Details

Autor(en) / Beteiligte

• Boot, Tom
• Pick, Andreas

Titel

Optimal Forecasts from Markov Switching Models

Ist Teil von

• Journal of business & economic statistics, 2018-10, Vol.36 (4), p.628-642

Ort / Verlag

Alexandria: Taylor & Francis

Erscheinungsjahr

2018

Quelle

EBSCOhost Business Source Ultimate

Beschreibungen/Notizen

• We derive forecasts for Markov switching models that are optimal in the mean square forecast error (MSFE) sense by means of weighting observations. We provide analytic expressions of the weights conditional on the Markov states and conditional on state probabilities. This allows us to study the effect of uncertainty around states on forecasts. It emerges that, even in large samples, forecasting performance increases substantially when the construction of optimal weights takes uncertainty around states into account. Performance of the optimal weights is shown through simulations and an application to U.S. GNP, where using optimal weights leads to significant reductions in MSFE. Supplementary materials for this article are available online.