Cette thèse est consacrée à l'étude de la formation des prix sur les marchés financiers, en particulier lorsque ceux-ci se composent d'un grand nombre d'agents. On commence par l'étude empirique d'un marché émergent -- le bitcoin -- de manière à mieux comprendre comment les actions individuelles affectent les prix -- ce que l'on appelle « l'impact de marché ». On développe ensuite un modèle théorique d'impact basé sur le concept d'agent hétérogène, qui parvient à reproduire les observations empiriques d'un impact concave dans un marché non manipulable. Le cadre de l'agent hétérogène nous permet de revisiter les concepts d'offre et de demande dans un cadre dynamique, de mieux comprendre l'impact du mécanisme de marché sur la liquidité, ou encore de poser les bases d'un simulateur de marché réaliste. On montre enfin, à travers l'étude empirique de plusieurs bulles et crashs sur le marché du bitcoin, le rôle crucial de la micro-structure dans la compréhension des phénomènes extrêmes. / This thesis is devoted to the study of price formation on financial markets, in particular when these are composed of a large number of agents. We start by the empirical study of an emergent market -- the bitcoin -- in order to better understand how individual actions impact prices -- a phenomenon known as « market impact ». We then develop a theoretical model based on the concept of heterogeneous agents, that allows to reproduce the empirical observations of a concave impact in a market that remains non-manipulable. The heterogeneous agents framework allows us to revisit the concepts of supply and demand in a dynamic context, to better understand how the choice of a particular market mechanism can impact liquidity, and to lay some grounds for a realistic market simulator. By studying several bubbles and crashes that happened on the bitcoin market, we finally show how relevant microstructure effects can be, in particular for understanding the occurrence of extreme phenomena.

En este trabajo se aplican modernas técnicas multicriterio para la selección de carteras, partiendo de información empírica muy amplia proveniente de la Bolsa de Madrid. En efecto, el número de títulos-valores considerados asciende a 104 durante un reciente período de cinco años, habiéndose recogido rendimientos por plusvalías, dividendos y ampliaciones de capital con periodicidad mensual a lo largo del periodo histórico. Basándose en este material estadístico, se han obtenido doce fronteras eficientes diversificadas, analizando sus peculiaridades. Estas fronteras se han diseñado de tal modo que cumplen en ellas las restricciones legales en cuanto a diversificación. Para seleccionar las carteras óptimas, se recurre a técnicas de bounding que se fundamentan en teoremas recientemente aparecidos en la literatura. Los objetivos del inversor son relevantes para optimizar los portafolios, teniendo en cuenta los coeficientes de aversión al riesgo, y más en general, las RMS entre rentabilidad y seguridad, de acuerdo con las preferencias inversoras. Los teoremas indicados permiten conseguir aproximaciones al óptimo cuando se carece de información completa sobre la función de utilidad. Este caso resulta especialmente importante, dadas las dificultades para especificar formas y parámetros de utilidad con respecto a fondos de inversión y otros inversores colectivos. Sin embargo, la fisonomía correspondiente al fondo de inversión y sus perfiles gestores dan lugar en la tesis a distintas alternativas de cartera, en casos tan diversos como las estrategias activas y la política buy & hold. / Pla Santamaría, D. (2000). Modelos multicriterio para la selección de portafolios en la Bolsa de Madrid [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/5184 / Palancia

The Czech National Bank, its legal status and scope of activities Abstract The theme of this thesis is the Czech National Bank, its legal status and scope of activities. The aim of the thesis is to describe and analyse the development of central banking and to evaluate current legal status of the Czech National Bank. Due to the volume of the Czech National Bank's activities, the work is focused only on the supervisory activities of the Czech National Bank and on the examination of the functioning of the unified supervision system. The thesis is divided into five parts. The first part deals with theoretical issues of the emergence of central banking and with the functions of central banks. The following part deals with the development of central banking in the Czech lands from the time of the Austrian Empire until the establishment of the independent Czech Republic. The third part of the thesis describes legal status of the Czech National Bank, its establishment in the Constitution of the Czech Republic, its tasks, objectives and its independence. Furthermore, the thesis describes bank's relationship with other constitutional institutions, its organizational structure, management and regulatory activities. The fourth part of the thesis deals with the supervisory activities of the Czech National Bank. At the...

