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A stock market is a typical complex network and it can be described by complex network. Recently more related researches have focused on modeling and analyzing of topological structure of complex stock network. For an investor, the best decision is to select the optimal portfolio in order to obtain the maximum income with the given risk level. In this paper, we propose a new optimal portfolio model with degree risk control based on Markowitz mean-variance model, which is different from the variance risk in traditional portfolio model. We regard the inverse of degree of each stock as its risk in complex stock network. We show the optimal portfolio of the new model is more reasonable than that of the old model. Meanwhile, we find the new model obtains the larger fluctuation of the optimal proportions. All stocks in Shanghai Stock Exchange Constituent Index, named SSE-180 usually, are selected to calculate the optimal portfolios of two models. According to notable differences of the proportions of two models, we identify a few stocks to determine their investing proportions. This helps to improve the optimality of portfolio to achieve our investing goal.