Fabian Krüger

Biographic Data

ID6449572
NAMEFabian Krüger
GIVEN NAMESFabian
FAMILY NAMEKrüger
SIGNATUREKRÜGER F
AFFILIATIONSKarlsruhe Institute of Technology
ORCID0000-0002-5112-9037
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS0
AUTHOR COUNT6
EDITOR COUNT0
FIRST PUBLICATION YEAR2016
LATEST PUBLICATION YEAR2023
H-INDEX0

  • Predicting the Global Minimum Variance Portfolio

    Laura Reh, Fabian Krüger et al.ARTICLEJournal of Business and Economic…2023

    We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP) for the conditional covariance matrix of asset returns. The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss function from which we can infer the GMVP weights without imposing any distributional assumptions …

  • Direction Augmentation in the Evaluation of Armed Conflict Predictions

    Johannes Bracher, Lotta Rüter et al.ARTICLEInternational Interactions2023References: 5

    In many forecasting settings, there is a specific interest in predicting the sign of an outcome variable correctly in addition to its magnitude. For instance, when forecasting armed conflicts, positive and negative log-changes in monthly fatalities represent escalation and de-escalation, respectively, and have very different implications. In the ViEWS forecasting challenge, a prediction competition on state-based violence, a novel evaluation scor…

  • Forecast uncertainty, disagreement, and the linear pool

    Open AccessMalte Knüppel, Fabian KrügerARTICLEJournal of Applied Econometrics2022

    The linear pool is the most popular method for combining density forecasts. We analyze its implications concerning forecast uncertainty, using a new framework that focuses on the means and variances of the individual and combined forecasts. Our results show that, if the variance predictions of the individual forecasts are unbiased, the well‐known “disagreement” component of the linear pool exacerbates the upward bias of its variance prediction. T…

  • Generic Conditions for Forecast Dominance

    Fabian Krüger, Johanna F ZiegelARTICLEJournal of Business and Economic…2021

    Recent studies have analyzed whether one forecast method dominates another under a class of consistent scoring functions. While the existing literature focuses on empirical tests of forecast dominance, little is known about the theoretical conditions under which one forecast dominates another. To address this question, we derive a new characterization of dominance among forecasts of the mean functional. We present various scenarios under which do…

  • Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts

    Fabian Krüger, Todd E Clark et al.ARTICLEJournal of Business and Economic…2017

    This article shows entropic tilting to be a flexible and powerful tool for combining medium-term forecasts from BVARs with short-term forecasts from other sources (nowcasts from either surveys or other models). Tilting systematically improves the accuracy of both point and density forecasts, and tilting the BVAR forecasts based on nowcast means and variances yields slightly greater gains in density accuracy than does just tilting based on the now…

  • Forecasting Conditional Probabilities of Binary Outcomes under Misspecification

    Open AccessGraham Elliott, Dalia Ghanem et al.ARTICLEThe Review of Economics and…2016

    We consider constructing probability forecasts from a parametric binary choice model under a large family of loss functions (“scoring rules”). Scoring rules are weighted averages over the utilities that heterogeneous decision makers derive from a publicly announced forecast (Schervish, 1989). Using analytical and numerical examples, we illustrate howdifferent scoring rules yield asymptotically identical results if the model is correctly specified…