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Thread: How to minimize volatility in dataset?

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    Question How to minimize volatility in dataset?




    Hi guys,

    We are currently struggling with a bit of an issue with regards to multiple regression.
    It concerns how to deal with substantial volatility in a dataset, which may affect least squares regression.

    The exact question goes like this:
    "The company has noticed that the dataset contains reasonably substantial volatility that may affect least squares regression. Explain what tools you would use to provide a more robust form of regression".

    My best suggestions to minimize volatility would be to:
    1) Take the square-root of each observation value
    2) Increase sample size

    However, I'm honestly not sure if this is in alignment with the question and/or whether or not it would contribute to create a more "robust" form of regression?

    Any advice is highly appreciated!

  2. #2
    Fortran must die
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    Re: How to minimize volatility in dataset?

    Variation in a data set is desirable I always thought. Certainly concerns are constantly raised that there is too little variation which can influence statistical tests. I have never heard that too much variation is an issue.
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

  3. #3
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    Re: How to minimize volatility in dataset?


    What is your definition of volatility?

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