Based On The Black-litterman Model With Liquidity Risk Measure Constraints Asset Allocation Model

In the theories of asset management, traditional Markowitz mean-variance model is the foundmental theory of the quantitive portfolio research. Thogh the approch is quite classical, its high sensitivity on inputs (return estimates) retricts its application of the investment activities. Espesially the forecasts of asset returns are absolutely judged by historical returns, ignoring the intestor's own subjective forecasts of the asset .The Black-Litterman Model (1990) yields consistent asset return forecasts as a weighted combination of market equilibrium returns and the intestor's own subjective forecasts of the asset ("views"). So the B-L Model revised returns then serve as a consistent input for mean-variance portfolio optimisation procedures. But as we know, there are two parts of the overall risk: one is pure risk resulting from moves in the mid-price, the other important part is liquidity risk arising from a trader not realizing the mid-price. While B-L Model just has focussed on the pure risk ignoring the liquidity risk. So, on the basic of B-L Model, we want to build a new reformed frame to add liquidity risk ristriction as an important component to mean-variance portfolio optimisation model. In the end we have tested the new model using the data of Chinese A shares market. The result demonstrates that the optimized portfolio is better than B-L model.