Quarterly Series and Handling Missing Values

The calculator supports calibration using quarterly time series and series with missing values. Below is an example compatible with our previous case study:

The calculator uses pairwise correlation calibration between asset classes, allowing it to handle a small number of missing values in the time series. However, keep the following in mind:

• The first value in a return series must be present.
• Ensure that empty rows at the bottom of the dataset are cleaned up to avoid "ghost rows."
• When calculating annualised returns, the first and last non-empty values in the series are used. For accurate calibration, it’s preferable to have the last value of the series available.