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Macroprudential Stress Tests: A Reduced-Form Approach to Quantifying Systemic Risk Losses
We present a novel approach that incorporates individual entity stress testing and losses from systemic risk effects (SE losses) into macroprudential stress testing. SE losses are measured using a reduced-form model to value financial entity assets, conditional on macroeconomic stress and the distress of other entities in the system. This valuation is made possible by a multivariate density which characterizes the asset values of the financial entities making up the system. In this paper this density is estimated using CIMDO, a statistical approach, which infers densities that are consistent with entities’ probabilities of default, which in this case are estimated using market-based data. Hence, SE losses capture the effects of interconnectedness structures that are consistent with markets’ perceptions of risk. We then show how SE losses can be decomposed into the likelihood of distress and the magnitude of losses, thereby quantifying the contribution of specific entities to systemic contagion. To illustrate the approach, we quantify SE losses due to Lehman Brothers’ default.
Handbook of Financial Stress Testing
Stress tests are the most innovative regulatory tool to prevent and fight financial crises. Their use has fundamentally changed the modeling of financial systems, financial risk management in the public and private sector, and the policies designed to prevent and mitigate financial crises. When financial crises hit, stress tests take center stage. Despite their centrality to public policy, the optimal design and use of stress tests remains highly contested. Written by an international team of leading thinkers from academia, the public sector, and the private sector, this handbook comprehensively surveys and evaluates the state of play and charts the innovations that will determine the path ahead. It is a comprehensive and interdisciplinary resource that bridges theory and practice and places financial stress testing in its wider context. This guide is essential reading for researchers, practitioners, and policymakers working on financial risk management and financial regulation.
Systemic Risk Modeling: How Theory Can Meet Statistics
We propose a framework to link empirical models of systemic risk to theoretical network/ general equilibrium models used to understand the channels of transmission of systemic risk. The theoretical model allows for systemic risk due to interbank counterparty risk, common asset exposures/fire sales, and a “Minsky" cycle of optimism. The empirical model uses stock market and CDS spreads data to estimate a multivariate density of equity returns and to compute the expected equity return for each bank, conditional on a bad macro-outcome. Theses “cross-sectional" moments are used to re-calibrate the theoretical model and estimate the importance of the Minsky cycle of optimism in driving systemic risk.
Huang Di Nei Jing Su Wen
"The essential reference for ancient Chinese medicine."—Donald Harper, University of Chicago
Quantifying Systemic Risk
In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises. One of the first books to address the challenges of measuring statistical risk from a system-wide persepective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.
Mathematical Reviews
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Research methods in palliative care
Palliative and end of life care are concerned with the physical, social, psychological and spiritual care of people with advanced disease. It currently has a poorly developed research base, but the need to improve this is increasingly recognised. One of the reasons for the lack of research - and the variable quality of the research that is undertaken - is the difficulty of conducting research with very ill and bereaved people. Standard and well-established research methods may need to be adapted to work in this context. This means that existing research methods textbooks may be of limited use to palliative care practitioners seeking to do research for the first time, or to more experienced r...
Huang Di Nei Jing Su Wen
"This complete annotated translation of the Su Wen is exemplary in every respect. The translation will stimulate new directions in research while providing the first accurate guide to the basic concepts of traditional Chinese medicine for a wider readership."—Donald Harper, The University of Chicago
Determinantal Point Processes for Machine Learning
This monograph provides a comprehensible introduction to DPPs, focusing on the intuitions, algorithms, and extensions that are most relevant to the machine learning community.
