A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series

Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility☆

Short-term predictability of crude oil markets: A detrended fluctuation analysis approach

Multifractality is ubiquitously observed in complex natural and socioeconomic systems. Multifractal analysis provides powerful tools to understand the complex nonlinear nature of time series in diverse fields. Inspired by its striking analogy with hydrodynamic turbulence, from which the idea of multifractality originated, multifractal analysis of financial markets has bloomed, forming one of the main directions of econophysics. We review the multifractal analysis methods and multifractal models adopted in or invented for financial time series and their subtle properties, which are applicable to time series in other disciplines. We survey the cumulating evidence for the presence of multifractality in financial time series in different markets and at different time periods and discuss the sources of multifractality. The usefulness of multifractal analysis in quantifying market inefficiency, in supporting risk management and in developing other applications is presented. We finally discuss open problems and further directions of multifractal analysis.

https://iopscience.iop.org/article/10.1088/1361-6633/ab42fb/pdf

Multifractal analysis of financial markets: a review.

Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models

Daily records of international crude oil prices are studied using multifractal analysis methods. Rescaled range Hurst analysis provides evidence that the crude oil market is a persistent process with long-run memory effects. On the other hand, height–height correlation analysis reveals evidence of multifractal structures in the sense that the crude oil dynamics displays mixing of (rough) Hurst exponents. The existence of two characteristic time scales in the order of weeks and quarters is discovered and the corresponding prices dynamics are extracted using moving-average-based filtering. These results seem to demonstrate that the crude oil market is consistent with the random-walk assumption only at time scales of the order of days to weeks. A plausible oil price formation mechanism is discussed in terms of the market dynamics at three different time scales.

Multifractal Hurst analysis of crude oil prices

A simple agent-based model is used to propose an explanation of the source of long-run memory in financial markets. It is shown that the resulting model is equivalent to a neutral-type differential equation in the price dynamics, which displays a persistence property that can be related to memory effects.

Myriam Cisneros

Papers

Multifractal Hurst analysis of crude oil prices

Technical trading can induce long-run memory in financial markets