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06/08/2023
Maximally Machine-Learnable Portfolios
When it comes to stock returns, any form of predictability can bolster r...
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06/21/2022
Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models
We use "glide charts" (plots of sequences of root mean squared forecast ...
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03/08/2022
When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume
Rapidly diminishing Arctic summer sea ice is a strong signal of the pace...
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02/08/2022
A Neural Phillips Curve and a Deep Output Gap
Many problems plague the estimation of Phillips curves. Among them is th...
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03/19/2021
On Spurious Causality, CO2, and Global Temperature
Stips, Macias, Coughlan, Garcia-Gorriz, and Liang (2016, Nature Scientif...
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03/02/2021
Slow-Growing Trees
Random Forest's performance can be matched by a single slow-growing tree...
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03/01/2021
Can Machine Learning Catch the COVID-19 Recession?
Based on evidence gathered from a newly built large macroeconomic data s...
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09/01/2020
Time-Varying Parameters as Ridge Regressions
Time-varying parameters (TVPs) models are frequently used in economics t...
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08/28/2020
How is Machine Learning Useful for Macroeconomic Forecasting?
We move beyond "Is Machine Learning Useful for Macroeconomic Forecasting...
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08/17/2020
To Bag is to Prune
It is notoriously hard to build a bad Random Forest (RF). Concurrently, ...
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08/04/2020
Macroeconomic Data Transformations Matter
From a purely predictive standpoint, rotating the predictors' matrix in ...
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06/23/2020
The Macroeconomy as a Random Forest
Over the last decades, an impressive amount of non-linearities have been...
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05/05/2020
Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis
Arctic sea ice extent (SIE) in September 2019 ranked second-to-lowest in...
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03/31/2020
