Preface: My knowledge is quite introductory to Bayesian analysis and statistical modeling so my problem might require re-framing and I could be trying to fit a round peg through a square hole.

I am trying to implement a single factor model where the factor parameter is time-varying and attempts to capture clustering. The stochastic vol example was somewhat helpful but this particular model has the parameter `beta(i)_p,t`

and conditional posterior distributions depending on `beta(i)_p,t-1`

and `beta(i-1)_p,t+1`

where is `i`

is the iteration step. Original Paper

The attached image provides a little more detail for the pricing model and priors. Any advice on implementing in PyMC3 and possible hyper-parameter distributions would be appreciated.