Jack Fosten

King’s College London - King's Business School

150 Stamford Street

London, SE1 9NH

United Kingdom

SCHOLARLY PAPERS

5

DOWNLOADS

870

SSRN CITATIONS

3

CROSSREF CITATIONS

3

Scholarly Papers (5)

1.

Out-of-Sample Tests for Conditional Quantile Coverage - An Application to Growth-at-Risk

Journal of Econometrics, Forthcoming
Number of pages: 42 Posted: 31 Aug 2020 Last Revised: 12 Jul 2023
University of Surrey - School of Economics, King’s College London - King's Business School and Goethe University Frankfurt
Downloads 394 (142,036)
Citation 4

Abstract:

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Interval Prediction, Quantile Regression, Multiple Hypothesis Testing, Weak Moment Inequalities, Wild Bootstrap, Growth-at-Risk.

2.

Predictive Ability Tests with Possibly Overlapping Models

Number of pages: 42 Posted: 06 Mar 2023 Last Revised: 20 Feb 2024
University of Surrey - School of Economics, King’s College London - King's Business School and Goethe University Frankfurt
Downloads 189 (298,008)
Citation 1

Abstract:

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degeneracy, uniform inference, block bootstrap, out-of-sample evaluation, excess bond returns

3.

Panel Data Nowcasting

Number of pages: 45 Posted: 15 Aug 2019 Last Revised: 23 Sep 2019
Jack Fosten and Ryan Greenaway-McGrevy
King’s College London - King's Business School and University of Auckland Business School
Downloads 106 (473,720)
Citation 3

Abstract:

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Panel Data, Nowcasting, Model Selection, Model Averaging, State-level GDP

4.

Testing Nowcast Monotonicity with Estimated Factors

Number of pages: 32 Posted: 31 Jul 2016 Last Revised: 30 Mar 2018
Jack Fosten and Daniel Gutknecht
King’s College London - King's Business School and Goethe University Frankfurt
Downloads 104 (480,407)
Citation 1

Abstract:

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Nowcasting, Factor Models, Moment Inequalities, Bootstrap

5.

Model Confidence Sets for Nowcast Procedures

Number of pages: 27 Posted: 25 Oct 2018
Jack Fosten and Daniel Gutknecht
King’s College London - King's Business School and Goethe University Frankfurt
Downloads 77 (579,987)

Abstract:

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Nowcasting, Multiple Model Comparison, Model Confidence Set, Bootstrap