Knowledge-based Black-Litterman Asset Allocation with High-Dimensional Realized Covariance

CFE-CMStatistics 2024, EFMA 2023

54 Pages Posted: 15 Apr 2025 Last revised: 29 Mar 2025

See all articles by Xinyu Huang

Xinyu Huang

University of Bath - School of Management

David Newton

University of Bath - School of Management

Emmanouil Platanakis

University of Bath - School of Management

Xiaoxia Ye

University of Nottingham

Date Written: March 29, 2025

Abstract

This paper introduces a knowledge-based Black-Litterman (KBL) asset allocation framework. Experts’ views are generated using a distributed modeling framework fusing several types of uncertain and incomplete knowledge from experts to derive optimal decisions rationally. We use Shannon’s information measure to develop aggregation rules integrating multiple experts’ predictions while calibrating their reliability. The fusion parameters are adaptively learned by minimizing the decision error of the induced combination, which we formulate as a constrained optimization problem. We further enhance covariance estimation by modeling realized covariances from high-frequency data using the Conditional Threshold Autoregressive Wishart (CTAW) model, providing the first analytical framework for addressing its high-dimensional estimation challenges. We derive explicit gradient expressions and solve the optimization using the method of moving asymptotes. Empirical analysis on a U.S. equity universe shows that the proposed approach achieves superior risk-adjusted returns, outperforming six established allocation strategies with statistically significant improvements over the   1/N benchmark in the presence of transaction costs. In addition, we show that incorporating our parameter estimation methods enhances the performance of existing benchmark strategies. Results remain robust to sensitivity tests.

Keywords: Risk Management, Investment Analysis, Black-Litterman, Parameter Uncertainty, Knowledge Fusion

Suggested Citation

Huang, Xinyu and Newton, David and Platanakis, Emmanouil and Ye, Xiaoxia, Knowledge-based Black-Litterman Asset Allocation with High-Dimensional Realized Covariance (March 29, 2025). CFE-CMStatistics 2024, EFMA 2023, Available at SSRN: https://ssrn.com/abstract=5185471 or http://dx.doi.org/10.2139/ssrn.5185471

Xinyu Huang

University of Bath - School of Management ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

David Newton

University of Bath - School of Management ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

Emmanouil Platanakis (Contact Author)

University of Bath - School of Management ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

Xiaoxia Ye

University of Nottingham ( email )

University Park
Nottingham, NG8 1BB
United Kingdom

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