Hi there, this is the first time I post up one of my completed Codecademy projects. Hope I’m doing it right.
I’ve loaded up my solution to the Real Estate Investment Trusts Analysis project which is part of the Analysing Financial Data with Python Skill Path as is an introduction to NumPy project using analysis of financial data.
You can find it on my Github here!
I would appreciate feedback to confirm my conclusions are correct, and also that it’s ok to be posting in this way via GitHub? Should I be providing additional acknowledgement of Codecademy, or any licensing information?
My conclusions are:
-
SBRA’s average daily simple return was 0.21% over the course of 2018 whereas EQR’s average daily simple return was 0.16% so based on this information, SBRA is more likely to be profitable in the future.
-
SBRA’s annualized daily log return in 2018 was 50% EQR’s annualized daily log return was 39% so based on this information, SBRA is more likely to be profitable in the future.
-
In 2018, the variance of SBRA’s daily log return was 0.00018, whereas for EQR was 0.000068 so SBRA has a higher variance thus riskier on a daily basis.
-
In 2018, the standard deviation of SBRA’s daily log return was 1.3%, whereas for EQR was 0.8% so SBRA has a higher standard deviation thus is riskier on a daily basis.
-
Correlation between SBRA and EQR is 0.62 which is a moderately strong positive correlation. i.e. quite likely one will move similarly to the other. So not great to have them both together in an investment portfolio.
-
SBRA was in 2018 a bit risker, but had moderately higher returns, so probably the better investment, unless you are very risk adverse.