Too Long; Didn't Read

I focus on methods to handle missing data in financial time series. Using some some example data I show that LOCF is usually a decent go-to method compared to dropping and imputation but has its faults - i.e. can create artificial undesirable jumps in data. However, alternatives like interpolation have their own problems especially in context of live prediction/forecasting.