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MULTIFRACTAL ANALYSIS WITH DETRENDING WEIGHTED AVERAGE ALGORITHM OF HISTORICAL VOLATILITY.
- Source :
- Fractals; Aug2021, Vol. 29 Issue 5, p1-11, 11p
- Publication Year :
- 2021
-
Abstract
- In this paper, we develop the multifractal detrending weighted average algorithm of historical volatility (MF-DHV) for one-dimensional multifractal measure based on the classical multifractal detrended fluctuation analysis (MF-DFA). In the calculation process of getting a local trend for MF-DHV, historical volatility is taken to develop an moving average algorithm, which is different from the simple moving average function in multifractal detrended moving average (MF-DMA). We assess the performance of three methods such as MF-DFA, MF-DMA, and MF-DHV based on the p-model multiplicative cascading constructed time series. The computational results show that all the estimated generalized Hurst exponent H (q) , the scaling exponent τ (q) , and the singularity spectrum f (α) of MF-DHV are in good agreement with the theoretical values. In addition, we also calculate the standard deviations of H err and τ err for three methods, and the lowest errors in MF-DHV provides the most accurate estimates. To avoid the accidental selection of parameters, we change the total length of the generated multifractal simulation data and p-value, respectively. It is found that in all the cases, the MF-DHV outperforms the other two methods. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0218348X
- Volume :
- 29
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Fractals
- Publication Type :
- Academic Journal
- Accession number :
- 151831877
- Full Text :
- https://doi.org/10.1142/S0218348X21501930