Factor Models for Portfolio Selection in Large Dimensions

This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns.

Factor Models for Portfolio Selection in Large Dimensions - SSRN

It displays superior all-around performance on historical data against a variety of state-of-the-art competitors, including static factor models ...

Factor models for portfolio selection in large dimensions - Zora.uzh.ch

It displays superior all-around performance on historical data against a variety of state-of-the-art competitors, including static factor models, exogenous ...

Factor Models for Portfolio Selection in Large Dimensions

This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns. Existing factor models ...

[PDF] Factor Models for Portfolio Selection in Large Dimensions

This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns. Existing factor models ...

Factor Models for Portfolio Selection in Large Dimensions

Abstract. This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns. Existing factor ...

Factor Models for Portfolio Selection in Large Dimensions - a-z.lu

Abstract This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns.

Factor models for portfolio selection in large dimensions

Abstract. This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns. Existing factor ...

Factor Models For Portfolio Selection in Large Dimensions - Scribd

This paper examines the usefulness of factor models for estimating large-dimensional covariance matrices to be used for Markowitz portfolio selection.

Factor models for portfolio selection in large dimensions - Zora.uzh.ch

This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns. Existing factor ...

Large Portfolios' Risks and High-Dimensional Factor Models

This dissertation explores two important topics on high-dimensional factor models. We first consider the problem of estimating and assessing the risk of a large ...

High-Dimensional Factor Models and the Factor Zoo | NBER

Since the data set is 3-dimensional (characteristics of funds over time), characteristic factors are based on a tensor factor model (TFM) that ...

5 Factor models — MOSEK Portfolio Optimization Cookbook 1.6.0

The purpose of factor models is to impose a structure on financial variables and their covariance matrix by explaining them through a small number of common ...

ESTIMATION OF LARGE DIMENSIONAL CONDITIONAL FACTOR ...

(2018) use model selection techniques to identify characteristics portfolios with a. 17. Page 18. good explanatory power for returns. These papers do not deal ...

High-dimensional portfolio optimization based on tree-structured ...

Certain characteristics are known to predict cross-sectional expected stock returns and risk exposures. We propose a novel portfolio optimization procedure ...

Portfolio selection revisited - FSU Math

Beyond their theoretical underpinnings, factor models facilitate the problem of estimating a high-dimensional return covariance matrix.4. They ...

Portfolio Optimization Using Factor Models - MathWorks

Multifactor models are often used in risk modeling, portfolio management, and portfolio performance attribution. A multifactor model reduces the dimension of ...

Factor Models in Portfolio and Asset Pricing Theory - SpringerLink

We discuss the role of factor models in implementing portfolio selection, defining the nature of systematic risk, and estimating the premium for risk bearing.

Large-Dimensional Portfolio Selection with a High-Frequency ...

Large-Dimensional Portfolio Selection with a High-Frequency-Based Dynamic Factor Model · Simon Tranberg Bodilsen · Do you have a job opening that ...

High-Dimensional Portfolio Selection with Cardinality Constraints

The flexibility and the stability of incorporating factor signals for augmenting out-of-sample performances are also demonstrated. Our strategy balances the ...