Advances in nowcasting economic activity: Secular trends, large shocks and new data
A key question for households, firms, and policy makers is: how is the economy doing now?
We develop a Bayesian dynamic factor model and compute daily estimates of US GDP …
We develop a Bayesian dynamic factor model and compute daily estimates of US GDP …
[HTML][HTML] Real-time inflation forecasting using non-linear dimension reduction techniques
In this paper, we assess whether using non-linear dimension reduction techniques pays off
for forecasting inflation in real-time. Several recent methods from the machine learning …
for forecasting inflation in real-time. Several recent methods from the machine learning …
Large (and Deep) Factor Models
We open up the black box behind Deep Learning for portfolio optimization and prove that a
sufficiently wide and arbitrarily deep neural network (DNN) trained to maximize the Sharpe …
sufficiently wide and arbitrarily deep neural network (DNN) trained to maximize the Sharpe …
A neural phillips curve and a deep output gap
P Goulet Coulombe - Available at SSRN 4018079, 2022 - papers.ssrn.com
Many problems plague the estimation of Phillips curves. Among them is the hurdle that the
two key components, inflation expectations and the output gap, are both unobserved …
two key components, inflation expectations and the output gap, are both unobserved …
Tracking economic activity with alternative high-frequency data
F Eckert, P Kronenberg, H Mikosch… - Available at SSRN …, 2022 - papers.ssrn.com
Most macroeconomic series failed to capture the sharp fluctuations during the COVID-19
pandemic. Also, it proved difficult to extract business cycle information from alternative high …
pandemic. Also, it proved difficult to extract business cycle information from alternative high …
[HTML][HTML] Factor-Augmented Autoregressive Neural Network to forecast Nox in the city of Madrid
G Fernández-Avilés, R Mattera, G Scepi - Socio-Economic Planning …, 2024 - Elsevier
Air pollution poses a significant threat to public health and the environment in urban areas
worldwide. In the context of urban air quality, nitrogen oxides (NOx), comprising nitrogen …
worldwide. In the context of urban air quality, nitrogen oxides (NOx), comprising nitrogen …
From reactive to proactive volatility modeling with hemisphere neural networks
P Goulet Coulombe, M Frenette, K Klieber - Available at SSRN, 2023 - papers.ssrn.com
We reinvigorate maximum likelihood estimation (MLE) for macroeconomic density
forecasting through a novel neural network architecture with dedicated mean and variance …
forecasting through a novel neural network architecture with dedicated mean and variance …
A neural Phillips curve and a deep output gap
PG Coulombe - arXiv preprint arXiv:2202.04146, 2022 - arxiv.org
Many problems plague the estimation of Phillips curves. Among them is the hurdle that the
two key components, inflation expectations and the output gap, are both unobserved …
two key components, inflation expectations and the output gap, are both unobserved …
From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks
PG Coulombe, M Frenette, K Klieber - arXiv preprint arXiv:2311.16333, 2023 - arxiv.org
We reinvigorate maximum likelihood estimation (MLE) for macroeconomic density
forecasting through a novel neural network architecture with dedicated mean and variance …
forecasting through a novel neural network architecture with dedicated mean and variance …
On statistical arbitrage under a conditional factor model of equity returns
We consider a conditional factor model for a multivariate portfolio of United States equities in
the context of analysing a statistical arbitrage trading strategy. A state space framework …
the context of analysing a statistical arbitrage trading strategy. A state space framework …