Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Mertona lēcienu-difūzijas modelis× | GARCH modelis (volatilitātes prognozēšana)× | |
|---|---|---|
| Nozare≠ | Finanses | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1976 | 1986 |
| Autors≠ | Robert C. Merton | Tim Bollerslev |
| Tips≠ | Continuous-time asset price model (diffusion plus Poisson jumps) | Conditional volatility model |
| Pirmavots≠ | Merton, R. C. (1976). Option Pricing When Underlying Stock Returns Are Discontinuous. Journal of Financial Economics, 3(1–2), 125–144. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| Citi nosaukumi≠ | Merton jump-diffusion, jump-diffusion process, Atlama Difüzyon Modeli (Merton Jump-Diffusion) | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | The Merton Jump-Diffusion model, introduced by Robert C. Merton in 1976, extends Geometric Brownian Motion by adding sudden price jumps generated by a Poisson process. It captures the volatility smile and the fat-tailed return behaviour that standard Black-Scholes cannot explain, and is widely used in option pricing and risk management. | The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series. |
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