Quantitative finance collector
C++ Matlab VBA/Excel Java Mathematica R/Splus Net Code Site Other
Sep 29

Assessing the Performance of Different Volatility Estimators: A Monte Carlo Analysis

Posted by abiao at 13:36 | Paper Review | Comments(2) | Reads(8232)
A great paper by Cartea, Álvaro and Karyampas, Dimitrios, published in Applied Mathematical Finance, Volume 19, Number 6, 1 December 2012 , pp. 535-552(18).

We test the performance of different volatility estimators that have recently been proposed in the literature and have been designed to deal with problems arising when ultra high-frequency data are employed: microstructure noise and price discontinuities. Our goal is to provide an extensive simulation analysis for different levels of noise and frequency of jumps to compare the performance of the proposed volatility estimators. We conclude that the maximum likelihood estimator filter (MLE-F), a two-step parametric volatility estimator proposed by Cartea and Karyampas (2011a; The relationship between the volatility returns and the number of jumps in financial markets, SSRN eLibrary, Working Paper Series, SSRN), outperforms most of the well-known high-frequency volatility estimators when different assumptions about the path properties of stock dynamics are used.

Journal paper, Working paper

Download our design home app on your mobile devices.
This article is top quality, one can find quite a few exclusive things that cannot be seen on other weblogs, really handy but yet very accurate!
archery king cheats
Pages: 1/1 First page 1 Final page
Add a comment
Enable HTML
Enable UBB
Enable Emots
Nickname   Password   Optional
Site URI   Email   [Register]