Arbeitspapier
Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models
We investigate covariance matrix estimation in vast-dimensional spaces of 1,500 up to 2,000 stocks using fundamental factor models (FFMs). FFMs are the typical benchmark in the asset management industry and depart from the usual statistical factor models and the factor models with observed factors used in the statistical and finance literature. Little is known 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 possible using high-dimensional shrinkage techniques. The gains, however, are not realized using standard plug-in shrinkage parameters from the literature, but require sample dependent tuning.
- Sprache
-
Englisch
- Erschienen in
-
Series: Tinbergen Institute Discussion Paper ; No. TI 2018-099/III
- Klassifikation
-
Wirtschaft
Portfolio Choice; Investment Decisions
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
Financial Econometrics
Large Data Sets: Modeling and Analysis
- Thema
-
Portfolio allocation
high dimensions
linear and non-linear shrinkage
factor models
- Ereignis
-
Geistige Schöpfung
- (wer)
-
van Vlodrop, Andries C.
Lucas, André
- Ereignis
-
Veröffentlichung
- (wer)
-
Tinbergen Institute
- (wo)
-
Amsterdam and Rotterdam
- (wann)
-
2018
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- van Vlodrop, Andries C.
- Lucas, André
- Tinbergen Institute
Entstanden
- 2018
Ähnliche Objekte (12)
Weak versus strong dominance of shrinkage estimators
The Fundamental Equation in Tourism Finance
Relating Stochastic Volatility Estimation Methods
Instrumental Variable Estimation for Duration Data
Gauss on least-squares and maximum-likelihood estimation
Nearly Unbiased Estimation in Dynamic Panel Data Models with Exogenous Variables
Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation
Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility
On Conditional Density Estimation
Fractional Cointegration Rank Estimation
EmmPack 1.01: C/C++ Code for Use with Ox for Estimation of Univariate Stochastic Volatility Models with the Efficient Method of Moments
Maximum Likelihood Estimation of Search Costs
Weak versus strong dominance of shrinkage estimators
The Fundamental Equation in Tourism Finance
Relating Stochastic Volatility Estimation Methods
Instrumental Variable Estimation for Duration Data
Gauss on least-squares and maximum-likelihood estimation
Nearly Unbiased Estimation in Dynamic Panel Data Models with Exogenous Variables
Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation
Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility
On Conditional Density Estimation
Fractional Cointegration Rank Estimation
EmmPack 1.01: C/C++ Code for Use with Ox for Estimation of Univariate Stochastic Volatility Models with the Efficient Method of Moments
Maximum Likelihood Estimation of Search Costs
Weak versus strong dominance of shrinkage estimators
The Fundamental Equation in Tourism Finance
Relating Stochastic Volatility Estimation Methods
Instrumental Variable Estimation for Duration Data
Gauss on least-squares and maximum-likelihood estimation
Nearly Unbiased Estimation in Dynamic Panel Data Models with Exogenous Variables
Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation
Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility
On Conditional Density Estimation
Fractional Cointegration Rank Estimation
EmmPack 1.01: C/C++ Code for Use with Ox for Estimation of Univariate Stochastic Volatility Models with the Efficient Method of Moments