পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| এক্সপোনেনশিয়াল GARCH (EGARCH)× | দীর্ঘ-স্মৃতি মডেল (ARFIMA, FIGARCH)× | |
|---|---|---|
| ক্ষেত্র≠ | অর্থমিতি | অর্থায়ন |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 1991 | 1980 |
| প্রবর্তক≠ | Nelson | Granger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH) |
| ধরন≠ | Conditional volatility model (asymmetric GARCH variant) | Fractionally integrated time series model |
| মৌলিক উৎস≠ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ | Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15-29. DOI ↗ |
| অপর নাম≠ | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | ARFIMA, FIGARCH, fractionally integrated models, fractional integration |
| সম্পর্কিত | 4 | 4 |
| সারসংক্ষেপ≠ | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. | Long-memory models are fractional-integration methods that capture genuine long memory through a hyperbolically decaying autocorrelation structure. ARFIMA, introduced by Granger and Joyeux (1980), models long memory in return series, while FIGARCH, introduced by Baillie, Bollerslev and Mikkelsen (1996), captures long memory in volatility series; the parameter d measures the degree of fractional integration. |
| ScholarGateডেটাসেট ↗ |
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