পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| অরৈখিক GARCH মডেল× | ডিসি-জিএআরসিএইচ মডেল (ডাইনামিক কন্ডিশনাল কোরিলেশন)× | |
|---|---|---|
| ক্ষেত্র | অর্থমিতি | অর্থমিতি |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 1991-1993 | 2002 |
| প্রবর্তক≠ | Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH | Robert F. Engle |
| ধরন≠ | Volatility model | Multivariate volatility model |
| মৌলিক উৎস≠ | Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance, 48(5), 1779-1801. DOI ↗ | Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗ |
| অপর নাম | NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model | DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC |
| সম্পর্কিত≠ | 6 | 5 |
| সারসংক্ষেপ≠ | The Nonlinear GARCH model extends the standard GARCH framework to capture asymmetric and nonlinear responses of conditional volatility to past shocks. It allows negative returns (bad news) to amplify volatility more than positive returns of equal magnitude, a phenomenon known as the leverage effect, which is empirically pervasive in financial markets. | The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series. |
| ScholarGateডেটাসেট ↗ |
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