Die Dissertation untersucht verschiedene Einflussfaktoren auf die Finanzierungskosten von Staaten. Dabei werden die Eurokrise, Rohstoffpreise und Klimawandel als drei wesentliche Einflussfaktoren herangezogen und deren empirische Wichtigkeit statistisch untersucht. Ein weiterer Artikel beschäftigt sich mit der Integration von Finanzmärkten auf die Ausbreitung von Konjunkturzyklen.:Chapter 1: Introduction 1 1.1 Motivation: The Curious Case and Multiple Facets of Sovereign Debt . . . . 1 1.2 Outline and Contribution of this Thesis to the Literature . . . . . . . . . . . 6 A.1 Appendix to Chapter 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 References to Chapter 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Chapter 2: Avoiding the Fall into the Loop: Isolating the Transmission of Bank-to-Sovereign Distress in the Euro Area 19 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.3 Data Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.3.1 Deriving Country-Specific Bank Distress . . . . . . . . . . . . . . . . . 24 2.3.2 Instrumenting Bank Distress using Exposure-Weighted Stock Market Returns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.3.3 Set of Dependent and Explanatory Variables . . . . . . . . . . . . . . 30 2.3.3.1 Dependent Variable . . . . . . . . . . . . . . . . . . . . . . . 30 2.3.3.2 Control Variables . . . . . . . . . . . . . . . . . . . . . . . . 33 2.4 Empirical Specification and Results . . . . . . . . . . . . . . . . . . . . . . . . 35 2.5 Robustness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.5.1 Comparison of IV and OLS during Eurozone Crisis . . . . . . . . . . . 38 2.5.2 Alternative Versions of the Dependent Variable . . . . . . . . . . . . . 40 2.5.3 Alternative Versions for Bank Distress Variable . . . . . . . . . . . . . 41 2.5.4 Alternative Versions for Instrumental Variable . . . . . . . . . . . . . 42 2.5.5 Strengthening the Exclusion Restriction of the Instrument . . . . . . . 46 2.5.6 Weekly Frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 2.5.7 Alternative Control Variables and Time Fixed Effects . . . . . . . . . 49 2.5.8 Wild Cluster Bootstrapping . . . . . . . . . . . . . . . . . . . . . . . . 52 2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 A.2 Appendix to Chapter 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 A.2.1 Drivers of Bank-to-Sovereign Distress Transmissions . . . . . . . . . . 54 A.2.1.1 Macroeconomic Performance . . . . . . . . . . . . . . . . . . 57 A.2.1.2 Government Bond Issuances, Redemptions and Holdings . . 62 A.2.1.3 Banking Sector Structure and Stability . . . . . . . . . . . . 66 A.2.1.4 Political Stability . . . . . . . . . . . . . . . . . . . . . . . . 72 A.2.2 Additional Tables and Figures . . . . . . . . . . . . . . . . . . . . . . . 77 References to Chapter 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Chapter 3: What drives the Commodity-Sovereign Risk Dependence in Emerging Market Economies? 87 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 3.2 Data, Variables and Summary Statistics . . . . . . . . . . . . . . . . . . . . . 92 3.2.1 Dependent Variable: Sovereign Default Risk . . . . . . . . . . . . . . . 92 3.2.2 Deriving Country-specific Commodity Performance . . . . . . . . . . . 94 3.2.3 Set of Control Variables . . . . . . . . . . . . . . . . . . . . . . . . . . 97 3.3 Empirical Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 3.3.1 Baseline Specification and Results . . . . . . . . . . . . . . . . . . . . 98 3.3.2 Alternative Specifications . . . . . . . . . . . . . . . . . . . . . . . . . 101 3.4 Drivers of the Commodity-Sovereign Risk Dependence . . . . . . . . . . . . . 104 3.4.1 Commodity-related Factors . . . . . . . . . . . . . . . . . . . . . . . . 105 3.4.2 Macroeconomic and International Factors . . . . . . . . . . . . . . . . 110 3.4.3 Policy Measures against Commodity Dependence . . . . . . . . . . . . 117 3.5 Robustness Checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 3.5.1 Dropping Countries with Liquidity Issues . . . . . . . . . . . . . . . . 127 3.5.2 Alternative Specifications for EMBI and Commodity Performance . . 129 3.5.3 Alternative Control Variables . . . . . . . . . . . . . . . . . . . . . . . 130 3.5.4 Alternative Fixed Effects, Frequency, Clustering and Time Series Results131 3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 A.3 Appendix to Chapter 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 References to Chapter 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Chapter 4: Financial Linkages and Sectoral Business Cycle Synchronization: Evidence from Europe 145 4.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 4.2 Empirical Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 4.2.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 4.2.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 4.3 Estimation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 4.3.1 Results for Overall Output Fluctuations (GDP) . . . . . . . . . . . . . 157 4.3.2 Results for Industrial Output Fluctuations . . . . . . . . . . . . . . . . 162 4.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 A.4 Appendix to Chapter 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 References to Chapter 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 Chapter 5: Physical Climate Change Risks and the Sovereign Creditworthiness of Emerging Economies 182 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 5.2 Physical Climate Change Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 5.2.1 Physical Climate Change Risk in Contrast to Transition Risk . . . . . 187 5.2.2 Physical Climate Change and Sovereign Creditworthiness . . . . . . . 189 5.3 Data and Descriptive Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . 191 5.3.1 Sovereign Creditworthiness . . . . . . . . . . . . . . . . . . . . . . . . 191 5.3.2 Temperature Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 5.4 Empirical Specification and Results . . . . . . . . . . . . . . . . . . . . . . . . 195 5.5 Channels of Temperature-Sovereign Risk Connection . . . . . . . . . . . . . . 197 5.5.1 General Warmness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 5.5.2 Seasonality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 5.5.3 Month and Season Effects . . . . . . . . . . . . . . . . . . . . . . . . . 205 5.5.4 Economic Sector Specialization . . . . . . . . . . . . . . . . . . . . . . 208 5.5.5 Institutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 5.5.6 Combining relevant Channels . . . . . . . . . . . . . . . . . . . . . . . 215 5.6 Robustness Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 5.6.1 Changing the Fixed Effects Specification . . . . . . . . . . . . . . . . . 218 5.6.2 Changing the Dependent Variable . . . . . . . . . . . . . . . . . . . . 220 5.6.3 Changing the Lag Structure . . . . . . . . . . . . . . . . . . . . . . . . 221 5.6.4 Changing the Historical Temperature Average Period . . . . . . . . . . 222 5.6.5 Dropping Countries with lower Data Coverage and larger Landmass . 226 5.6.6 Other Temperature Anomaly Measures . . . . . . . . . . . . . . . . . 227 5.6.7 Analyzing Debt Sustainability . . . . . . . . . . . . . . . . . . . . . . . 229 5.6.8 Testing for Transition Risks . . . . . . . . . . . . . . . . . . . . . . . . 229 5.6.9 Changing Economic Sector Specialization Measures . . . . . . . . . . . 231 5.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 A.5 Appendix to Chapter 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 References to Chapter 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247

