Abstract: Industrial allocation is one of the indispensable steps in portfolio investment process. The traditional allocation models of industry ignores the overall correlation of the industry network. Based on the Black-Litterman (BL) model (the predictive values of machine learning and time series models are subjective points of view) in industrial allocation together with complex network theory, we propose a graphical presentation of the BL model, prove the mathematical relation between the optimal portfolio of the BL model and the graphical presentation and do the corresponding empirical analysis. Then we propose an industry allocation model, named BL+Network model. The model perfects the application framework of complex network method in “top-down” portfolio management. Empirical comparison with some traditional models finds that BL+Network model improves evidently Sharpe ratio and gain-loss ratio, industries whose eigenvector centrality degree are in near of the median sequence number should be allocated more, but fewer industries is not always better. This research provides a new perspective for asset allocation study, and extends the cross application of BL model and complex network method to portfolio management.

Key words: complex network, BL+Network model, eigenvector centrality degree