本文通过东方财富选取A股市场五个板块的五只股票,分别是计算机软件行业的科大讯飞(002230)、电力行业的长江电力(600900)、饮料行业的五粮液(000858)、基本金属行业的中国铝业(601600)、贸易行业的中国中免(601888),提取五只股票2024年1月2日到3月28日的每日收盘价数据,建立马科维茨模型(均值–方差模型),通过均值、标准差、方差、协方差等有效信息,计算出权重、最小方差组合,以股票投资组合收益率最大为目标,分散所选择股票组合的投资风险,根据不同的投资者风险厌恶类型,最终确定最优投资组合。得出结论,股票长江电力的投资应占比最多,而股票中国铝业的投资比例应最少。In this paper, five stocks in five sectors of the A-share market are selected by Oriental Wealth, namely IFlytek (002230) in the computer software industry, Yangtze Electric Power (600900) in the power industry, Wuliangye (000858) in the beverage industry, Aluminum Corporation of China (601600) in the base metal industry, and China Free (601888) in the trade industry. The daily closing price data of five stocks from January 2 to March 28, 2024 was extracted, the Markowitz model (mean-variance model) was established, and the weight and minimum square were calculated through the effective information such as mean, standard deviation, variance and covariance poor portfolio, aiming at the maximum return rate of the stock portfolio, the investment risk of the selected stock portfolio was spread, and finally, the optimal investment portfolio was determined according to different risk aversion types of investors. It is concluded that the investment of Yangtze Power should be the most, while the investment of Chinalco should be the least.
随着我国经济的持续增长,投资的队伍也在不断壮大,“鸡蛋不能放在同一个篮子里”是所有投资者都知晓的道理。同时,鸡蛋该如何分配便成了我们所面临的问题。本论文通过应用马科维茨模型,研究并分析了沪股通中的投资组合优化问题。我们收集了沪股通中5只不同行业的股票从2023年12月1日到2024年3月8日之间62个工作日的收盘价为样本数据,首先将股票的日收盘价转换为日收益率,然后根据这些数据运用Matlab计算出了每只股票的期望收益率、方差、协方差矩阵等,并进行了初步分析。其次,我们利用二次规划的拉格朗日乘子法求解出在禁止卖空和允许卖空两种条件下的最优投资组合权重、期望收益率和标准差。实证结果表明,在“允许卖空”条件下,最优投资组合的收益率rp = 0.11%,投资风险σp = 0.007853;在“禁止卖空”条件下,最优投资组合的收益率rp = 0.15%,投资风险σp = 0.00827。由此可见,“禁止卖空”条件下的组合收益率较高,同时所对应的风险(标准差)也较大。With the continuous growth of China’s economy, the investment team is also constantly expanding. “eggs can not be placed in the same basket” is a truth known to all investors. At the same time, how to allocate eggs has become a problem we are facing. This paper studies and analyzes the investment portfolio optimization problem in the Shanghai-Hong Kong Stock Connect by applying the Markowitz model. We collected the closing prices of 5 stocks from different industries in the Shanghai-Hong Kong Stock Connect as sample data from December 1, 2023 to March 8, 2024, a total of 62 working days. Firstly, we converted the daily closing prices of the stocks into daily returns, and then based on these data, calculated the expected return rate, variance, covariance matrix, etc. of each stock using Matlab and conducted preliminary analysis. Secondly, we used the Lagrange multiplier method of quadratic programming to find the optimal investment portfolio weights, expected return rate, and standard deviation under the conditions of prohibiting short selling and allowing short selling. The empirical results show that under the “allowing short selling” condition, the optimal investment portfolio return rate (rp) is 0.11% and the investment risk (σp) is 0.007853;under the “prohibit short selling” condition, the optimal investment portfolio return rate (rp) is 0.15% and the investment risk (σp) is 0.00827. Therefore, it can be seen that the portfolio return rate under the “prohibit short selling” condition is higher, but the corresponding risk (standard devi
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