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Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models
van Vlodrop, Andries - 2019
We investigate covariance matrix estimation in vast-dimensional spaces of 1,500 up to 2,000 stocks using fundamental … about estimation risk in FFMs in high dimensions. We investigate whether recent linear and non-linear shrinkage methods help … to reduce the estimation risk in the asset return covariance matrix. Our findings indicate that modest improvements are …
Persistent link: https://www.econbiz.de/10012896346
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Density and Risk Prediction with Non-Gaussian COMFORT Models
Paolella, Marc S.; Polak, Pawel - 2022
generalized hyperbolic innovations. The novelty of the model is that parameter estimation is conducted by joint maximum likelihood …
Persistent link: https://www.econbiz.de/10014236254
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Efficient Factor Selection : Explaining Risk and Mean Returns Jointly
Balvers, Ronald J. - 2018
An asset pricing model is customarily evaluated by how well it explains means of returns. But how well the model explains fluctuations of returns is similarly important though often overlooked in the literature. We derive “efficient” factors that combine both objectives and turn out to...
Persistent link: https://www.econbiz.de/10012922680
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Dimensions of macroeconomic uncertainty : a common factor analysis
Henzel, Steffen; Rengel, Malte - 2014
Uncertainty about the future course of the economy is a possible driver of aggregate fluctuations. To identify the different dimensions of uncertainty in the macroeconomy we construct a large dataset covering all types of economic uncertainty. We then identify two fundamental factors which...
Persistent link: https://www.econbiz.de/10010412767
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Dimensions of macroeconomic uncertainty : a common factor analysis
Henzel, Steffen; Rengel, Malte - 2013
In the current literature uncertainty about the future course of the economy is identified as a possible driver of business cycle fluctuations. In fact, uncertainty surrounds the movements of all economic variables which gives rise to a monitoring problem. We identify the different dimensions of...
Persistent link: https://www.econbiz.de/10010188870
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Proxy VAR models in a data-rich environment
Bruns, Martin - 2019
financial variables changes the model dynamics and delivers price responses which are more in line with economic theory. A …
Persistent link: https://www.econbiz.de/10012125244
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Measurement of Common Risk Factors : A Panel Quantile Regression Model for Returns
Cech, Frantisek - 2017
This paper investigates how to measure common market risk factors using newly proposed Panel Quantile Regression Model for Returns. By exploring the fact that volatility crosses all quantiles of the return distribution and using penalized fixed effects estimator we are able to control for...
Persistent link: https://www.econbiz.de/10012948828
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Nichtparametrische Inferenz für Copulas : quantitative Risikoanalysen für den deutschen Finanzmarkt
Dobrić, Jadran - 2008
Persistent link: https://www.econbiz.de/10003751715
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Comments on: Nonparametric tail risk, stock returns and the macroeconomy
Camponovo, Lorenzo; Scaillet, Olivier; Trojani, Fabio - 2016
Persistent link: https://www.econbiz.de/10011518800
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Multivariate crash risk
Chabi-Yo, Fousseni; Huggenberger, Markus; Weigert, Florian - 2021 - This version: May 21, 2021
This paper investigates whether multivariate crash risk (MCRASH), defined as exposure to extreme realizations of multiple systematic factors, is priced in the cross-section of expected stock returns. We derive an extended linear model with a positive premium for MCRASH and we empirically confirm...
Persistent link: https://www.econbiz.de/10012585546