I am working on building a linear regression model and I convert the close prices and volume to natural log. However, volume in few instances returned 'inf' value due to huge volume, hence throws error. Is it better to replace 'inf' with max volume or how would I deal with such scenarios?
Hello Manoj,
Encountering 'inf' (infinity) values in your data after taking the natural logarithm typically indicates that some of the original values were zero. The natural logarithm of zero is undefined, hence the 'inf' value. In the context of volume, a zero value is not meaningful, and it's more likely that the volume was extremely low rather than truly zero.
Check if there are any issues with the data you are working with. If the volume data is 0 due to issues with the data, then you can replace the 0 values of volume with the mean, median, or rolling mean of volumes.
However, if you feel like it's completely understandable that some of the volume data can have zeros and there is no issue with the data, then you can try the following to solve this.
- Add a small constant to the volume data. This helps avoid taking the logarithm of zero.
- As proposed by you, you can replace 'inf' with the maximum volume in your dataset.
- If there are extreme volume values that are causing issues, you might consider excluding those data points from your analysis or applying some form of imputation. For imputation, you could use statistical methods like median imputation or replace extreme values with the mean, depending on the distribution of your data.
- Instead of using the natural logarithm, you can try other transformations that handle zero values differently. For example, you could use the square root or cube root transformation.
I hope this helps!