Author: Samuel Frame
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
The hypothesis that asset returns are log-normally distributed has been widely rejected. The extant literature has shown that empirical asset returns are highly skewed and leptokurtic (fat tails). The Affine Jump-Diffusion (AJD) model improves upon the log-normal specification by adding a jump component to the return process. The two-sided jump-diffusion (TSJD) model further improves upon the AJD specification by allowing for the tail behavior of the return distribution to be asymmetrical. The Pareto-Beta (Ramezani and Zeng, 1998) and the Double Exponential (Kou, 2002) models present two alternative TSJD specifications. Under the Pareto-Beta specification, two Poisson processes govern the arrival rate of good and bad news, leading to Pareto distributed up-jumps or Beta distributed down-jumps in prices. Under the Double Exponential specification, a single Poisson process generates jumps in returns but the up and down magnitudes are generated by two exponential distributions. Both specifications results in highly asymmetric jump diffusion processes with desirable empirical and theoretical features. Accordingly, these models have been widely adopted in the portfolio choice, option pricing, and other branches of the literature. The primary objective of this paper is to contribute to the econometric methods for estimating the parameters of the TSJD models. Relying on the Bayesian approach, we develop a Markov Chain Monte Carlo (MCMC) estimation technique that is appropriate to these specifications. We then provide an empirical assessment of these model using daily returns for the S&P-500 and the NASDAQ indexes, as well as individual stocks. We complete our analysis by providing a comparison of the estimated parameters under the MCMC and the MLE methodologies.
Bayesian Estimation of Asymmetric Jump-Diffusion Processes
Author: Samuel Frame
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
The hypothesis that asset returns are log-normally distributed has been widely rejected. The extant literature has shown that empirical asset returns are highly skewed and leptokurtic (fat tails). The Affine Jump-Diffusion (AJD) model improves upon the log-normal specification by adding a jump component to the return process. The two-sided jump-diffusion (TSJD) model further improves upon the AJD specification by allowing for the tail behavior of the return distribution to be asymmetrical. The Pareto-Beta (Ramezani and Zeng, 1998) and the Double Exponential (Kou, 2002) models present two alternative TSJD specifications. Under the Pareto-Beta specification, two Poisson processes govern the arrival rate of good and bad news, leading to Pareto distributed up-jumps or Beta distributed down-jumps in prices. Under the Double Exponential specification, a single Poisson process generates jumps in returns but the up and down magnitudes are generated by two exponential distributions. Both specifications results in highly asymmetric jump diffusion processes with desirable empirical and theoretical features. Accordingly, these models have been widely adopted in the portfolio choice, option pricing, and other branches of the literature. The primary objective of this paper is to contribute to the econometric methods for estimating the parameters of the TSJD models. Relying on the Bayesian approach, we develop a Markov Chain Monte Carlo (MCMC) estimation technique that is appropriate to these specifications. We then provide an empirical assessment of these model using daily returns for the S&P-500 and the NASDAQ indexes, as well as individual stocks. We complete our analysis by providing a comparison of the estimated parameters under the MCMC and the MLE methodologies.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
The hypothesis that asset returns are log-normally distributed has been widely rejected. The extant literature has shown that empirical asset returns are highly skewed and leptokurtic (fat tails). The Affine Jump-Diffusion (AJD) model improves upon the log-normal specification by adding a jump component to the return process. The two-sided jump-diffusion (TSJD) model further improves upon the AJD specification by allowing for the tail behavior of the return distribution to be asymmetrical. The Pareto-Beta (Ramezani and Zeng, 1998) and the Double Exponential (Kou, 2002) models present two alternative TSJD specifications. Under the Pareto-Beta specification, two Poisson processes govern the arrival rate of good and bad news, leading to Pareto distributed up-jumps or Beta distributed down-jumps in prices. Under the Double Exponential specification, a single Poisson process generates jumps in returns but the up and down magnitudes are generated by two exponential distributions. Both specifications results in highly asymmetric jump diffusion processes with desirable empirical and theoretical features. Accordingly, these models have been widely adopted in the portfolio choice, option pricing, and other branches of the literature. The primary objective of this paper is to contribute to the econometric methods for estimating the parameters of the TSJD models. Relying on the Bayesian approach, we develop a Markov Chain Monte Carlo (MCMC) estimation technique that is appropriate to these specifications. We then provide an empirical assessment of these model using daily returns for the S&P-500 and the NASDAQ indexes, as well as individual stocks. We complete our analysis by providing a comparison of the estimated parameters under the MCMC and the MLE methodologies.
Bayesian Prediction for a Jump Diffusion Process
Full Bayesian Analysis for Price Calculation in Jump-diffusion Models
Ill-posedness of Parameter Estimation in Jump Diffusion Processes
A Repeat Purchase Diffusion Model: Bayesian Estimation and Control
Author: Gary L. Lilien
Publisher: Sagwan Press
ISBN: 9781377061207
Category : Business & Economics
Languages : en
Pages : 58
Book Description
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Publisher: Sagwan Press
ISBN: 9781377061207
Category : Business & Economics
Languages : en
Pages : 58
Book Description
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Parameter Estimation for the Drift of a Time-inhomogeneous Jump Diffusion Process
A Repeat Purchase Diffusion Model
Parameters Estimation for Jump-diffusion Process Based on Low and High Frequency Data
Estimation of Jump-diffusion Processes Via Empirical Characteristic Functions
Author: Maria Semenova
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Thèse. HEC. 2006
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Thèse. HEC. 2006