Autocorrelation


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Autocorrelation

The correlation of a variable with itself over successive time intervals. Sometimes called serial correlation.

Serial Correlation

In technical analysis, a measure of how well past occurrences predict future occurrences. Most importantly, serial correlation checks whether and how often a particular price movement will result in a different price movement. Serial correlation lies at the heart of technical analysis. It is also called autocorrelation.
References in periodicals archive ?
Equation 1 accounts for the presence of autocorrelation (also known as serial correlation) in the data through the term n', which indicates the effective number of data points.
The strength of the Autocorrelation function is its ability to identify low repetition rate events with low duty cycle and the ability to separate random events from periodic events.
Finally, we conducted a generalized linear mixed model (GLMM) grouping nearby sampling sites (< 60 m apart), in three groups (low, middle and high elevation), following recommendations provided by the autocorrelation analysis.
column 8 includes a name of the file with a stored autocorrelation function of standard binary sequence for a given transmission system (this function is used during the test of hypothesis with zero correlation coefficient between the bit autocorrelation function of the binary sequence analysed and standard bit autocorrelation function of binary sequence for the system with the name entered in column 1),
The results of the spatial autocorrelation study are presented in figure 3, wherein the global spatial autocorrelation index, "Moran's Index" (equation 6), are presented for each year in the series.
ij] is the spatial weight as described above for global autocorrelation.
After examining the maps, contours and test of spatial autocorrelation of IMR, it was evident that the geographical aspects have effects on infant mortality rates in the districts of Punjab, Pakistan.
Parameters estimated from standard occupancy models using adjacent spatial sampling units may be biased by autocorrelation in availability for detection between replicated observations.
For example, Pagano and Garen (2005) found that a large proportion of unregulated streams in the upper Colorado River Basin showed autocorrelation in the form of a 1-y lag during 1982-2001, the most recent period they evaluated.
Using ADF and autocorrelation, the results show inefficient EMH for both markets.