Should we denoise a time series before calculating correlation? The Next CEO of Stack OverflowLong time scale correlationCorrelation between an event and a time seriesUsing mutual information to estimate correlation between a continuous variable and a categorical variableTime Series (White Noise)Measuring correlation of two time seriesFinding time series mean variance skewness of stationary time seriesWhy do time series need to be stationary for computing cross-correlation?Is cross-correlation valid for time-series such as these (with trends)?Contrasting effects on correlation between two variables with increase or change in datasetHow to find Cross Correlation of two series over time containing periodic trends?
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Should we denoise a time series before calculating correlation?
The Next CEO of Stack OverflowLong time scale correlationCorrelation between an event and a time seriesUsing mutual information to estimate correlation between a continuous variable and a categorical variableTime Series (White Noise)Measuring correlation of two time seriesFinding time series mean variance skewness of stationary time seriesWhy do time series need to be stationary for computing cross-correlation?Is cross-correlation valid for time-series such as these (with trends)?Contrasting effects on correlation between two variables with increase or change in datasetHow to find Cross Correlation of two series over time containing periodic trends?
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While I understand the answer may depends on, say from method of denoising, to the information contained in the dataset. May I ask in general, does it make sense to denoise a time series before calculating correlation (say, Pearson Correlation).
For example, if I apply a low-pass filter to log changes of stock price of GS and JPM, and then calculate the Pearson Correlation between them. Would it be correct if I claim that I am evaluating the 'relationship' of the trend of these 2 stocks?
correlation time-series
$endgroup$
add a comment |
$begingroup$
While I understand the answer may depends on, say from method of denoising, to the information contained in the dataset. May I ask in general, does it make sense to denoise a time series before calculating correlation (say, Pearson Correlation).
For example, if I apply a low-pass filter to log changes of stock price of GS and JPM, and then calculate the Pearson Correlation between them. Would it be correct if I claim that I am evaluating the 'relationship' of the trend of these 2 stocks?
correlation time-series
$endgroup$
add a comment |
$begingroup$
While I understand the answer may depends on, say from method of denoising, to the information contained in the dataset. May I ask in general, does it make sense to denoise a time series before calculating correlation (say, Pearson Correlation).
For example, if I apply a low-pass filter to log changes of stock price of GS and JPM, and then calculate the Pearson Correlation between them. Would it be correct if I claim that I am evaluating the 'relationship' of the trend of these 2 stocks?
correlation time-series
$endgroup$
While I understand the answer may depends on, say from method of denoising, to the information contained in the dataset. May I ask in general, does it make sense to denoise a time series before calculating correlation (say, Pearson Correlation).
For example, if I apply a low-pass filter to log changes of stock price of GS and JPM, and then calculate the Pearson Correlation between them. Would it be correct if I claim that I am evaluating the 'relationship' of the trend of these 2 stocks?
correlation time-series
correlation time-series
asked Mar 20 at 10:56
roninronin
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