Forecasting Odds Movements in Horse Racing

Student thesis: Master thesis (including HD thesis)

  • Martin Georges Raymond Maillard
4. term, Mathematics-Economics, Master (Master Programme)
In this thesis we consider the odds movements
in horse racing on a betting exchange. Due
to the odds structure on a betting exchange
we choose to model the odds movements as
the tick increments rather than the change
in odds. This leads us to construct the
odds trajectory model. Since the parameters
in the odds trajectory model are not timevarying
we explore an alternative state-space
model, namely the dynamic Skellam model.
The dynamic Skellam model is a nonlinear
non-Gaussian model and this presents some
challenges in filtering and smoothing the
data. As a smoothing method we maximize
the likelihood function where the evaluation
of the likelihood function is done by using
importance sampling method. The filtering
of the data also utilizes importance sampling
more specifically we use a particle filter,
namely the bootstrap filter. Lastly, we
forecast the odds movements by combining
the estimated filtering values with the odds
trajectory model
Publication date2 Jun 2020
Number of pages63
ID: 333457988