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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.
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.
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