Special Issue "Advances in Financial and Insurance Risk Management – Selected Papers from the Seventh CEQURA Conference, 26-27 September 2016, Munich, Germany"

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074).

Deadline for manuscript submissions: closed (28 February 2017).

Special Issue Editor

Prof. Dr. Stefan Mittnik
E-Mail
Guest Editor
Center for Quantitative Risk Analysis (CEQURA) and Department of Statistics, Ludwig Maximilian University of Munich, Germany
Interests: statistics; econometrics; financial econometrics; quantitative finance; empirical finance; risk management; time series; volatility; forecasting
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Special Issue Information

Dear Colleagues,

The 7th CEQURA Conference on Advances in Financial and Insurance Risk Management is organized by the Society for Financial and Insurance Econometrics in collaboration with the Montreal Institute of Structured Products and Derivatives and Bayerisches Finanz Zentrum. It provides a platform for presenting and discussing current developments in research and industry, and fosters the exchange between academics and practitioners from the risk management community. The conference will take place in Munich, Germany, on 26-27 September 2016.

The conference serves to discuss various aspects of financial and insurance risk management. Topics of interest include:

  • Market, credit, operational, liquidity and energy risk
  • Stress testing and scenario analysis
  • Systemic risk in banking and insurance
  • Solvency II and Basel III
  • Dependence modeling
  • Risk dynamics
  • Real- and financial-sector interactions
For further details about the conference programme, please see the conference page. This Special Issue will collect selected papers from the conference.

Prof. Dr. Stefan Mittnik
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Open AccessArticle
The Solvency II Standard Formula, Linear Geometry, and Diversification
J. Risk Financial Manag. 2017, 10(2), 11; https://doi.org/10.3390/jrfm10020011 - 18 May 2017
Abstract
The core of risk aggregation in the Solvency II Standard Formula is the so-called square root formula. We argue that it should be seen as a means for the aggregation of different risks to an overall risk rather than being associated with variance-covariance [...] Read more.
The core of risk aggregation in the Solvency II Standard Formula is the so-called square root formula. We argue that it should be seen as a means for the aggregation of different risks to an overall risk rather than being associated with variance-covariance based risk analysis. Considering the Solvency II Standard Formula from the viewpoint of linear geometry, we immediately find that it defines a norm and therefore provides a homogeneous and sub-additive tool for risk aggregation. Hence, Euler’s Principle for the reallocation of risk capital applies and yields explicit formulas for capital allocation in the framework given by the Solvency II Standard Formula. This gives rise to the definition of diversification functions, which we define as monotone, subadditive, and homogeneous functions on a convex cone. Diversification functions constitute a class of models for the study of the aggregation of risk and diversification. The aggregation of risk measures using a diversification function preserves the respective properties of these risk measures. Examples of diversification functions are given by seminorms, which are monotone on the convex cone of non-negative vectors. Each L p norm has this property, and any scalar product given by a non-negative positive semidefinite matrix does as well. In particular, the Standard Formula is a diversification function and hence a risk measure that preserves homogeneity, subadditivity and convexity. Full article
Open AccessArticle
On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts
J. Risk Financial Manag. 2017, 10(1), 7; https://doi.org/10.3390/jrfm10010007 - 07 Feb 2017
Cited by 2
Abstract
This paper establishes a selection of stylized facts for high-frequency cointegrated processes, based on one-minute-binned transaction data. A methodology is introduced to simulate cointegrated stock pairs, following none, some or all of these stylized facts. AR(1)-GARCH(1,1) and MR(3)-STAR(1)-GARCH(1,1) processes contaminated with reversible and [...] Read more.
This paper establishes a selection of stylized facts for high-frequency cointegrated processes, based on one-minute-binned transaction data. A methodology is introduced to simulate cointegrated stock pairs, following none, some or all of these stylized facts. AR(1)-GARCH(1,1) and MR(3)-STAR(1)-GARCH(1,1) processes contaminated with reversible and non-reversible jumps are used to model the cointegration relationship. In a Monte Carlo simulation, the power and size properties of ten cointegration tests are assessed. We find that in high-frequency settings typical for stock price data, power is still acceptable, with the exception of strong or very frequent non-reversible jumps. Phillips–Perron and PGFF tests perform best. Full article
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