A new analysis of VIX using mixture of regressions: Examination and short‐term forecasting for the S & P 500 market. Issue 1 (19th January 2018)

• Record Type: Journal Article
• Authors: Miljkovic, Tatjana; SenGupta, Indranil
• Is Part Of: High frequency. Volume 1:Issue 1 (2018)
• Page Start: 53
• Page End: 65
• Publication Date: 2018-01-19
• Subjects: EM algorithm -- empirical analysis -- Lévy processes -- mixture -- modeling -- VIX price index; Time-series analysis -- Periodicals; Big data -- Periodicals; Finance -- Statistical methods -- Periodicals; Mathematical models -- Periodicals; 519.55
• DOI: 10.1002/hf2.10009
• Languages: English
• ISSNs: 2470-6981

Abstract

Abstract: A novel approach to the analysis of S & P 500 market fluctuations is proposed using a K‐component mixture of regressions model. The Barndorff‐Nielsen and Shephard stochastic model is employed where the estimates of jumps of log‐returns are governed by Lévy subordinators. Daily VIX and VIX 2 close prices are analyzed as the indicators of log‐return volatility and the corresponding variance of the S & P 500 index using the mixture model. The behavior of the S & P 500 market from 1 August 2005 to 31 December 2009 is analyzed and forecasted. A set of rules are provided to predict monthly fluctuation in the S & P 500 market. The procedure used in this paper gives a novel approach for constructing an "indicator"of non‐Gaussian jump of an empirical data set in finance using mixture of regression (Gaussian) analysis.