Second-order moving average and scaling of stochastic time series

By E. Alessio, Anna Filomena Carbone, G. Castelli, V. Frappietro. 2002

405 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Condensed Matter Physics, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/a920f968029153d2692fedcd13c15f08e081412f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Ladislav Kristoufek
2. T. Di Matteo
3. Shu-Peng Chen
4. Miloslav S. Vosvrda
5. Jozef Baruník
6. Ling-Yun He
7. H. Eugene Stanley

In Condensed Matter Physics

1. Ladislav Kristoufek
2. T. Di Matteo
3. Miloslav S. Vosvrda
4. Shu-Peng Chen
5. Jozef Baruník
6. Ling-Yun He
7. Longbing Xu
8. Jie Cao

In Economics and Econometrics

1. Ladislav Kristoufek
2. Miloslav S. Vosvrda
3. Guangxi Cao
4. Longbing Xu
5. Jie Cao
6. Ling-Yun He
7. Shu-Peng Chen
8. Jozef Baruník

Citations in the corpus

• Time-dependent Hurst exponent in financial time series (2004, methodology): “For the sake of clarity, we begin with a summary of the DMA algorithm [9].”
• Measuring capital market efficiency: Global and local correlations structure (2012, methodology): “r of the polynomial t over all boxes with length s, scale according to F2 DFA (s) /s2H [28]. Note that we use s min= 5 and s max= T=5. 4.1.2. Detrending moving average Detrending moving average (DMA) [1] is based on a moving average ltering. For a window length , we construct a centered moving avera”
• Multi-scaling in finance (2007, methodology): “Let us start by mentioning the most popular: the detrended fluctuation analysis (DFA) (Peng et al. 1994, Vandewalle and Ausloos 1997, Viswanathan et al. 1997, Ausloos et al. 1999, Janosi et al. 1999, Liu et al. 1999, Raberto et al. 1999, Stanley et al. 1999, Ausloos 2000, Hu et al. 2001, Chen et al.”
• A new approach to quantify power-law cross-correlation and its application to commodity markets (2011, methodology): “Meanwhile, Detrended Moving Average (DMA), which can filter the trends by the moving average, is based on the Moving Averaging (MA) or mobile average technique proposed by Vandewalle and Ausloos [27, 28], and then further developed to quantify long-range auto-correlation in non-stationary fluctuatio”
• Multifractal detrended cross-correlations between the Chinese exchange market and stock market (2012, methodology): “Concerning the methodology, Jiang and Zhou created MF-X-DMA [28] which is an extension of [27] using MF-DMA [40] and DMA [41].”