New Variance Journal Resource: Articles in Press

08/17/2016 —

A new page has been added to the Variance website, “Articles in Press.” Because of copyediting and other requirements of the publication process, there is typically a collection of papers – often a dozen or more – that have been accepted for publication in Variance, but that will not be formally published for many months.  This has meant that, although there are some very interesting articles in the pipeline, logistical requirements result in delays in getting them to our readers.

In an effort to make these accepted papers available and of benefit to the membership as soon as possible, we have created an “Articles in Press” section of the Variance website, where we now post PDF files of papers upon or shortly after acceptance.  The posted papers will not yet have been fully copyedited or be free of typos, but the final submitted versions of accepted papers are now available here, until formal publication occurs.

Here’s a random, small sampling of the fifteen accepted Variance papers currently (mid-2016) available in this new section:

  • “Counterfactual Disaster Risk Analysis” by Gordon Woo advocates the use of “counterfactual history” to develop possible alternative future catastrophe scenarios.  The paper is a discussion and collection of examples for imaginatively considering “the dynamic perturbations that might transition a system to a disaster state.”
  • “Casualty Catastrophe Analytics” by Steve D’Arcy contemplates an area of risk that has immense loss potential, and that needs more attention, including thoughtful consideration of past, current, and future approaches to identifying, quantifying, and managing these risks.
  • “TMV-Based Capital Allocation for Multivariate Risks” by Maochao Xu describes a novel capital allocation framework based on a Tail Mean-Variance principle.  This approach allows for controlling the magnitude and variability of tail risks simultaneously.

The Variance “Articles in Press” section can be accessed from the Variance home page.

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