# 英国代写论文：投资模型

The dynamics of the market may change and hence the investor may again need to optimize the portfolio and rebalance the stocks. It can be a costly affair for the investor.
Another aspect is the liquidity. Liquidity can be a big issue and the investor may not be able to take action according to the market prices and thus the returns can be affected.
Standard deviation assumes that the returns are normally distributed. However, this may not be case in the real world. The returns of the stock may not be normally distributed and hence this can affect the results. The output given by the model may not be correct and hence it may not represent the true mean variance optimization.

As the number of stocks increases the model becomes more complicated and the simpler formulas are used to generalize the results. Thus it may not represent the true mean variance optimization. Thus this model becomes difficult to implement with a large number of stocks.
Thus there are many drawbacks if the model which can force the investor not to use this model. However, the best way to use this method is to realize the drawbacks of this method and accordingly take the decision. No model is perfect and thus if the investor knows the issues in the model he can take a decision which cater to his needs.
Optimal portfolio comes in between and 14% and 18%. Hence 16% is taken the return for optimal portfolio. The formula y = [ E (rp) – rf ] / A s2p is taken for calculating the percentage in the portfolio , the value is 85.14% in risky assets and the remaining value is risk free assets i.e. 14.86%.