DLM is basically the acronym for Dynamic Linear Models.
Kalman Filter is the most basic form of a DLM.
DLMs have been used extensively in many different fields.
Can we use Dynamic Linear Models in building trading models?
Of course we can. Dynamic Linear Models can help you predict price.
The trick lies in using a discounting factor that helps information decays.
Information in financial markets decay. We don't know the rate of decay.
We can use a number of discounting factors between 0 and 1.
After that we can use Bayesian Statistics to check which model is the best.
I have written a blog post: Dynamic Linear Models For Traders.
You can read it. I have explained everything in it.
DLMs can be easily build using R as well as Python.
