Background
As a Business Economics student, I have studied about asset allocations (for example, assume I have $1000, and I want to invest in stock A and stock B. My asset allocation strategy describes how much I put into stock A and how much I put into stock B.) One strategy is to minimize the portfolio variance (ie. distributing the $1000 in such a way so that the total variance of stock A and stock B is minimized).
Goals
This project aims at creating a Python program that helps investors implement this strategy; this project also attempts to evaluate the benefits and costs of applying this strategy in the real world.
Hypothesis
The benefits of minimizing the variance of a two assets portfolio outweigh the costs of minimizing the variance of this portfolio. Methodology II section will explain more detailed how to measure the benefits and costs of minimizing the variance.
Data sources
I have obtained all the raw data from Google finance; Google spreadsheet has a function that allows users to import data (such as weekly prices of different stocks) from Google finance. Then I copied and pasted these data into Excel.
From Excel, I export the weekly stock prices data as a CSV file for Python to format; Python returns a new CSV file that I can analyze using Excel. Different CSV files are transferred back and forth between Python and Excel throughout the project. The Reflection section will address the technical challenges in using Python to handle CSV files.
As a Business Economics student, I have studied about asset allocations (for example, assume I have $1000, and I want to invest in stock A and stock B. My asset allocation strategy describes how much I put into stock A and how much I put into stock B.) One strategy is to minimize the portfolio variance (ie. distributing the $1000 in such a way so that the total variance of stock A and stock B is minimized).
Goals
This project aims at creating a Python program that helps investors implement this strategy; this project also attempts to evaluate the benefits and costs of applying this strategy in the real world.
Hypothesis
The benefits of minimizing the variance of a two assets portfolio outweigh the costs of minimizing the variance of this portfolio. Methodology II section will explain more detailed how to measure the benefits and costs of minimizing the variance.
Data sources
I have obtained all the raw data from Google finance; Google spreadsheet has a function that allows users to import data (such as weekly prices of different stocks) from Google finance. Then I copied and pasted these data into Excel.
From Excel, I export the weekly stock prices data as a CSV file for Python to format; Python returns a new CSV file that I can analyze using Excel. Different CSV files are transferred back and forth between Python and Excel throughout the project. The Reflection section will address the technical challenges in using Python to handle CSV files.