Investment Analysis Simulation Report

Investment Simulation 3

Stocks list: This time I still use the 15 stocks I have chosen in simulation 2. (Exhibit A)

Steps to get data for Sharpe model:

1.Rf: Use VMMXX to get Rf.  Rf＝p2-p1. Here we only use Rf from October 2009 to September 2014. (Exhibit B)

2. Rm and Ri: Use Get Historical Data From Yahoo spreadsheet to get Rm. First I type in the 15 companies. Then I chose the frequency as monthly. To make sure all data are included, the time period is from August 2009 to October 2014. I use the data collected in VFIAX as Rm. Each stock’s Ri can also be found here. (Exhibit C&D)

3. α，β，σ：Put Rf, Rm, Ri into MMTool spreadsheet, calculate each stock’s historical monthly α，β，σ. Then calculate historical annual α，β，σ.

αAnnual = 12 × αMonthly

βAnnual = βMonthly

σ(e)Annual = × σ(e)Monthly[pic 1]

Lastly, calculate prospective annual α，β，σ. (Exhibit E)

α = 0.00%

β =[pic 2]

σ= σ(e)Annual

Weight output in Sharpe model:

Put each stock’s α，β，σ into Sharpe Optimal Portfolio Selection spreadsheet and run the optimizer.

Exhibit B

[pic 3]

Exhibit C

[pic 4]

Exhibit D

[pic 5]

Exhibit E

[pic 6]

Investment Philosophy: Stocks with smaller market capitalizations tend to have superior returns.

Rationale: According to the model built by Klein and Bawa (1977), they find that if insufficient information about a subset of securities, investors will not hold these securities because of estimation risk. If investor differ in the amount of information available, they will limit their diversification to different subsets of all securities in the market. [1]  The amount of information collected is related with the size of the firm. In this way, many investors would not desire to hold the common stock of very small firms. Thus lack of information about small firms leads to limited diversification and therefore to higher returns for the stocks of small firms. [2] 

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