matlab代写-ECON40115

ECON40115-ECON410JN
Portfolio Management 2020/2021 Masters Programmes

SUMMATIVE ASSIGNMENT

x The summative assignment is to build your own portfolio and evaluate it against
benchmarks. The data will be aYaLOabOe fURP DUO ZLWh Whe fLOe QaPe µdaWa.cVY¶.
x You have to use three benchmarks: the ex-post optimal portfolio, the equal-weight
portfolio, and the mean-variance portfolio with no-short-sale constraint and variance
equal to the equal-weighted portfolio variance over the sample period.
x You can choose any model as your own strategy, but it should not be a mean-variance
or minimum variance portfolio with some constraints.
x For the performance evaluation, you have to report the following measures: cumulative
return, mean return, standard deviation of the returns, Sharpe ratio, and turnover. Make
one performance table with (four) columns for the models and rows for the measures
(keep the order above). Returns and the standard deviation must be in percentage.
Annualize mean return, stdev, and Sharpe.
Cumulative Ret
Mean Ret
Stdev
Sharpe
Turnover
x Make the same table assuming 10 basis point transaction costs.
x The report should include the chosen model, implementation details, empirical results,
critical evaluation of the results, and the program source (in the appendix). The source
should be executable when copied and pasted.

Overall word limit, 2,500 words maximum.

Portfolio Management 期末作业要求 使用 Matlab 字数限制：不超过 2500字
• 作业是建立自己的投资组合，并根据 benchmarks进行评估。
• 你必须使用三个 benchmarks：事后最优投资组合、等权投资组合、均值-方差投资组合(无卖空限制且方差等于

• 你可以选择任何模型作为自己的策略，但不能是有一定约束条件的均值方差或最小方差组合。
• 对于绩效评估，你必须报告以下衡量指标：累计回报率、平均回报率、回报率的标准差、夏普比率和换手率。

Ex-post optimal portfolio Equal-weight portfolio Mean-variance portfolio Your Portfolio
Cumulative Return
Mean Return
Standard Deviation
Sharpe Ratio
Turnover Rate
• 假设交易成本为 10个基点，做同样的表格。
• 报告应包括所选择的模型、实施细节、实证结果、对结果的评价和源代码（附在附录中）。源代码在复制和粘贴

Data
Data source (from K. French website)
- Asset returns: 30_Industry.csv
- Factor returns/risk-free rate: FF_Factors.csv (risk-free rate column: ‘RF’)
- Make portfolios using the 30 industry portfolios.
- Note that all the returns are monthly returns and percentage values.

• 资产收益: 30_Industry.csv
• 因子收益/无风险利率: FF_Factors.csv (无风险利率列: 'RF')
• 使用 30个行业组合构建投资组合。
• 注意，所有的回报率都是月度回报率和百分比值。

Sample Period
- Out-of-sample period: 2000.01 to 2019.10, i.e., make the first portfolio at the beginning of 2000.01 (end of
1999.12) and the last portfolio at the beginning of 2019.10 (end of 2019.09).
- Estimation window size: 20 years
- Estimate input parameters every month by rolling the estimation window.

• 样本外期间：2000.01 至 2019.10，即在 2000.01 年初（1999.12 年底）构建第一个组合，在 2019.10 年初
（2019.09年底）构建最后一个组合。
• 估计窗口大小：20年
• 通过滚动估计窗口估计每月输入参数。

Rebalancing/Evaluation
Rebalancing
- Rebalance the portfolio monthly during the out-of-sample period.
- This means that you will have 238 monthly returns for each portfolio.

• 在样本外期间，每月对组合进行重新平衡。
• 这意味着您的每个投资组合将有 238个月度收益。
Performance Evaluation
- Follow the table format given in the summative assignment.
- Changing the order of columns/rows is not accepted.
- Use returns in excess of the risk-free rate for all calculations, e.g., the cumulative return should be the
cumulative excess return.
- Report annualized percentage values for the mean, std, and Sharpe.
- Two decimal points for all numerical values.

• 遵循作业要求中给出的表格格式
• 不能改变列/行的顺序
• 在所有计算中使用超过无风险利率的收益，例如，累计收益应该是累计超额收益。
• 报告均值、标准差和夏普比率的年化百分比值。
• 所有数值均为小数点后两位。

Benchmarks
Ex-post optimal portfolio
- This is the tangent portfolio obtained from the sample mean and covariance matrix over the out-of-sample
period.
- This is a hypothetical optimal portfolio you can have if you can observe future returns.

• 这是由样本均值和协方差矩阵在样本外期间得到的切线组合。
• 这是一个假设的你可以拥有的最佳投资组合，如果你能观察到未来的收益。
Equal-weight portfolio
- 1/N rule.

• 1/N规则（等权重）
Mean-variance portfolio with no short-sale and variance targeting
- Use the variance of the equal-weight portfolio over the out-of-sample period as the variance target.
- Find the tangent portfolio under the short-sale constraint, and then mix it with the risk-free asset so that the
variance matches the target.

• 用等权重组合在样本外期间的方差作为方差目标。
• 找到卖空约束下的切线组合，然后将其与无风险资产混合，使方差与目标相符。

What to report
Below are the minimum you should report.
- The chosen model: You should explain the model and show the exact formula you use. Source code
- Implementation details: Estimation methods, assumptions made, etc.
- Empirical results and analysis
- References: Only those cited in the report
- Source code: Should have sufficient comments so I can understand the code.

• 所选模型：你应该解释这个模型，并展示你使用的具体公式。
• 实施细节：估算方法、所作的假设等。
• 实证结果和分析
• 参考文献：报告中引用的那些
• 源代码：应该有足够的注释，这样我才能理解代码。