Machine learning advances for time series forecasting
RP Masini, MC Medeiros… - Journal of economic …, 2023 - Wiley Online Library
In this paper, we survey the most recent advances in supervised machine learning (ML) and
high‐dimensional models for time‐series forecasting. We consider both linear and nonlinear …
high‐dimensional models for time‐series forecasting. We consider both linear and nonlinear …
[PDF][PDF] Can the term spread predict output growth and recessions? A survey of the literature
DC Wheelock, ME Wohar - Federal Reserve Bank of St. Louis …, 2009 - files.stlouisfed.org
This article surveys recent research on the usefulness of the term spread (ie, the difference
between the yields on long-term and short-term Treasury securities) for predicting changes …
between the yields on long-term and short-term Treasury securities) for predicting changes …
Implications of COVID-19 pandemic on the global trade networks
CT Vidya, KP Prabheesh - Research on Pandemics, 2021 - taylorfrancis.com
This article measures the trade interconnectedness among countries before and after the
COVID-19 outbreak, and forecasts the future direction of trade. Using Trade Network …
COVID-19 outbreak, and forecasts the future direction of trade. Using Trade Network …
Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster
The ongoing COVID-19 pandemic has caused global health impacts, and governments
have restricted movements to a certain extent. Such restrictions have led to disruptions in …
have restricted movements to a certain extent. Such restrictions have led to disruptions in …
25 years of time series forecasting
JG De Gooijer, RJ Hyndman - International journal of forecasting, 2006 - Elsevier
We review the past 25 years of research into time series forecasting. In this silver jubilee
issue, we naturally highlight results published in journals managed by the International …
issue, we naturally highlight results published in journals managed by the International …
Forecasting output and inflation: The role of asset prices
JH Stock, MW Watson - Journal of economic literature, 2003 - aeaweb.org
Are asset prices useful predictors of inflation and real output growth? After reviewing the
large literature on this topic, we undertake an empirical analysis of quarterly data for seven …
large literature on this topic, we undertake an empirical analysis of quarterly data for seven …
A neural network approach for credit risk evaluation
The Basel Committee on Banking Supervision proposes a capital adequacy framework that
allows banks to calculate capital requirement for their banking books using internal …
allows banks to calculate capital requirement for their banking books using internal …
A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market
Evidence exists that emerging market stock returns are influenced by a different set of factors
than those that influence the returns for stocks traded in developed countries. This study …
than those that influence the returns for stocks traded in developed countries. This study …
Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination
In this paper, we examine the forecast accuracy of linear autoregressive, smooth transition
autoregressive (STAR), and neural network (NN) time series models for 47 monthly …
autoregressive (STAR), and neural network (NN) time series models for 47 monthly …
Neural network forecasts of Canadian stock returns using accounting ratios
D Olson, C Mossman - International Journal of Forecasting, 2003 - Elsevier
This study compares neural network forecasts of one-year-ahead Canadian stock returns
with the forecasts obtained using ordinary least squares (OLS) and logistic regression (logit) …
with the forecasts obtained using ordinary least squares (OLS) and logistic regression (logit) …