পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| চরম মান তত্ত্ব (Extreme Value Theory - EVT)× | শর্তাধীন ঝুঁকি-মূল্য (প্রত্যাশিত ঘাটতি)× | |
|---|---|---|
| ক্ষেত্র | অর্থায়ন | অর্থায়ন |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2001 | 2000 |
| প্রবর্তক≠ | Coles (textbook treatment); McNeil, Frey & Embrechts | Rockafellar & Uryasev (2000); Acerbi & Tasche (2002) |
| ধরন≠ | Tail / extreme-event model | Coherent tail-risk measure |
| মৌলিক উৎস≠ | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 | Rockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗ |
| অপর নাম | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold | CVaR, expected shortfall, average value-at-risk, tail VaR |
| সম্পর্কিত | 5 | 5 |
| সারসংক্ষেপ≠ | Extreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold. | Conditional Value-at-Risk (CVaR), also called Expected Shortfall, is a coherent tail-risk measure that quantifies the conditional expectation of losses beyond the Value-at-Risk threshold. It was introduced for optimization by Rockafellar and Uryasev (2000) and shown to be coherent by Acerbi and Tasche (2002), and it has replaced VaR as the regulatory standard under Basel III/IV. |
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