Sunday, January 24, 2021

Machine Learning Advances for Time Series Forecasting

Check out this fine survey by Masini, Medeiros and Mendes,

For me the coolest thing is new insights into optimal regularization and subset averaging for density forecast mixtures. Amazingly, and very much related to the survey (but not widely recognized, including in the survey), optimally-regularized regression-based combinations and subset-average combinations are VERY closely connected. You can see the connection clearly in both of the papers below, in the first for point forecasts, and in the second for density forecasts. Effectively, the optimal regularization *IS​* subset averaging!

Diebold, F.X. and Shin, M. (2019), "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," International Journal of Forecasting, 35, 1679-1691.

Diebold, F.X., Shin, M. and Zhang, B. (2021), “On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates,” arXiv:2012.11649.

No comments:

Post a Comment

Note: Only a member of this blog may post a comment.