השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| מודל GARCH לא-לינארי× | מודל TGARCH (Threshold GARCH)× | |
|---|---|---|
| תחום | אקונומטריקה | אקונומטריקה |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 1991-1993 | 1993-1994 |
| הוגה השיטה≠ | Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| סוג≠ | Volatility model | Asymmetric volatility model |
| מקור מכונן≠ | 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 ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| כינויים | NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| קשורות | 6 | 6 |
| תקציר≠ | 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 Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative. |
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