Market-Watch-Tech-Analysis

In this project I want to show my python coding skills in Google Colaboratory Environment. Beside this, I will try to show all steps of technical analysis of investment portfolio using next python libraries:

1. Pandas(pandas data reader)
2. yfinance
3. NumPy(linAlg)
4. SciPy(optimize and stats)
5. Plotly(graph objects and subplots)
6. Statsmodels.api

I will do it in 7 steps:

1. Portfolio Optimization
2. Efficient Frontiers
3. CAPM Model
4. Sharpe's Ratio
5. Testing Portfolio Performances
6. Robustness portfolio
7. Black-Litterman model

After I did this I will compare it with non-technical analysis portfolio (Decision comes from gut and inspiration).

According to non-tech analysis starting portfolio, we use 6 companies:

1. Starbucks - SBUX - 0.13 weight
2. Coca Cola - KO - 0.22 weight
3. Microsoft - MSFT 0.04 weight
4. Pfizer - PFE 0.37 weight
5. Nike - NKE 0.12 weight
6. Exxon Mobil - 0.12 weight

Later Non Technical portfolio had 83 trades and a lot buying-selling companies, so for this analysis I will use only this 6 stocks

According to TA starting portfolio, we use 6 companies:

1. Astra Zeneca - AZN
2. Nvidia - NVD
3. Under Armour
4. Rivian - RIVN
5. Carnival Corporation - CCL
6. McDonalds - MCD