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Testing for structural stability of factor augmented forecasting models

Journal of econometrics, 2014-09, Vol.182 (1), p.100-118

2014

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A survey of dynamic Nelson-Siegel models, diffusion indexes, and big data methods for predicting interest rates

Quantitative finance and economics, 2019-01, Vol.3 (1), p.22-45

2019

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Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods

International journal of forecasting, 2018-04, Vol.34 (2), p.339-354

2018

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New evidence of the marginal predictive content of small and large jumps in the cross-section

Econometrics, 2020-06, Vol.8 (2), p.1-52

2020

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Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction

Journal of econometrics, 2015-08, Vol.187 (2), p.606-621

2015

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Jackknife estimation of a cluster-sample IV regression model with many weak instruments

Journal of econometrics, 2023-08, Vol.235 (2), p.1747-1769

2023

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Forecasting volatility using double shrinkage methods

Journal of empirical finance, 2021-06, Vol.62, p.46-61

2021

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Further Evidence on the Usefulness of Real-Time Datasets for Economic Forecasting

Quantitative finance and economics, 2017-01, Vol.1 (1), p.2-25

2017

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Macroeconomic and financial mixed frequency factors in a big data environment

Journal of the Royal Statistical Society Series C: Applied Statistics, 2024-06, Vol.73 (3), p.682-714

2024

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Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

International journal of forecasting, 2019-04, Vol.35 (2), p.555-572

2019

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Methods for backcasting, nowcasting and forecasting using factor‐MIDAS: With an application to Korean GDP

Journal of forecasting, 2018-04, Vol.37 (3), p.281-302

2018

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Money and output viewed through a rolling window

Journal of monetary economics, 1998-06, Vol.41 (3), p.455-474

Swanson, Norman R.

1998

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Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data

2021

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Testing for jumps and jump intensity path dependence

Journal of econometrics, 2018-06, Vol.204 (2), p.248-267

2018

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A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks

The review of economics and statistics, 1997-11, Vol.79 (4), p.540-550

1997

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Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions

Journal of the American Statistical Association, 1997-03, Vol.92 (437), p.357-367

1997

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Evaluation of dynamic stochastic general equilibrium models based on distributional comparison of simulated and historical data

Journal of econometrics, 2007-02, Vol.136 (2), p.699-723

2007

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Predictive Inference for Integrated Volatility

Journal of the American Statistical Association, 2011-12, Vol.106 (496), p.1496-1512

2011

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Bootstrap conditional distribution tests in the presence of dynamic misspecification

Journal of econometrics, 2006-08, Vol.133 (2), p.779-806

2006

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Prediction and simulation using simple models characterized by nonstationarity and seasonality

International review of economics & finance, 2015-11, Vol.40, p.312-323

2015

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NONPARAMETRIC BOOTSTRAP PROCEDURES FOR PREDICTIVE INFERENCE BASED ON RECURSIVE ESTIMATION SCHEMES

International economic review (Philadelphia), 2007-02, Vol.48 (1), p.67-109

2007

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The real-time predictive content of money for output

Journal of monetary economics, 2001-08, Vol.48 (1), p.3-24

2001

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Forecasting economic and financial time-series with non-linear models

International journal of forecasting, 2004-04, Vol.20 (2), p.169-183

2004

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Information in the Revision Process of Real-Time Datasets

Journal of business & economic statistics, 2009-10, Vol.27 (4), p.455-467

2009

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An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors

International journal of forecasting, 2023-12

2023

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Testing for structural stability of factor augmented forecasting models

A survey of dynamic Nelson-Siegel models, diffusion indexes, and big data methods for predicting interest rates

Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods

New evidence of the marginal predictive content of small and large jumps in the cross-section

Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction

Jackknife estimation of a cluster-sample IV regression model with many weak instruments

Forecasting volatility using double shrinkage methods

Further Evidence on the Usefulness of Real-Time Datasets for Economic Forecasting

Macroeconomic and financial mixed frequency factors in a big data environment

Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

Methods for backcasting, nowcasting and forecasting using factor‐MIDAS: With an application to Korean GDP

Money and output viewed through a rolling window

Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data

Testing for jumps and jump intensity path dependence

A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks

Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions

Evaluation of dynamic stochastic general equilibrium models based on distributional comparison of simulated and historical data

Predictive Inference for Integrated Volatility

Bootstrap conditional distribution tests in the presence of dynamic misspecification

Prediction and simulation using simple models characterized by nonstationarity and seasonality

NONPARAMETRIC BOOTSTRAP PROCEDURES FOR PREDICTIVE INFERENCE BASED ON RECURSIVE ESTIMATION SCHEMES

The real-time predictive content of money for output

Forecasting economic and financial time-series with non-linear models

Information in the Revision Process of Real-Time Datasets

An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors

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