Relevant bibliographies by topics / Elicitabilità

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters

Academic literature on the topic 'Elicitabilità'

Author: Grafiati
Published: 9 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Elicitabilità"

1

Ziegel, Johanna F. "COHERENCE AND ELICITABILITY." Mathematical Finance 26, no. 4 (2014): 901–18. http://dx.doi.org/10.1111/mafi.12080.

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He, Xue Dong, Steven Kou, and Xianhua Peng. "Risk Measures: Robustness, Elicitability, and Backtesting." Annual Review of Statistics and Its Application 9, no. 1 (2022): 141–66. http://dx.doi.org/10.1146/annurev-statistics-030718-105122.

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Risk measures are used not only for financial institutions’ internal risk management but also for external regulation (e.g., in the Basel Accord for calculating the regulatory capital requirements for financial institutions). Though fundamental in risk management, how to select a good risk measure is a controversial issue. We review the literature on risk measures, particularly on issues such as subadditivity, robustness, elicitability, and backtesting. We also aim to clarify some misconceptions and confusions in the literature. In particular, we argue that, despite lacking some mathematical c
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3

Fissler, Tobias, and Johanna F. Ziegel. "Higher order elicitability and Osband’s principle." Annals of Statistics 44, no. 4 (2016): 1680–707. http://dx.doi.org/10.1214/16-aos1439.

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Nolde, Natalia, and Johanna F. Ziegel. "Elicitability and backtesting: Perspectives for banking regulation." Annals of Applied Statistics 11, no. 4 (2017): 1833–74. http://dx.doi.org/10.1214/17-aoas1041.

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Nolde, Natalia, and Johanna F. Ziegel. "Rejoinder: “Elicitability and backtesting: Perspectives for banking regulation”." Annals of Applied Statistics 11, no. 4 (2017): 1901–11. http://dx.doi.org/10.1214/17-aoas1041f.

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Chen, James Ming. "Coherence Versus Elicitability in Measures of Market Risk." International Advances in Economic Research 20, no. 3 (2014): 355–56. http://dx.doi.org/10.1007/s11294-014-9480-1.

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Holzmann, Hajo, and Bernhard Klar. "Discussion of “Elicitability and backtesting: Perspectives for banking regulation”." Annals of Applied Statistics 11, no. 4 (2017): 1875–82. http://dx.doi.org/10.1214/17-aoas1041a.

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Schmidt, Patrick. "Discussion of “Elicitability and backtesting: Perspectives for banking regulation”." Annals of Applied Statistics 11, no. 4 (2017): 1883–85. http://dx.doi.org/10.1214/17-aoas1041b.

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Davis, Mark H. A. "Discussion of “Elicitability and backtesting: Perspectives for banking regulation”." Annals of Applied Statistics 11, no. 4 (2017): 1886–87. http://dx.doi.org/10.1214/17-aoas1041c.

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Zhou, Chen. "Discussion on “Elicitability and backtesting: Perspectives for banking regulation”." Annals of Applied Statistics 11, no. 4 (2017): 1888–93. http://dx.doi.org/10.1214/17-aoas1041d.

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Dissertations / Theses on the topic "Elicitabilità"

1

RUFFO, CHIARA MARIA. "Relevant Properties of the Lambda Value at Risk and Markov Switching Mixture of Multivariate Gaussian Distributions in a Bayesian Framework." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2019. http://hdl.handle.net/10281/243541.

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Le misure di rischio e l’asset allocation sono questioni di fondamentale importanza per i mercati finanziari. Lo studio è suddiviso in due parti. Nella prima parte vengono dimostrate proprietà molto importanti per il Lambda Value at Risk, mentre nella seconda parte vengono utilizzati modelli Markov Switching per modellizzare i rendimenti di serie finanziarie e viene introdotta una regola di trade basata sui regimi. L’ultima crisi finanziaria ha evidenziato le debolezze del Value at Risk. Per questo l’interesse verso misure di rischio alternative è aumentato notevolmente negli ultimi anni.
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Wimmerstedt, Lisa. "Backtesting Expected Shortfall: the design and implementation of different backtests." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172444.

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In recent years, the question of whether Expected Shortfall is possible to backtest has been a hot topic after the findings of Gneiting in 2011 that Expected Shortfall lacks a mathematical property called elicitability. However, new research has indicated that backtesting of Expected Shortfall is in fact possible and that it does not have to be very difficult. The purpose of this thesis is to show that Expected Shortfall is in fact backtestable by providing six different examples of how a backtest could be designed without exploiting the property of elicitability. The different approaches are
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Book chapters on the topic "Elicitabilità"

1

Roccioletti, Simona. "Elicitability." In Backtesting Value at Risk and Expected Shortfall. Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-11908-9_3.

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2

Chen, James Ming. "Latent Perils: Stressed VaR, Elicitability, and Systemic Effects." In Postmodern Portfolio Theory. Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/978-1-137-54464-3_17.

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3

Wüthrich, Mario V., and Michael Merz. "Predictive Modeling and Forecast Evaluation." In Springer Actuarial. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12409-9_4.

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AbstractThis chapter is the core theoretical chapter on predictive modeling, forecast evaluation and model selection. The main problem in actuarial modeling is to forecast and price future claims. For this, we build predictive models, and this chapter deals with assessing and ranking these predictive models. We therefore introduce the mean squared error of prediction (MSEP) and, more generally, the expected generalization loss (GL) to assess predictive models. This chapter is complemented by a more decision-theoretic approach to forecast evaluation, it discusses deviance losses, proper scoring
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Journal articles
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