25 citations · 33 across the 7 of their papers we have counts for
8 papers
From Many Models, One: Macroeconomic Forecasting with Reservoir Ensembles
Giovanni Ballarin, Lyudmila Grigoryeva, Yui Ching Li
Model combination is a powerful approach for achieving superior performance compared to selecting a single model. We study both theoretically and empirically the effectiveness of e…
Multi-Horizon Echo State Network Prediction of Intraday Stock Returns
Giovanni Ballarin, Jacopo Capra, Petros Dellaportas
Stock return prediction is a problem that has received much attention in the finance literature. In recent years, sophisticated machine learning procedures have been shown to perfo…
Memory Capacity of Nonlinear Recurrent Networks: Is it Informative?
Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega
The total memory capacity (MC) of linear recurrent neural networks (RNNs) has been proven to be equal to the rank of the corresponding Kalman controllability matrix, and it is almo…
Impulse Response Analysis of Structural Nonlinear Time Series Models
Giovanni Ballarin
This paper proposes a semiparametric sieve approach to estimate impulse response functions of nonlinear time series within a general class of structural autoregressive models. We p…
Memory of recurrent networks: Do we compute it right?
Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega
Numerical evaluations of the memory capacity (MC) of recurrent neural networks reported in the literature often contradict well-established theoretical bounds. In this paper, we st…
Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data
Giovanni Ballarin, Petros Dellaportas, Lyudmila Grigoryeva +3
Macroeconomic forecasting has recently started embracing techniques that can deal with large-scale datasets and series with unequal release periods. MIxed-DAta Sampling (MIDAS) and…
Ridge Regularized Estimation of VAR Models for Inference
Giovanni Ballarin
Ridge regression is a popular method for dense least squares regularization. In this work, ridge regression is studied in the context of VAR model estimation and inference. The imp…
On the Limiting Distribution of Sieve VAR() Estimators in Small Samples
Giovanni Ballarin
When a finite order vector autoregressive model is fitted to VAR() data the asymptotic distribution of statistics obtained via smooth functions of least-squares estimates r…