alexa Critical Analysis of the Stochastic Volatility of the S
ISSN: 2151-6219

Business and Economics Journal
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Critical Analysis of the Stochastic Volatility of the S&P 500 Index between 2000-2010

Brandon Renfro* and Rebecca Asante

Hampton University, Hampton, Virginia, USA

*Corresponding Author:
Brandon Renfro
Instructor, Hampton University
Hampton, Virginia, USA
Tel: +374 10 23-72-61
E-mail: [email protected]

Received date: July 07, 2014; Accepted date: August 10, 2014; Published date: August 17, 2014

Citation: Brandon Renfro and Rebecca Asante (2014) Critical Analysis of the Stochastic Volatility of the S&P 500 Index between 2000-2010. Bus Eco J 5:102. doi: 10.4172/2151-6219.1000102

Copyright: © 2014 Renfro B, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



This paper presents an empirical analysis of the correlation between some demographic and financial predictor variables and the stochastic volatility of the Standard and Poor’s (S&P) 500 index between January 2000 and December 2010 inclusive. In particular, the predictor variables used for the statistical analysis are: prime rate (PR)(t), the United States population proportion between the ages of 40-64 (PP(t)), inflation rate (IR(t)), logarithm of the unemployment rate (log(UE)(t)), and consumer confidence (CC)(t)). The empirical relationship between these variables is established using multiple regression analytic techniques with EXCEL software. The relevance of each predictor variable is assessed by inspection of the P-value of the associated multiple regression coefficient. The plot of the observed and modeled S&P 500 index for the 149 data points (months) corresponding to the period spanning January 2000 and December 2010 elucidates the potential of the empirical model to forecast the volatility of the S&P 500 for the period in question. The constructed empirical multiple regression model for the observed S&P 500 has the configuration:

Ŷ= -160.313+7331.269*(PR)(t)+4780.536*(PP)(t)+611.035*(IR)(t)


The adjusted R2 for the empirical model is approximately 0.49 .This means that during the period 2000-2010, about 49% of the variability of the S&P 500 volatility could be explained by the information accrued from the joint influence of the five predictor variables.


Share This Page

Additional Info

Loading Please wait..
Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version