Manage Finance Data with Python & Pandas: Unique Masterclass

Analyze Stocks with Pandas, Numpy, Seaborn & ChatGPT. Create, analyze & optimize Index & Portfolios (CAPM, Alpha, Beta)

Created by: Alexander Hagmann
Data Scientist | Finance Professional | Entrepreneur

What Will I Learn?

• Step into the Financial Analyst role and give advice on a client´s financial Portfolio (Final Project)
• Import large Financial Datasets / historical Prices from Web Sources and analyze, aggregate and visualize them
• Calculate Return, Risk, Correlation and Rolling Statistics for Stocks, Indexes and Portfolios
• Create, analyze and optimize financial Portfolios and understand the use of the Sharpe Ratio
• Intuitively understand Modern Portfolio Theory (CAPM, Beta, Alpha, CML, SML, Risk Diversification) with Real Data examples
• Create Interactive Price Charts with Technical Indicators (Volume, OHLC, Candlestick, SMA etc.)
• Create Financial Indexes (price-, equal- and value- weighted) and understand the difference between Price Return and Total Return
• Easily switch between daily, weekly, monthly and annual returns and understand the benefits of log returns
• Start from Zero and learn all the Basics of the powerful Pandas Library

Requirements

• No specific Finance knowledge needed! The course intuitively explains the major fundamentals of Finance and Portfolio Theorie based on data examples.
• Ideally some Spreadsheet Basics/Programming Basics (not mandatory, the course guides you through the basics)
• A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
• An internet connection capable of streaming videos
• Some high school level math skills would be great (not mandatory, but it helps)

Target audience

• Investment & Finance Professionals who want to transition from Excel into Python to boost their careers and working efficiency.
• (Finance) Students and Researchers who need to handle large datasets and reached the limits of Excel.
• Data Scientists who want to improve their Data Handling/Manipulation skills (in particular for Time Series Data)
• Everyone who want to step into (Financial) Data Science. Pandas is Key to everything.
• Everyone curious about how Financial Performance is measured and how (Stock) Indexes and Portfolios are created, analyzed, visualized and optimized. It´s the easiest way to understand the concepts with data examples rather than theories and formulas.