Identifier

etd-042910-154228

Abstract

Large data sets are required to store all of the information contained in option chains. The data set we work with includes all U.S. exchange traded put and call options. This data set is part of a larger data set commonly referred to as the National Best Bid Offer (NBBO) data set. The national bid best offer is a Securities and Exchange Commission (SEC) term for the best available ask price and bid price. Brokers must guarantee investors these prices on their trades. We have acquired data for the 5 year period from 2005 to 2009 for all U.S. traded options. Each year of data is approximately 6 gigabytes. The company, (DeltaNeutral - Options Data And End Of Day Downloads, 2010), from which we acquired the data, also has a software package, OptimalTrader, to process the data. For this data to be used in research projects, the data must be accessible by specific underlying security for selected date ranges. This type of data is more useful to the financial mathematics student than the output given by the software provided by DeltaNeutral. The software used in this data manipulation is Matlab. Each individual file of original data was parsed, and new files were written with some reformatting in which the original data was largely reorganized. The new organization will make searching for information from one stock or any specific group of stocks easier to achieve. We have created 3 m-files in Matlab which deal with reformatting the data, error handling, and searching through the original or reformatted data. The result is that new datasets can be created for further studying and manipulation. Future students working with this data should find this method, toolset, and the newly constructed datasets to be useful tools in working with options data and examining option chains.

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Mathematical Sciences

Project Type

Thesis

Date Accepted

2010-04-29

Accessibility

Unrestricted

Subjects

option chain, Matlab, financial engineering

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