Welcome to Python for Financial Analysis and Algorithmic Trading! Are you interested in how people use Python to conduct rigorous financial analysis and pursue algorithmic trading, then this is the right course for you!
This course will guide you through everything you need to know to use Python for Finance and Algorithmic Trading! We’ll start off by learning the fundamentals of Python, and then proceed to learn about the various core libraries used in the Py-Finance Ecosystem, including jupyter, numpy, pandas, matplotlib, statsmodels, zipline, Quantopian, and much more! We’ll cover the following topics used by financial professionals:
- Python Fundamentals
- NumPy for High Speed Numerical Processing
- Pandas for Efficient Data Analysis
- Matplotlib for Data Visualization
- Using pandas-datareader and Quandl for data ingestion
- Pandas Time Series Analysis Techniques
- Stock Returns Analysis
- Cumulative Daily Returns
- Volatility and Securities Risk
- EWMA (Exponentially Weighted Moving Average)
- Statsmodels
- ETS (Error-Trend-Seasonality)
- ARIMA (Auto-regressive Integrated Moving Averages)
- Auto Correlation Plots and Partial Auto Correlation Plots
- Sharpe Ratio
- Portfolio Allocation Optimization
- Efficient Frontier and Markowitz Optimization
- Types of Funds
- Order Books
- Short Selling
- Capital Asset Pricing Model
- Stock Splits and Dividends
- Efficient Market Hypothesis
- Algorithmic Trading with Quantopian
- Futures Trading
