10473289%2E2011%2E637876
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This article compares performances of two MCMC samplers to estimate parameters and latent stochastic processes in the standard log-normal stochastic volatility (LNSV) model:
On the other hand, for the affine jump diffusion model (and all models in which Brownian motion is used in the spec- ification of the stochastic volatility), the volatility activity
(a) Local linear estimation of the conditional mean function using the bandwidth h ′ = 5809 ; (b) Estimates of the conditional variance function based on the squared residuals using
This study employs a class of nonlinear asymmetric stochastic volatility model by applying the Box–Cox transformation to the volatility equation and calls it
The study also found that the implied volatility from the Black-Scholes model had more explanatory power than the implied volatility calculated based on Heston 1993, a stochastic
ةيدوعسلا ةيبرعلا ةكلملما ميلعتلا ةرازو فولجا ةعماج ABSTRACT Different models for stochastic volatility for choice evaluate have been presented to catch the volatility effect since
Proposed channel estimation using uncorrelated LS codes in interference free window proposed estimation 1 Using the following properties, we propose the first channel estimation
Based on the estimation of dynamic stock returns volatility of individual firms by using EGARCH, the analysis is continued by regressing the volatility or ln𝜎𝑡2 estimated with
