whether a model of self-assembly can capture the hierarchical growth seen in nature or in other fields of mathematics. In this work, we consider hierarchical growth in substitution rules; informally, a substitution rule describes the iterated process by which the polygons of a given set are individually enlarged and dissected. We develop the Polygonal Two-Handed Assembly Model (p-2HAM) where building blocks, or tiles, are polygons and growth occurs when tiles bind to one another via matching, complementary bonds on adjacent sides; the resulting assemblies can then be used to construct new, larger structures. The p-2HAM is based on a handful of well-studied models, notably the Two-Handed Assembly Model and the polygonal free-body Tile Assembly Model. The primary focus of our work is to provide conditions which are either necessary or sufficient for the ``bordered simulation'' substitution rules. By this, we mean that a border made up of tiles is allowed to form around an assembly which then coordinates how the assembly interacts with other assemblies. In our main result, we provide a construction which gives a sufficient condition for bordered simulation. This condition is presented in graph theoretic terms and considers the adjacency of the polygons in the tilings associated to a given substitution rule. Alongside our results, we consider a collection of over one hundred substitution rules from various sources. We show that only the substitution rules in this collection which satisfy our sufficient condition admit bordered simulation. We conclude by considering open questions related to simulating substitution rules and to hierarchical growth in general.

Algorithmic and high-frequency trading on capital market Abstract The subject of this diploma thesis is legal regulation and development of regulation of algorithmic and high-frequency trading on capital market within Community Law but also within several European countries, USA and Japan. The aim of this diploma thesis is to define terms of algorithmic and high-frequency trading, which were not thoroughly regulated until lately, to outline development of legal regulation, to compare different approaches to their regulation in different countries and to assess the phenomenon of algorithmic and high- frequency trading. The diploma theses uses descriptive method to define the fundamental terms and discuss positive legal framework. It also uses deduction for assessment and comparative method to examine different approaches to legal regulation in different countries. The first chapter characterizes capital market as a place in which algorithmic and high- frequency trading takes place, including its historical development, participants and supervisory authorities. The second chapter defines terms of algorithmic and high-frequency trading considering their historical development and both mutual similarities their differences and their characteristics. It also includes an analysis of their key aspects and related...

Background:  Despite the utilization of algorithms as data management tools, they are increasingly used as people management tools to allocate, optimize and evaluate workers. This is especially popular among digital labor platforms of the gig economy as it is seen as one of the core innovations that enabled such platforms. Usually, these platform workers are self-employed, which results in an apparent autonomy while working under a rigid algorithm. For those workers, proactively shaping the job according to their own needs and abilities, commonly known as job crafting, may be increasingly important. As research suggests that job crafting occurs across professions and industries, how is it possible under the constraints of algorithmic management?  Purpose:  This thesis investigates the abilities of German food delivery riders of the company Lieferando to perform job crafting while being managed by an algorithm.  Method:  To meet the purpose of this study, the authors conducted a qualitative study. The data was collected through technology-mediated interviews with riders of the company Lieferando in Germany. The authors applied an online recruitment strategy through various social media websites to find suitable interviewees. Interview partners were picked with a random sampling strategy. The interviews were semi-structured, and the researchers guided the interviewees through a previously prepared topic guide with open-ended questions.  Conclusion:  The results of this study provide empirical evidence that riders of the food delivery company Lieferando engage in job crafting activities although working under the constraints of algorithmic management. The outcomes further show that all riders performed task crafting and cognitive crafting in various ways, whereas engagement in relational crafting was less developed. Riders not only have the ability to modify their work but also enrich it.  The findings of this study allow to draw several theoretical and managerial implications as well as provide possible research opportunities for future studies.

Ocean of Forms is a cycle of five songs for solo soprano voice and electronic/computer music accompaniment on poems by noted Bengali poet, musician, philosopher, and author Rabindranath Tagore. This work approaches the song cycle as a vehicle for expressing and highlighting the poet's words. Word and syllabic stress, text painting, melodic development, and formal structure all function in relation to the text and its meaning. the replacement of the traditional piano accompaniment with electronic accompaniment provides further possibilities for new timbral structures and transformations, expressive microtonal intonation, algorithmic and aleatoric formal structures, acousmatic and spatialized sound, and a broad sonic palette. This work strives to provide a more fully developed expression of the text as afforded by these expanded musical means. the critical essay primarily explores the interaction between text and music in the work. the first chapter explores the historical precedents for the genre of the song cycle and other texted music as well as specific influences on the work. the following chapters explore the connections between the text and the vocal line and electronic/computer music, respectively. the final chapter deals with the formal structure of the work, especially the justly-tuned harmonic scheme and its relation to the text.

In this thesis, the aim is to investigate whether a pairs trading strategy on Swedish stocks can generate a higher risk-adjusted return compared to a buy-and-hold strategy on a benchmark index. The benchmark index is the OMX Stockholm Benchmark-index (OMXSBPI), which is an index that should reflect the Swedish market in general. With a statistical focus, a trading algorithm is built which is then evaluated on data between the years 2018 to 2021. The statistical concepts this thesis is based on are stationarity and cointegration and it is the Augmented Dickey-Fuller test that forms the basis for being able to test these concepts. The risk-adjusted return for the strategy is evaluated using the popular measure Sharpe ratio, which is then compared to the Sharpe ratio for the OMXSBPI-index. The results obtained in this study can not confirm that the pairs trading strategy is better than a buy-and-hold strategy on the OMXSBPI-index in terms of risk-adjusted return. One indication, however, is that the strategy seems to perform better in conditions when the market is declining. In 2018, the index went down by 7.7060 while the strategy went up by 7.5100 percent. As it is data for only one year, it is not possible to determine whether it is due to chance or a potential edge of the strategy.