Investment Analysis & Portfolio Management with Python

Financial Analysis Done Right - Rigorously Analyse Investments & Manage Portfolios using Python for Finance / Investing

Created by: Fervent #LearnWithDistinction
Rigorous courses, backed by research, taught with simplicity

Created by: Support from Fervent

What Will I Learn?

• Calculate stock returns manually as well as on Python, using real world data obtained from free sources.
• Extensively work with a variety of Python libraries including Pandas, NumPy, SciPy, Matplotlib, to name a few.
• Understand why the math works, and what the equations mean - even if your math is weak and if math freaks you out.
• Witness the power of diversification and how the risk of your portfolio can be lower than the individual assets that make up the portfolio!
• Estimate the Expected Returns of Stocks using the Mean Method, State Contingent Weighted Probabilities, as well as Asset Pricing Models.
• Calculate the total risk, market risk, and firm specific risk of stocks from scratch, and explore how the different risks interact.
• Measure your investment portfolio's performance by calculating portfolio returns and risks.
• Optimise your portfolios by maximising your returns while minimising your risk.
• Create custom functions to automate your Investment Analysis & Portfolio Management techniques, leveraging the power of Python.
• Explore computations from scratch, so you understand how Python works behind the scenes.

Requirements

• Coding knowledge is REQUIRED. You don't need to be an 'expert' in Python, but you DO need to know how to code.
• At a minimum, we assume you know what lists, dictionaries, and tuples are; and you know the difference between strings, integers, and floats.
• This is a Finance course which uses Python. It is NOT a Python course about Finance.
• No prior knowledge of Finance is required nor assumed.
• It's okay if math freaks you out. Seriously. Every single equation is explained one variable at a time. We rip it apart to its core, and show you how simple it really is.
• Knowledge of basic statistical analysis is useful but NOT essential.
• You'll need a calculator, pen and paper (seriously), and your development environment (e.g. Jupyter Notebooks, Text Editors)
• We work with Jupyter Notebooks in the course, but .py versions of all Python code is available for download.

Target audience

• Ivy League / Russell Group University students looking to increase their competitive advantage and enhance their skills.
• Finance Managers keen on applying conceptual techniques including portfolio design using Python.
• Investors wanting to work with techniques that are rigorously grounded in academic and practitioner literature.
• Analysts, and aspiring Investment Bankers wanting to gain a solid foundation in investment analysis.
• Anyone who wants to learn investment analysis and portfolio management with Python!