Special Issue "Risk vs Performance Measures: Robustness, Elicitability and Time-Dependency"

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (31 October 2018)

Special Issue Editor

Guest Editor
Prof. Dr. Damiano Rossello

Department of Economics, University of Catania–Corso Italia, 55, I- 95129, Italy
Website | E-Mail
Interests: stochastic models for risk and performance measures; statistical robustness of risk and performance functionals

Special Issue Information

Dear Colleagues,

I would like to invite you to submit a paper to a forthcoming Special Issue on “Risk vs Performance Measures: Robustness, Elicitability and Time-Dependency”.

This Special Issue aims to collect advances in the theory and practice of monetary risk measures, with special emphasis on the duality between risk and performance measures. It is well-established how investors deal with a trade-off between reward and risk associated with a financial position, either in a static or in a dynamic fashion. The literature devoted to the analysis of this trade-off needs to be enforced by focusing on the connection among risk measures, acceptable cash flows and indices of performance then delivering a unifying framework.

Submissions providing theoretical as well as empirical results are welcome. The submitted papers are expected to provide insights on the robustness, the elicitability and the time-consistency or path-dependency of the various measures considered in the unified framework.

Prof. Dr. Damiano Rossello
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. Risks 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 350 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.

Keywords

  • Elicitable risk functionals
  • Statistical robustness
  • Duality between risk and performance measures
  • Acceptable indices of performance
  • Elicitable indices of performance

Published Papers (4 papers)

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Research

Open AccessArticle Firm’s Risk-Return Association Facets and Prospect Theory Findings—An Emerging versus Developed Country Context
Received: 13 November 2018 / Revised: 3 December 2018 / Accepted: 4 December 2018 / Published: 8 December 2018
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Abstract
A risk-return association under normal market conditions can be conventional positive (risk-averse) or “paradoxical” negative (risk seeking). This study has the objective to investigate whether such an association is stable across market trends (i.e., bull and bear) and for overall, industry-classified and partitions [...] Read more.
A risk-return association under normal market conditions can be conventional positive (risk-averse) or “paradoxical” negative (risk seeking). This study has the objective to investigate whether such an association is stable across market trends (i.e., bull and bear) and for overall, industry-classified and partitions sub-samples after controlling for a firm’s age, size, leverage and liquidity using operating performance risk-return measures. In total, this study analyses 2666 firms (1199 firms from 15 developed countries and 1467 firms from 12 emerging countries) for the period of 1999–2015. Results show that in the overall and bull sub-periods, firms across countries are showing conventional positive (superior firms) and “paradoxical” negative (poor firms) in most cases. However, in the bear sub-periods all firms from emerging countries are risk seeking in order to maintain their position in the pecking order. Full article
Open AccessArticle A Discussion on Recent Risk Measures with Application to Credit Risk: Calculating Risk Contributions and Identifying Risk Concentrations
Received: 11 October 2018 / Revised: 26 November 2018 / Accepted: 30 November 2018 / Published: 7 December 2018
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Abstract
In both financial theory and practice, Value-at-risk (VaR) has become the predominant risk measure in the last two decades. Nevertheless, there is a lively and controverse on-going discussion about possible alternatives. Against this background, our first objective is to provide a current overview [...] Read more.
In both financial theory and practice, Value-at-risk (VaR) has become the predominant risk measure in the last two decades. Nevertheless, there is a lively and controverse on-going discussion about possible alternatives. Against this background, our first objective is to provide a current overview of related competitors with the focus on credit risk management which includes definition, references, striking properties and classification. The second part is dedicated to the measurement of risk concentrations of credit portfolios. Typically, credit portfolio models are used to calculate the overall risk (measure) of a portfolio. Subsequently, Euler’s allocation scheme is applied to break the portfolio risk down to single counterparties (or different subportfolios) in order to identify risk concentrations. We first carry together the Euler formulae for the risk measures under consideration. In two cases (Median Shortfall and Range-VaR), explicit formulae are presented for the first time. Afterwards, we present a comprehensive study for a benchmark portfolio according to Duellmann and Masschelein (2007) and nine different risk measures in conjunction with the Euler allocation. It is empirically shown that—in principle—all risk measures are capable of identifying both sectoral and single-name concentration. However, both complexity of IT implementation and sensitivity of the risk figures w.r.t. changes of portfolio quality vary across the specific risk measures. Full article
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Open AccessArticle An Intersection–Union Test for the Sharpe Ratio
Received: 26 February 2018 / Revised: 12 April 2018 / Accepted: 13 April 2018 / Published: 19 April 2018
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Abstract
An intersection–union test for supporting the hypothesis that a given investment strategy is optimal among a set of alternatives is presented. It compares the Sharpe ratio of the benchmark with that of each other strategy. The intersection–union test takes serial dependence into account [...] Read more.
An intersection–union test for supporting the hypothesis that a given investment strategy is optimal among a set of alternatives is presented. It compares the Sharpe ratio of the benchmark with that of each other strategy. The intersection–union test takes serial dependence into account and does not presume that asset returns are multivariate normally distributed. An empirical study based on the G–7 countries demonstrates that it is hard to find significant results due to the lack of data, which confirms a general observation in empirical finance. Full article
Open AccessArticle Lambda Value at Risk and Regulatory Capital: A Dynamic Approach to Tail Risk
Received: 17 January 2018 / Revised: 24 February 2018 / Accepted: 1 March 2018 / Published: 6 March 2018
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Abstract
This paper presents the first methodological proposal of estimation of the ΛVaR. Our approach is dynamic and calibrated to market extreme scenarios, incorporating the need of regulators and financial institutions in more sensitive risk measures. We also propose a [...] Read more.
This paper presents the first methodological proposal of estimation of the Λ V a R . Our approach is dynamic and calibrated to market extreme scenarios, incorporating the need of regulators and financial institutions in more sensitive risk measures. We also propose a simple backtesting methodology by extending the V a R hypothesis-testing framework. Hence, we test our Λ V a R proposals under extreme downward scenarios of the financial crisis and different assumptions on the profit and loss distribution. The findings show that our Λ V a R estimations are able to capture the tail risk and react to market fluctuations significantly faster than the V a R and expected shortfall. The backtesting exercise displays a higher level of accuracy for our Λ V a R estimations. Full article
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