পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| শর্তাধীন ঝুঁকি-মূল্য (প্রত্যাশিত ঘাটতি)× | ARIMA (Autoregressive Integrated Moving Average) মডেল× | |
|---|---|---|
| ক্ষেত্র≠ | অর্থায়ন | অর্থমিতি |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2000 | 2015 |
| প্রবর্তক≠ | Rockafellar & Uryasev (2000); Acerbi & Tasche (2002) | Box & Jenkins (Box-Jenkins methodology) |
| ধরন≠ | Coherent tail-risk measure | Univariate time-series model |
| মৌলিক উৎস≠ | Rockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 |
| অপর নাম≠ | CVaR, expected shortfall, average value-at-risk, tail VaR | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| সম্পর্কিত | 5 | 5 |
| সারসংক্ষেপ≠ | 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. | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). |
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