Nov 06 2020 20 mins 8
It can be difficult to estimate time-evolving parameters in financial models due to noise in the financial signal and ambiguity in defining the model itself. How can we address these challenges and make more descriptive/predictive parameter estimates? Join Tom, Tony and Julia as they discuss how Kalman Filters can be used to estimate parameters that are less sensitive to noise and at lower risk of overfitting than those calculated with traditional statistical techniques.
