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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?










share|cite|improve this question









$endgroup$
















    0












    $begingroup$


    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?










    share|cite|improve this question









    $endgroup$














      0












      0








      0





      $begingroup$


      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?










      share|cite|improve this question









      $endgroup$




      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






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked Mar 20 at 10:56









      roninronin

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