Methods for detrending success metrics to account for inflationary and deflationary factors*
By Alexander M. Petersen, Orion Penner, H. Eugene Stanley. 2011
533 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/070e07233e009423dbf38dd3add0dee6ecaf7434
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Alessandro Vespignani
- Romualdo Pastor-Satorras
- Guido Caldarelli
- Stefano Battiston
- Jean-Philippe Bouchaud
- Ladislav Kristoufek
- Claudio Castellano
In Economics and Econometrics
- Stefano Battiston
- Rahul Kaushik
- Alessandro Vespignani
- Guido Caldarelli
- Michelangelo Puliga
- Jean-Philippe Bouchaud
- Ladislav Kristoufek
- Claudio Castellano
Citations in the corpus
- Multifractal detrended cross-correlations between the Chinese exchange market and stock market (2012, unknown): “[23] proposes the Qcc(m) test method.”
- Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market (2014, unknown): “Although several researchers [20–29] discuss the DCCA methodology, little attention focuses on the asymmetries of the cross-correlation.”
- Mixed-correlated ARFIMA processes for power-law cross-correlations (2013, background): “As the financial time series provide sufficient number of observations and they have been shown to possess long-range auto-correlations (volatility, traded volume, signs of changes and absolute returns to name the most frequently studied ones), these also create an appropriate setting for the power-”