Detrend

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Detrend

To remove the general drift, tendency, or bent of a set of statistical data as related to time. Often accomplished by regressing a variable or a time index and perhaps the square of the time index and capturing the residuals. A stochastic detrend would be to subtract a moving-average (say for five years) from the value of the variable.

Detrend

The removal of a trend from the consideration of several variables. A detrend may be necessary to discover a company's true financial health. For example, one may detrend increased sales around Christmas time to see a more accurate account of a company's sales in a given year.
References in periodicals archive ?
AIRWeather's reconstructed data involves de-shifting and de-trending the cleaned daily minimum and maximum temperature time series to remove data inconsistencies due to factors unrelated to weather.
Canova (1998a,b) and Massmann and Mitchell (2002) find business cycle inference to be sensitive to the de-trending method employed.
7) In response, therefore, we consider a richer set of de-trending methods, plus a measure of the business cycle derived using an algorithm to detect turning points.
WeatherBook offers statistical de-trending tools allowing users to view the full range of pricing scenarios, and provides flexible P&L reporting capabilities for easy integration with financial software packages.
Even whilst avoiding the most obvious of these pitfalls it must immediately be obvious that the objective of precision in dating will be compromised by the smoothing involved in the de-trending.
All available data were used for the preliminary de-trending of the imbalances indicators.
Admittedly, de-trending the data exacerbates the end-point problem and thus worsens the real-time performance of the model.
Expanded views of some of the longer time series photometry runs are plotted in Figure 2, after de-trending the data and subtracting the mean magnitude.
The time series required de-trending (by differencing at 1 month) and de-seasonalizing (by differencing at 12 months).
Topics include a means for comprehensive analysis of the effect of microarray data preprocessing methods on differentially expressed transcript selection, differentiation detection in microarray normalization, spatial de-trending and normalization methods for two-channel DNA and protein microarray data, a survey of cDNA microarray normalization, technical variations in modeling the joint expression of several genes, analysis for certain data normalization, and array-based analysis for the detection of chromosomal aberrations and copy number variations.
The ABP results are implicitly forecasting future values of actual GDP prior to de-trending (using an IMA(2,2) model).
1 also provides several other new features, including: * Streamlined 'one-click' analysis for rapid pricing with multiple, customizable models * An ability to directly define and model straddles and strangles as well as uncapped weather derivative contracts * Non-parametric de-trending methods for analyzing weather data that exhibits significant non-linear trends over the last 20 to 50 years * Flexible reports allowing users to customize the risk metrics and risk breakdowns included in daily portfolio valuation reports