Kalman Filters are used in signal processing to estimate the underlying state of a process. They are incredibly useful for finance, as we are constantly taking noisy estimates of key quantities and trading indicators. This notebook introduces Kalman Filters and shows some examples of application to quantitative finance. You can view the corresponding notebooks from this lecture here: [ Ссылка ].
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