95 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.The second part of this thesis describes an approach that uses the above asymptotic expansion to invert, the option pricing function and extract the latent volatility, thereby overcoming one of the key difficulties in the estimation problem. The method is applied to estimate three popular stochastic volatility models, two of which have not previously been amenable to maximum likelihood estimation with option price data other than through the use of proxies for the latent volatility.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
In this paper we apply Bayesian methods to estimate a stochastic volatility model using both the pri...
In this paper we develop a general method for deriving closed-form approximations of European option...
We develop a qualitative and quantitative analysis on stochastic volatility models. These models rep...
95 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.The second part of this thesis...
We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
This article describes a maximum likelihood method for estimating the parameters of the standard squ...
This article describes a maximum likelihood method for estimating the parameters of the standard squ...
<div><p>This article describes a maximum likelihood method for estimating the parameters of the stan...
In this paper we apply Bayesian methods to estimate a stochastic volatility model using both the pri...
In this paper we develop a general method for deriving closed-form approximations of European option...
We develop a qualitative and quantitative analysis on stochastic volatility models. These models rep...
95 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.The second part of this thesis...
We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
Based on the fact that realized measures of volatility are affected by measurement errors, we introd...
This article describes a maximum likelihood method for estimating the parameters of the standard squ...
This article describes a maximum likelihood method for estimating the parameters of the standard squ...
<div><p>This article describes a maximum likelihood method for estimating the parameters of the stan...
In this paper we apply Bayesian methods to estimate a stochastic volatility model using both the pri...
In this paper we develop a general method for deriving closed-form approximations of European option...
We develop a qualitative and quantitative analysis on stochastic volatility models. These models rep...