Final Project: Rerun the coding file 'final_2021_solution_update.R' and use the data you collected from the market. Make sure you collect or download data from the market (not restricted to stocks) and try to keep your portfolio including at least 5 assets. Show the performance of MVP (minimum variance portfolio) based on equal weighting, single factor, three factor and PCA models.

Final Project: Rerun the coding file 'final_2021_solution_update.R' and use the data you collected from the market. Make sure you collect or download data from the market (not restricted to stocks) and try to keep your portfolio including at least 5 assets. Show the performance of MVP (minimum variance portfolio) based on equal weighting, single factor, three factor and PCA models.

Rerun the coding file ‘final_2021_solution_update.R’ and use the data you collected from the market. Make sure you collect or download data from the market (not restricted to stocks) and try to keep your portfolio including at least 5 assets. Show the performance of MVP (minimum variance portfolio) based on equal weighting, single factor, three-factor, and PCA models.

1. Based on CAPM model, compute MVP monthly returns based on estimated covariance matrix for the 8-asset portfolio by using past 60-month returns from 2015/01 - 2021/03. (Hint: you can use SIT package or portfolioBacktest package to help you to run backtesting!) 2. Based on FF 3-factor model, compute MVP monthly returns covariance matrix for the 8-asset portfolio by using past 60-month returns from 2015/01 - 2021/03. 3. Based on PCA with 3 factors, compute MVP monthly returns covariance matrix for the 8-asset portfolio by using past 60-month returns from 2015/01 - 2021/03. (Hint: you can use package factorAnalytics or covFactorModel to extract covariance matrix based on 3-factor PCA analysis!) 4. Plot the performance of three strategies in the above and comment and conclude the results. (Plus points!)

Questions: 1. Import data 2. Calculate weekly and monthly returns using log returns 3. Convert monthly returns into tibble format. 4. Download Fama French 3 factors data and change to digit numbers (not in percetage): 5. Merge monthly return data in question 3 and 4 into tibble format. 6. Based on CAPM model, compute MVP monthly returns based on estimated covariance matrix for the 8-asset portfolio by using past 60-month returns from 2015/01 - 2021/03. 7. Based on FF 3-factor model, compute MVP monthly returns covariance matrix for the 8-asset portfolio by using past 60-month returns from 2015/01 - 2021/03.

Name: Adriani Hermawan Homework 5 1. Download 10 industry portfolio returns (average value-weighted monthly returns) from Fama French data library (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html) 2. Compute equal weight portfolio returns EACH month starting from 2000/01 to 2020/03. Denote this strategy as the Benchmark portfolio and create its backtesting report using SIT. 3. Compute MVP portfolio returns by rebalancing EACH month starting from 2000/01 to 2020/03. Use in-sample data range of 36 months to compute covariance matrix. Denote this strategy as the MVP portfolio and create its backtesting report using SIT. 4. Plot both strategies side by side and compare their performance and comment.

Name: Adriani Hermawan Homework: The monthly series of 3-month Treasury bill rates of the secondary market is used as the proxy for risk-free rate and has been deducted from the monthly returns to obtain the excess returns for stocks and market index. Compute global minimum variance portfolio weights and return by using single index model. Plot the weights for each MVP.

Name: Adriani Hermawan Homework 3: Question 3

Name: Adriani Hermawan Homework 2: Question 1 & Question 2

Homework 1 Name: Adriani Hermawan