Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Modele de risc de lichiditate (Amihud, Roll, LOT)× | Modelul HAR-RV al volatilității realizate× | |
|---|---|---|
| Domeniu | Finanțe | Finanțe |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 2002 | 2009 |
| Autorul original≠ | Amihud (2002); Roll (1984); Lesmond, Ogden & Trzcinka (LOT) | Fulvio Corsi |
| Tip≠ | Liquidity / illiquidity measurement models | Linear time-series regression for volatility |
| Sursa seminală≠ | Amihud, Y. (2002). Illiquidity and Stock Returns: Cross-Section and Time-Series Effects. Journal of Financial Markets, 5(1), 31-56. DOI ↗ | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗ |
| Denumiri alternative≠ | Amihud illiquidity, Roll spread estimator, LOT spread measure, Lesmond-Ogden-Trzcinka measure | HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility) |
| Înrudite | 5 | 5 |
| Rezumat≠ | Liquidity Risk Models are a family of measures that quantify how easily an asset trades by capturing its price impact, its effective bid-ask spread, and a holding-period adjustment. The family brings together the Amihud illiquidity ratio (Amihud, 2002), the Roll serial-covariance spread estimator (Roll, 1984), and the LOT (Lesmond-Ogden-Trzcinka) realised-spread measure. | The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility. |
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