'Filtering Noise from Volatility': Paper 5 in a Series 'Uncovering Hidden Dependencies'
REVOLUTION IN UNCOVERING HIDDEN DEPENDENCIES, Forthcoming
7 Pages Posted: 16 Jan 2014 Last revised: 18 Jan 2014
Date Written: March 26, 2013
Abstract
Alexander Izmailov, Ph.D (theoretical physics) and Brian Shay, Ph.D (mathematics), of Market Memory Trading, L.L.C., present in a series of nine (9) white papers, aspects of a revolutionary advance in uncovering hidden dependencies via filtering noise from correlation matrices developed by the New York based company, Market Memory Trading, L.L.C. (MMT). Correlations are quantitative measures of these dependencies and noise filtering increases their accuracy as a decision-making tool, from asset allocation to LIBOR Surveillance and cyber security.
“FILTERING NOISE FROM VOLATILITY.” White Paper 5, dated March 26, 2013, provides a demonstration of the omnipresence of noise in volatilities of returns of financial instruments; and a demonstration that more than 30% of SP500 securities can have percentage change in volatility of more than 10% as a result of noise filtering. Refer to Appendix A for Complete Series.
Keywords: volatility, noise filtering, option trading
JEL Classification: C1, C4, C6, G1, G11, F47, F10, F17, C61, C67
Suggested Citation: Suggested Citation