Titlebook: Risk Analysis for the Digital Age; Anton Gerunov Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive license to Spr

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Standard Risk Metrics,sometimes, the incredible propensity of individuals and organizations to ignore this fact. Against the backdrop of increasing economic sophistication and ever-expanding risk exposure, particularly to high impact risks, it is of paramount importance to understand and rigorously manage the inherent un

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Risk in Digital Assets,d presents one with unique digital assets. All of these serve to greatly increase the risk exposure of organizations and individuals by both modifying probability of occurrence, and amplifying impact. On the analytic front, this puts new challenges and requires new approaches and tools for modeling

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Networks of Risk,work nodes, and all their interactions being the connecting edges. Our economies and cities are no less structured as a network than our personal relations and critical infrastructures . How different nodes are connected in such systems has crucial implications for their functioning, stability, resi

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Humans in the Network,e based on extensive research. The perfect way to model preferences has not yet been reached and each of the many proposals has some shortcomings. However, the practical imperative to understand how human beings perceive risk and act under uncertainty is probably stronger than ever, necessitating th

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Networks of Risk,m a more sophisticated view of real-life risk exposures. Formal metrics of the network structure are introduced with clear recourse to what they mean for the risk manager. Finally, the focus shifts to the actual construction of networks with empirical data leveraging a Bayesian approach.

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Understanding Risk,randomness and probability and their interpretation reflects a deep underlying view of how the world functions. Essentially, how one views the world defines how one perceives risk and acts upon it. This chapter reviews the mathematical foundations of modeling risk and provides a first pass at quantitatively measuring it.