Please use this identifier to cite or link to this item:
Title: Monte Carlo Pricing of Derivative Securities and Uncertainty in Volatility Estimation
Authors: Joplin, George A.
Keywords: Text;Honors papers;Mathematics and Computer Science, Department of;Economics, Department of;Student research
Issue Date: May-2011
Publisher: Memphis, Tenn. : Rhodes College
Abstract: In the standard time-inhomogeneous di usion model, estimation of the volatility function is far more important for Monte Carlo pricing than estimation of the drift function (due to a standard application of Girsanov's Theorem). As such, we study the distribution of option prices under the uncertainty of volatility function estimation. First, we run Monte Carlo simulations to price a variety of options using a xed estimate of the volatility function. Then, we run Monte Carlo simulations to price a variety of options using a bootstrapped re-estimation of volatility function in each Monte Carlo trial. The di erences in the resulting distributions of option prices may have implications for thinking about the bid-ask spread on an option price, and can be compared to historical data to gain a more complete perspective on the acceptability of various American-style option prices. Description: George Joplin granted permission for the digitization of this paper. It was submitted by CD.
Description: George A. Joplin granted permission for his paper to be published in DLynx. He submitted at PDF copy of his paper.
Appears in Collections:Honors Papers

Files in This Item:
File Description SizeFormat 
Joplin_George_Honors_2011[1].pdf806.6 kBAdobe PDFThumbnail

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.