A Research On The Application Of The Black-Litterman Model On Industry Asset Allocation

Asset allocation plays an important role in financial investment.Fund managers get higher return and less risk by building the portfolio.Industry allocation is the key to asset allocation.In developed countries,quantized methods of industry allocation had been widely used in practice.But in China,the mainstream method of industry allocation is still the fundamental analysis.We seldom focus on the quantitative method of industry allocation.Therefore,this paper wants to find a quantitative method for industry allocation.This paper initially proposes to use Black-Litterman(BL)model in industry assets allocation.BL model not only considers the investor's view but also considers the implied return of the market in asset allocation.And this model solves the shortcoming of Mean Variance model.MV model relies a lot on the history data to do asset allocation.In the past,the security analyst' view which was not easy to quantified was taken as the subjective vector in BL model.This paper initially uses ARFIMA-GARCH model to get subjective vector because of the long term memory and heteroscedasticity of time series.In the empirical part,this paper selects 11 industry indexes which are sorted by GICS.We use ARFIMA-GARCH model to forecast the yields data from July 2016 to December 2016.Then put the forecasting results into BL model to do industry allocation.The empirical result shows that the yields forecasted by ARFIMA-GARCH when put into BL model have a better allocation results compared to ARFIMA and GARCH.And BL model which consider the investor's view can get a more balance configuration ratio and higher sharp ratio compared with the mean variance model.Compared to the market weight portfolio,this model can get excess returns.Overall,BL model is effective in industry allocation.