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Machine Learning (ML) is so pervasive in our todays life that we don't even realise that, more often than expected, we are using systems based on it. It is also evolving faster than ever before. When deploying ML systems that make decisions on their own, we need to think about their ignorance of our uncertain world. The uncertainty might arise due to scarcity of the data, the bias of the data or even a mismatch between the real world and the ML-model. Given all these uncertainties, we need to think about how to build systems that are not totally ignorant thereof. Bayesian ML can to some extent deal with these problems. The specification of the model using probabilities provides a convenient way to quantify uncertainties, which can then be included in the decision making process.
In this thesis, we introduce the Bayesian ansatz to modeling and apply Bayesian ML models in finance and economics. Especially, we will dig deeper into Gaussian processes (GP) and Gaussian process latent variable model (GPLVM). Applied to the returns of several assets, GPLVM provides the covariance structure and also a latent space embedding thereof. Several financial applications can be build upon the output of the GPLVM. To demonstrate this, we build an automated asset allocation system, a predictor for missing asset prices and identify other structure in financial data.
It turns out that the GPLVM exhibits a rotational symmetry in the latent space, which makes it harder to fit. Our second publication reports, how to deal with that symmetry. We propose another parameterization of the model using Householder transformations, by which the symmetry is broken. Bayesian models are changed by reparameterization, if the prior is not changed accordingly. We provide the correct prior distribution of the new parameters, such that the model, i.e. the data density, is not changed under the reparameterization. After applying the reparametrization on Bayesian PCA, we show that the symmetry of nonlinear models can also be broken in the same way.
In our last project, we propose a new method for matching quantile observations, which uses order statistics. The use of order statistics as the likelihood, instead of a Gaussian likelihood, has several advantages. We compare these two models and highlight their advantages and disadvantages. To demonstrate our method, we fit quantiled salary data of several European countries. Given several candidate models for the fit, our method also provides a metric to choose the best option.
We hope that this thesis illustrates some benefits of Bayesian modeling (especially Gaussian processes) in finance and economics and its usage when uncertainties are to be quantified.
This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies the martingale method. More precisely, we construct the non-separable value function by formalizing the optimal constrained terminal wealth to be a (conjectured) contingent claim on the optimal non-constrained terminal wealth. This is relevant by itself, but also opens up the opportunity to derive new solutions to constrained problems. As a second contribution, we thus derive new results for non-strict constraints on the shortfall of inter¬mediate wealth and/or consumption.
Sozialräume der Global Financial Class : Untersuchungen in den Finanzzentren Frankfurt und Sydney
(2016)
Dieses Working Paper untersucht die Bedeutung von Global Cities für die Formierung einer globalen Finanzklasse anhand der Finanzzentren Frankfurt und Sydney. In einer vergleichenden Ethnographie dieser beiden Städte werden urbane Räume und soziale Kontexte erforscht, die durch die kulturellen Praktiken und stilistischen Gemeinsamkeiten der modernen Finanzklasse geprägt sind. Es werden dabei vier charakteristische kulturelle Muster identifiziert: Dies sind die Muster der Repräsentation, der Exklusivität, der Aspiration und der sozialen Durchlässigkeit.
Im Muster der Repräsentation verbindet sich das Finanzwesen auf eine symbolische Weise mit Politik und Gesellschaft, während im Muster der Exklusivität der Kern ökonomischer Praktiken dem Zugriff der Allgemeinheit entzogen wird. Das Muster der Aspiration ermöglicht Praktiken der Herstellung und des Austestens von Zugehörigkeit, während der Modus sozialer Durchlässigkeit eine Auseinandersetzung mit anderen gesellschaftlichen Gruppen und die Aufnahme fremder kultureller Muster durch Praktiken der cultural omnivorousness ermöglicht.
Die Praktiken, die diese vier typischen Muster konstituieren, nehmen dabei jeweils lokale Eigenhei- ten auf, die in einen global verlaufenden Klassenbildungsprozess eingespeist werden und diese glo- bale Klasse in den Städten verankern.
This working paper gives insights on a theoretical perspective on class formation in the context of global financial markets and presents first empirical findings regarding the formation of a global financial class. It draws on numerous encounters with financial professionals that were inter- viewed in Frankfurt (Germany) and Sydney (Australia). As a preliminary conclusion from those inves- tigations on a micro-perspective, we state that acting on the market creates a sense of global socia- bility, whereby organizations only play a secondary role. Careers in finance follow internationally homogenized pathways. This process of global class formation is taking place prominently in global financial centers. Therefore we link the level of investigation on a micro-perspective (experience of financial professionals) with global city life and the fabric of the city. This results in empirical findings on a meso-level from an ethnography of the social and professional urban environment of finance in the two global cities. Symbolic struggles engraved in the built environment of Frankfurt and Sydney are traced and discussed against the background of every-day-practices of aspiration in the financial districts investigated.
Facial Width-to-Height Ratio (fWHR) has been linked with dominant and aggressive behavior in human males. We show here that on portrait photographs published online, chief executive officers (CEOs) of companies listed in the Dow Jones stock market index and the Deutscher Aktienindex have a higher-than-normal fWHR, which also correlates positively with their company’s donations to charitable causes and environmental awareness. Furthermore, we show that leaders of the world’s most influential non-governmental organizations and even the leaders of the Roman Catholic Church, the popes, have higher fWHR compared to controls on public portraits, suggesting that the relationship between displayed fWHR and leadership is not limited to profit-seeking organizations. The data speak against the simplistic view that wider-faced men achieve higher social status through antisocial tendencies and overt aggression, or the mere signaling of such dispositions. Instead they suggest that high fWHR is linked with high social rank in a more subtle fashion in both competitive as well as prosocially oriented settings.
Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the components as well as dynamic feedback between the components. Special cases and relationships with previously proposed specifications are discussed and stationarity conditions are derived. An empirical application to NASDAQ-index data indicates the appropriateness of the model class and illustrates that the approach can generate a plausible disaggregation of the conditional variance process, in which the components' volatility dynamics have a clearly distinct behavior that is, for example, compatible with the well-known leverage effect. Klassifikation: C22, C51, G10
Im Kontext der Diskussion zur „Globalisierung des Managements“ und der daraus entstandenen These einer transnationalen Klasse untersuchen wir in diesem Beitrag den Stellenwert internationaler Berufserfahrung bei Bankvorständen in Deutschland und weltweit. Bisherige Forschungen (etwa Pohlmann 2009) argumentieren, dass bei den Top-100- Industrieunternehmen in den USA, Ostasien und Deutschland Karriereverläufe im mittleren und Spitzenmanagement kaum internationalisiert sind und Hauskarrieren die Regel seien. Unsere eigene explorative Untersuchung legt die Vermutung nahe, dass die Situation im deutschen sowie im globalen Bankensektor anders aussieht. Vor allem in Deutschland verlaufen die Top-Karrieren im Unterschied zu Industrieunternehmen deutlich internationaler, was auf andere personelle Konstellation im Feld des global vernetzten Finanzsektors hinweist. Im deutschen wie im globalen Finanzsektor könnten wir es hierbei mit dem Phänomen einer „Transnationalisierung ohne Migration“ zu tun haben.
In methodischer Hinsicht macht unsere Studie auf die Grenzen quantitativer Forschungsdesigns bei der Untersuchung internationaler Berufserfahrung und internationalen Arbeitspraxen aufmerksam. Daher plädieren wir für ein an die Kategorien der Bourdieu‘schen Sozialtheorie angelehntes qualitatives Forschungsdesign für die Untersuchung der Herausbildung einer globalen Klasse auf den globalisierten Finanzmärkten.