The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Modelling Extremal Events
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“EVT-based approaches allow for more robust identification of extreme events by modeling the tails of temperature distributions, addressing the inadequacies of fixed percentile thresholds.”
From Advancing Heatwave Forecasting via Distribution Informed-Graph Neural Networks (DI-GNNs): Integrating Extreme Value Theory with GNNs (2024) · cites this paper as [30]
In the citing paper
“DI-GNN incorporates Generalized Pareto Distribution (GPD)-derived descriptors into the feature space, adjacency matrix, and loss function to enhance its sensitivity to rare heatwave occurrences.”
From Advancing Heatwave Forecasting via Distribution Informed-Graph Neural Networks (DI-GNNs): Integrating Extreme Value Theory with GNNs (2024) · cites this paper as [30]
In the citing paper
“The Distribution-Informed Graph Neural Network (DI-GNN) represents a significant advancement in the modeling of rare and extreme events, transcending the limitations of traditional feature engineering by embedding Extreme Value Theory (EVT) principles directly into the learning process.”
From Advancing Heatwave Forecasting via Distribution Informed-Graph Neural Networks (DI-GNNs): Integrating Extreme Value Theory with GNNs (2024) · cites this paper as [30]
Citations
Cites
Glas, C. A. W. (2017) · Chapman & Hall/CRC eBooks · doi:10.1201/b19166-11 · Cited by 24
Snapp, R. R. (2014) · Springer eBooks · doi:10.1007/978-1-4614-6170-8_155 · Cited by 3
Time Series Analysis for Heavy-Tailed Processes
Emberchts, P., Klüppelberg, C., & Mikosch, T. (1997) · Springer eBooks · doi:10.1007/978-3-642-33483-2_8 · Cited by 2
Self-citationDefinition and Elementary Properties
Davies, B. (1978) · Applied mathematical sciences · doi:10.1007/978-1-4757-5512-1_1 · Cited by 2
Cited by
Sorted by citations
Artzner, P., Delbaen, F., Eber, J., & Heath, D. (1999) · Mathematical Finance · doi:10.1111/1467-9965.00068 · Cited by 8,849
Conditional value-at-risk for general loss distributions
Rockafellar, R. T., & Uryasev, S. (2002) · Journal of Banking & Finance · doi:10.1016/s0378-4266(02)00271-6 · Cited by 3,850
Empirical properties of asset returns: stylized facts and statistical issues
Rama Cont, A. (2001) · Quantitative Finance · doi:10.1080/713665670 · Cited by 3,511
Extreme Correlation of International Equity Markets
Longin, F. M., & Solnik, B. H. (2001) · The Journal of Finance · doi:10.1111/0022-1082.00340 · Cited by 2,611
Top Incomes in the Long Run of History
Atkinson, A. B., Piketty, T., & Saez, E. (2011) · Journal of Economic Literature · doi:10.1257/jel.49.1.3 · Cited by 2,362
Metadata
- Authors
- Embrechts, P., Klüppelberg, C., & Mikosch, T.
- Affiliations
- Technical University of Munich (DE)
- University of Copenhagen (DK)
- Venue
- Springer eBooks
- Publisher
- Springer Berlin Heidelberg
- Published
- 1997
- OpenAlex
- W2502254989
- Cited by
- 4,402
- References
- 4
- Citations by year
- 2026: 140 · 2025: 137 · 2024: 128 · 2023: 142 · 2022: 136 · 2021: 115 · 2020: 164 · 2019: 142 · 2018: 192 · 2017: 175 · 2016: 198 · 2015: 182 · 2014: 250 · 2013: 200 · 2012: 252
- FWCI
- 46.74
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Probability and Risk Models
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Social Sciences › Economics, Econometrics and Finance › Finance › Stochastic processes and financial applications
- Keywords
- extreme value theory, financial fluctuations, stock market shocks, risk management
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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