7 citations · 30 across the 13 of their papers we have counts for
6 papers · 1 filter
Forecasting inflation using disaggregates and machine learning
Gilberto Boaretto, Marcelo C. Medeiros
This paper examines the effectiveness of several forecasting methods for predicting inflation, focusing on aggregating disaggregated forecasts - also known in the literature as the…
Modeling and Forecasting Intraday Market Returns: a Machine Learning Approach
Iuri H. Ferreira, Marcelo C. Medeiros
In this paper we examine the relation between market returns and volatility measures through machine learning methods in a high-frequency environment. We implement a minute-by-minu…
The Proper Use of Google Trends in Forecasting Models
Marcelo C. Medeiros, Henrique F. Pires
It is widely known that Google Trends have become one of the most popular free tools used by forecasters both in academics and in the private and public sectors. There are many pap…
Bridging factor and sparse models
Jianqing Fan, Ricardo Masini, Marcelo C. Medeiros
Factor and sparse models are two widely used methods to impose a low-dimensional structure in high-dimensions. However, they are seemingly mutually exclusive. We propose a lifting…
Machine Learning Advances for Time Series Forecasting
Ricardo P. Masini, Marcelo C. Medeiros, Eduardo F. Mendes
In this paper we survey the most recent advances in supervised machine learning and high-dimensional models for time series forecasting. We consider both linear and nonlinear alter…
Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction
Jianqing Fan, Ricardo P. Masini, Marcelo C. Medeiros
Optimal pricing, i.e., determining the price level that maximizes profit or revenue of a given product, is a vital task for the retail industry. To select such a quantity, one need…