BISF Project
Statistical and predictive analysis on financial data based on the material of th Business Intelligence for Financial Services @ Unimib 2021/22.
Choosen stocks:
- Energy Sector
- XOM (Exxon Mobil Corporation)
- WMB (Williams Cos Inc)
- Technology Sector
- AAPL (Apple)
- TSLA (Tesla)
- Financial Sector
- JPM (JPMorgan Chase & Co.)
- BLK (BlackRock, Inc.)
Scheme of the Analysis:
- Summary of the used data
- Descriptive Statistics
- Simple and composite returns
- Returns distribution
- Q-Q plot of returns
- Univariate Statistics (mean, variance, skewness and kutrosis)
- Covariance Matrix
- Correlation matrix
- Correlation throught time
- Predictive Analysis
- Feature engineering
- splitting data in train set and test set
- Model training
- Results
- Trading Strategy and backtesting
- Trading strategy anatomy
- Backtesting
- Backtesing with a money management rules
- CAPM
- Beta of stocks
- Fama-French Factors
- Portfolio Optimization
- Efficient Frontier
- Minium Variance Portfolio
- Maxium Sharpe Ratio Portfolio
- Montecarlo simulation
- Optimal portfolio vs Effective Portfolio
You can find the notebook also on google colab.
Author
Paolo D'Elia