This master thesis deals with the investment recommendation for Czechoslovak Com- mercial Bank, a.s. The recommendation is based on business strategy based on Fibonacci retracement and analysis of the current risks of financial markets. The first part deals with the parameters and the results of the business strategy. Second part proposes investment and non-investment recommendations. At the end of the thesis are summarized all aspects of the research.

This Master's thesis focuses on applying artificial intelligence tools for the prediction of development financial markets. Major emphasis is placed on evaluating the usability of neural networks to determine the prediction in the foreign exchange markets. It is also provided suggestion for fully automated processing of market data and subsequent submitting of trading orders.

This thesis will focus on developing investment strategies for selected venture with temporarily free funds. The theoretical part will deal with the opportunities and tools of investing in financial markets, active and passive portfolio management and collective investment institutions. The practical part will focus on the analysis and comparison of the selected investment opportunities in the financial market with final recommendations.

This thesis deals with problems of the technical analyses and its usage during creation of the automated trading systems. Theoretical section explains the basic principles of functioning of the monetary market (Forex) and includes technical indicators. Portfolio of strategies, as output of this work, was applied onto monetary pairs of Euro/American dollar and British pound/American dollar. Computer program Adaptrade Builder was used for proposed commercial strategies with help of the genetic algorithms and subsequently tested on the MetaTrader 4 commercial platform.

The thesis deals with designing an automated trading system, especially for intra-day trading the currency markets. The aim is to create a comprehensive theoretical background, practical work knowledge can be used to develop appropriate automated trading system. The thesis is an emphasis on technical and partly a psychological analysis of currency markets. Designed system will be suitably optimized to maximize profits and stability of applications on the most liquid currency pairs.

Chapter 1 Summary of the Dissertation "We are in the golden age of fraud." Jim Chanos, Kynikos Associates, Financial Times 24/07/2020. Beyond the speculations about the consecutive waves of Covid, 2020 will be reminded for one of the most notorious failures of a listed firm, due to a massive accounting fraud: the German payment fintech Wirecard. The firm, with 30 subsidiaries in 26 countries, joined the prestigious DAX index just two years before. The spillovers of the billion-euro fraud range from the arrest of top managers to suspicion of auditors, politicians, and regulatory authorities (BaFin, European Commission, and ESMA), as suggested the Financial Times headline "Why was Frankfurt so blind for so long?"1 Such a failure serves as a reminder of the relevance of financial markets regulation, oversight, and enforcement, in order to protect investors and to encourage compliance with regulations. Research on the relationship between the publication of financial misconducts and financial performance for corporates has continuously grown, as illustrated by the recent in- depth literature reviews undergone by Amiram et al. (2018) and Liu and Yawson (2020). It is fueling regulatory debates on how to enforce more efficiently financial regulations. Some specificities of white-collar crimes must be accounted for...