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Fabian Krüger

Dados Biográficos

ID6449572
NOMEFabian Krüger
PRENOMESFabian
SOBRENOMEKrüger
ASSINATURAKRÜGER F
AFILIAÇÕESKarlsruhe Institute of Technology
ORCID0000-0002-5112-9037
VERIFICADOSim
TOTAL DE OBRAS6
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR6
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2016
ANO MAIS RECENTE DE PUBLICAÇÃO2023
ÍNDICE H0
  • Predicting the Global Minimum Variance Portfolio

    Laura Reh, Fabian Krüger et al.•ARTICLE•Journal 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.•ARTICLE•International Interactions•2023•Referências: 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 Access•Malte Knüppel, Fabian Krüger•ARTICLE•Journal of Applied Econometrics•2022

    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 Ziegel•ARTICLE•Journal 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.•ARTICLE•Journal 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 Access•Graham Elliott, Dalia Ghanem et al.•ARTICLE•The 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…

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  • Forecasting Conditional Probabilities of Binary Outcomes under Misspecification

    Open Access•Graham Elliott, Dalia Ghanem et al.•ARTICLE•The 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…

  • Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts

    Fabian Krüger, Todd E Clark et al.•ARTICLE•Journal 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…

  • Generic Conditions for Forecast Dominance

    Fabian Krüger, Johanna F Ziegel•ARTICLE•Journal 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…

  • Forecast uncertainty, disagreement, and the linear pool

    Open Access•Malte Knüppel, Fabian Krüger•ARTICLE•Journal of Applied Econometrics•2022

    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…

  • Predicting the Global Minimum Variance Portfolio

    Laura Reh, Fabian Krüger et al.•ARTICLE•Journal 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.•ARTICLE•International Interactions•2023•Referências: 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…

Econometrics (6 obras) · Mathematics (6 obras) · Economics (5 obras) · Statistics (5 obras) · Forecasting Techniques and Applications (4 obras) · Computer Science (3 obras) · Financial Risk and Volatility Modeling (3 obras) · Monetary Policy and Economic Impact (3 obras) · Market Dynamics and Volatility (2 obras) · Atmospheric and Environmental Gas Dynamics (1 obra)

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