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Empirical Analyses of German Foreign Bank Lending
The aim of this thesis is to shed light on German banks' foreign lending, which has grown substantially over the past two decades and forms an integral part of worldwide capital flows at present. For this purpose, a new micro data-set on German foreign bank lending from Deutsche Bundesbank is used. The thesis begins by providing background information on Germany's banking sector and the importance of foreign bank lending for different banking groups. It turns out that mainly Big Banks and Landesbanks are engaged in foreign lending. As a consequence, the data-set, which is described in detail, focuses on those banking groups. In the first empirical analysis, I study the major determinants of ...
Bank Capital and Risk-Taking
The year-long consultations on Basel II mirror the international popularity of capital requirements as a regulatory instrument. Yet, the impact of capital requirements on banks' behavior is not fully understood. The aim of this study is to contribute to this understanding.
Financial Regulation at the Crossroads
This book brings outstanding expertise and provides insightful perspectives from nineteen authors with diverse backgrounds, including officials from international organizations, national regulators, and commercial banking, as well as academics in law, economics, political economy, and finance. The authors not only shed light on the causes of the financial turmoil, but also present thoughtful proposals that contribute to the future policy debate, and discuss opportunities that financial services can offer in funding activities which raise standards of living through initiatives in microfinance, renewable energy, and food distribution. The contributions to this volume tackle several of the tho...
Machine Learning in Insurance
Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.
Social Structures of Direct Democracy
Neoliberalism has pushed capitalism to its limits, hollowing out global economies and lives in the process, while people have no voice. John Asimakopoulos addresses the problem with a theory to practice model that reconciles Marxism, with its diverse radical currents, and democratic theory. Social Structures of Direct Democracy develops a political economy of structural equality in large-scale society making strong empirical arguments for radical transformation. Key concepts include filling positions of political and economic authority (e.g., legislatures and corporate boards) with randomly selected citizens leaving the demos as the executive. Asimakopoulos shows that an egalitarian society leads to greater innovation, sustainable economic growth, and positive social benefits in contrast to economies based on individualism, competition, and inequality.
