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AR(p)-based detrended fluctuation analysis

Alvarez-Ramirez, J. and E. Rodriguez

Physica A: Statistical Mechanics and its Applications, 2018, vol. 502, issue C, 49-57

Abstract: Autoregressive models are commonly used for modeling time-series from nature, economics and finance. This work explored simple autoregressive AR(p) models to remove long-term trends in detrended fluctuation analysis (DFA). Crude oil prices and bitcoin exchange rate were considered, with the former corresponding to a mature market and the latter to an emergent market. Results showed that AR(p)-based DFA performs similar to traditional DFA. However, the former DFA provides information on stability of long-term trends, which is valuable for understanding and quantifying the dynamics of complex time series from financial systems.

Keywords: Detrended fluctuation analysis; Detrending method; Autoregressive model; Crude oil market; Bitcoin (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:49-57