Question

英语达人们帮忙翻译一下吧~~谢谢啦各位 悬赏25分

马考威茨的投资组合理论不但为分散投资提供了理论依据，而且也为如何进行有效的分散投资提供了分析框架。但在实际运用中，马考威茨模型也存在着一定的局限性和困难：
　　1．马考威茨模型所需要的基本输入包括证券的期望收益率、方差和两两证券之间的协方差。当证券的数量较多时，基本输入所要求的估计量非常大，从而也就使得马考威茨的运用受到很大限制。因此，马考威茨模型目前主要被用在资产配置的最优决策上。
　　2．数据误差带来的解的不可靠性。马考威茨模型需要将证券的期望收益率、期望的标准差和证券之间的期望相关系数作为已知数据作为基本输入。如果这些数据 没有估计误差，马考威茨模型就能够保证得到有效的证券组合。但由于期望数据是未知的，需要进行统计估计，因此这些数据就不会没有误差。这种由于统计估计而带来的数据输入方面的不准确性会使一些资产类别的投资比例过高而使另一些资产类别的投资比例过低。
　　3．解的不稳定性。马考威茨模型的另一个应用问题是输人数据的微小改变会导致资产权重的很大变化。解的不稳定性限制了马考威茨模型在实际制定资产配置政策方面的应用。如果基于季度对输人数据进行重新估计，用马考威茨模型就会得到新的资产权重的解，新的资产权重与上一季度的权重差异可能很大。这意味着必须对资产组合进行较大的调整，而频繁的调整会使人们对马考威茨模型产生不信任感。
　　4．重新配置的高成本。资产比例的调整会造成不必要的交易成本的上升。资产比例的调整会带来很多不利的影响，因此正确的政策可能是维持现状而不是最优化。
不要机器翻译的啊~麻烦各位了

Answer 1

MaKao wei's portfolio theory is not only provides theoretical basis for the diversification of investment, and also for how to effectively disperse investment provides analysis framework. But in actual use, MaKao wei watts model also has certain limitations and difficulties:
1. MaKao wei watts model need basic input including securities expectations yields, variance and two of the covariance between two securities. When the number of securities are too, basic input the required estimator is very large, and also can make MaKao wei's use is very limited. Therefore, MaKao wei watts model at present mainly used in the optimal asset allocation decisions.
2. Data error of the solution and not bring reliability. MaKao wei watts model of securities expect to return, and hope, standard deviation and the expectations of the correlation coefficient between securities as a known as the basic input data. If these data no estimate error, MaKao wei watts model can effectively ensure the portfolio. But because the expected data is unknown, need the statistics estimate, so the data will not without error. The statistical estimate because brought the data input on accuracy can make some asset classes of investment high proportion and the other some asset classes of investment ratio is too low.
3. The solution of stability. MaKao wei watts model of another application problem is input data small changes can lead to assets of the weights of the great changes. The stability of the solution of the restrictions MaKao wei watts model formulated in actual application of asset allocation policy. If the input data to based on the quarter to estimate, MaKao wei watts model with will get new assets of the solution of the weight, the new assets on the weight and the weight of the differences in the first quarter can be very large. This means that it must be on asset combination for major changes, and frequent adjustment will make people to MaKao wei watts model produce distrust.
4. The high cost of new configuration. The adjustment of assets ratio will cause unnecessary transaction costs to rise. The adjustment of assets ratio will bring many adverse effects, so the right policy could maintain the status quo is not optimal.
我是高中生，很多词都不会。用翻译器翻译的。将就一下吧。如果没有别的更好的，就选我为最佳吧，谢谢。

Answer 2

1楼想分数想疯了。都说不要机器翻译的了

这个文章难度太大，还涉及证券名词。等高手吧。

Answer 3

Makaoweici of the portfolio theory not only provided a theoretical basis for diversification, but also for how to conduct effective diversification provides analytical framework. In practical use, however, makaoweici model there are some limitations and difficulties:
1. Makaoweici basic models need input include securities expected yield, variance and covariance between 22 securities. When the number of securities during periods, as called for in the basic input estimates are very large, thus making makaoweici use is greatly restricted. Therefore, the makaoweici models are now mainly used in the optimal asset allocation decisions.
2. Unreliability of data error solution. Makaoweici model needs to be the expected yields, the expected standard deviation of securities and securities as known data expects between correlation coefficient as the basic input. If these data are not estimation error, makaoweici model will be able to ensure access to effective portfolio. But because of the expected data is unknown, requires statistical estimation, these data will not be without error. This statistical estimate resulting from inaccuracies in data entered the investment ratio is too high will make some asset classes and investment ratio is too low in other asset classes.
3. Instability of the solution. Another application of makaoweici model problem is that small changes can lead to lost data asset weights of great changes. Instability of the solution has limited makaoweici application model developed at the actual asset allocation policy. If based on quarterly data back to the lost people estimated that makaoweici model will be weighted solution for new assets, new asset weights and weight differences can be significant for the previous quarter. This means major adjustments to the portfolio, and frequent adjustments would distrust the people on the makaoweici model.
4. High costs of reconfiguration. Assets ratio adjustment will cause unnecessary increases in transaction costs. Assets ratio adjustment will bring a lot of adverse effects, so the correct policy may be to maintain the status quo rather than optimization.

Answer 4

MaKao wei's portfolio theory is not only provides theoretical basis for the diversification of investment, and also for how to effectively disperse investment provides analysis framework. But in actual use, MaKao wei watts model also has certain limitations and difficulties:
1. MaKao wei watts model need basic input including securities expectations yields, variance and two of the covariance between two securities. When the number of securities are too, basic input the required estimator is very large, and also can make MaKao wei's use is very limited. Therefore, MaKao wei watts model at present mainly used in the optimal asset allocation decisions.
2. Data error of the solution and not bring reliability. MaKao wei watts model of securities expect to return, and hope, standard deviation and the expectations of the correlation coefficient between securities as a known as the basic input data. If these data no estimate error, MaKao wei watts model can effectively ensure the portfolio. But because the expected data is unknown, need the statistics estimate, so the data will not without error. The statistical estimate because brought the data input on accuracy can make some asset classes of investment high proportion and the other some asset classes of investment ratio is too low.
3. The solution of stability. MaKao wei watts model of another application problem is input data small changes can lead to assets of the weights of the great changes. The stability of the solution of the restrictions MaKao wei watts model formulated in actual application of asset allocation policy. If the input data to based on the quarter to estimate, MaKao wei watts model with will get new assets of the solution of the weight, the new assets on the weight and the weight of the differences in the first quarter can be very large. This means that it must be on asset combination for major changes, and frequent adjustment will make people to MaKao wei watts model produce distrust.
4. The high cost of new configuration. The adjustment of assets ratio will cause unnecessary transaction costs to rise. The adjustment of assets ratio will bring many adverse effects, so the right policy could maintain the status quo is not optimal.