Chaos in historical prices and volatilities with five-dimensional euclidean spaces

Abstract

From the Diagram Accuracy-Deviation and the new quantifier of chaos, this paper presents time series analysis for historical prices, volatilities and returns. The study cases are financial price series of United States Brent Oil (BNO), Wipro Limited (WIT), Nasdaq, Inc. (NDAQ) and SPDR S&P 500 ETF (SPY). Detection of chaos and randomness cover the period from November 2010 to November 2018. This work introduces the chaoticity in the Lorenz’s sense, a new measure for comparison between time series. The set of results enlights the underlying dynamics of the time evolution observed in economic indexes nowadays.