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We introduce a universal framework for mean-covariance robust risk measurement and portfolio optimization. We model uncertainty in terms of the Gelbrich distance on the mean-covariance space, along with prior structural information about the population dis ...
Autonomous mobility devices such as transport, cleaning, and delivery robots, hold a massive economic and social benefit. However, their deployment should not endanger bystanders, particularly vulnerable populations such as children and older adults who ar ...
This thesis examines how banks choose their optimal capital structure and cash reserves in the presence of regulatory measures. The first chapter, titled Bank Capital Structure and Tail Risk, presents a bank capital structure model in which bank assets a ...
This thesis work focuses on optimal control of partial differential equations (PDEs) with uncertain parameters, treated as a random variables. In particular, we assume that the random parameters are not observable and look for a deterministic control which ...
An accurate assessment of the risk of extreme environmental events is of great importance for populations, authorities and the banking/insurance/reinsurance industry. Koch (2017) introduced a notion of spatial risk measure and a corresponding set of axioms ...
Improving risk assessment and conducting thorough cost-benefit analyses of the different proposed management options are of paramount importance to making informed decisions. However, getting a comprehensive picture of a complex, ambiguous and uncertain ri ...
This thesis develops models for three problems of liquidity under asymmetric information.
In the chapter "Disclosures, Rollover Risk, and Debt Runs" I build a model of dynamic debt
runs without perfect information in order to understand the impact of asset ...
Neighborhood-scale projects often commence with the conceptualization of several massing-schemes as potential design solutions. There is growing interest in using building performance simulation (BPS) to evaluate and rank such conceptual stage schemes in o ...
Most efforts to understand snakebite burden in Nepal have been localized to relatively small areas and focused on humans through epidemiological studies. We present the outcomes of a geospatial analysis of the factors influencing snakebite risk in humans a ...
This paper studies the problem of learning under both large datasets and large-dimensional feature space scenarios. The feature information is assumed to be spread across agents in a network, where each agent observes some of the features. Through local co ...
