Excluding mean in variance calculation

In summary, the author of a finance book suggests excluding the mean when calculating the variance of returns, using a formula of (1/N) * sum of (x_i)^2. This method is not commonly used and may yield problematic results in finance. The second moment, or variance, may not have a useful application without considering the mean of the values.
  • #1
Polymath89
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I'm reading a finance book in which the author proposes to exclude the mean when calculating the variance of returns, because he thinks it's difficult to distinguish the drift of the price from the variance of that time series. So he basically calculates the sample variance like this [itex]\frac{1}{N}\sum_{i=1}^n (x_i)^2[/itex]. I haven't seen anybody calculate variance like this before, so my question is whether this is a common way to calculate it or whether this could yield problematic results?
 
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  • #2
This is the second moment. I doubt that it has a useful application in finance without looking at the mean of the values, but I don't know.
 

1. What is the purpose of excluding the mean in variance calculation?

The purpose of excluding the mean in variance calculation is to avoid bias in the estimate of variance. When the mean is included in the calculation, it can affect the value of the variance and make it appear larger than it actually is.

2. How is the mean excluded in variance calculation?

The mean can be excluded in variance calculation by using the formula for sample variance, which divides by n-1 instead of n. This is known as the Bessel's correction and it adjusts the calculation to account for the fact that we are working with a sample rather than the entire population.

3. Does excluding the mean change the interpretation of the variance?

No, excluding the mean does not change the interpretation of the variance. It is still a measure of how spread out the data points are from the average. However, the value of the variance may be different when the mean is excluded.

4. Is excluding the mean always necessary in variance calculation?

No, excluding the mean is not always necessary in variance calculation. It is only necessary if the goal is to estimate the variance of the entire population based on a sample. If the goal is to just describe the spread of data within a sample, the mean can be included in the calculation.

5. Are there any situations where excluding the mean may not be appropriate?

Yes, there are some situations where excluding the mean may not be appropriate. For example, if the data set contains extreme outliers, excluding the mean may not accurately represent the spread of the majority of the data points. In this case, alternative measures of spread such as the interquartile range may be more appropriate.

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