Stock Technical Analysis with Python

Course details

Learn stock technical analysis through a practical course with Python programming language using real world data. It explores main concepts from basic to expert level which can help you achieve better grades, develop your finance career or make decisions as DIY investor. All of this while referencing best practitioners in the field.

Become a Stock Technical Analysis Expert in this Practical Course with Python

• Download stock data and perform technical analysis operations by installing related packages and running code on the Python IDE.
• Compute lagging stock technical indicators such as moving averages and Bollinger bands®.
• Calculate leading stock technical indicators such as moving averages convergence/divergence and relative strength index.
• Determine single technical indicator based stock trading opportunities through price, double, bands and signal crossovers.
• Define multiple stock indicators based stock trading occasions through price crossovers confirmed by bands crossovers.
• Outline long (buy) or short (sell) stock trading strategies based on single or multiple technical indicators trading openings.
• Evaluate stock trading strategies performances by comparing them against buy and hold benchmark.

Become a Stock Technical Analysis Expert and Put Your Knowledge in Practice

Learning stock technical analysis is indispensable for finance careers in areas such as equity research or equity trading. It is also essential for academic careers in quantitative finance.  And it is one of the two most common analysis techniques for DIY investors.

But as learning process can become difficult as complexity grows, this course helps by leading you through step by step real world practical examples for greater effectiveness.

Content and Overview

This practical course contains 45 lectures and 8.5 hours of content. It's designed for all stock technical analysis knowledge levels and a basic understanding of Python programming language is useful but not required.

At first, you'll learn how to download stock data and perform technical analysis operations by installing related packages and running code on the Python IDE. Next, you'll calculate lagging stock technical indicators such as simple moving averages (SMA), exponential moving averages (EMA), Bollinger bands® (BB), parabolic stop and reverse (SAR). After that, you'll compute leading stock technical indicators such as average directional movement index (ADX), commodity channel index (CCI), moving averages convergence/divergence (MACD), rate of change (ROC), relative strength index (RSI), stochastic oscillator (Full STO) and Williams %R.

Then, you'll define single technical indicator based stock trading openings through price, double, bands and signal crossovers. Next, you'll determine multiple technical indicators based trading opportunities through price crossovers which need to be confirmed by second technical indicator band crossover. Later, you'll give shape to stock trading strategies which are long (buying) or short (selling) using single or multiple technical indicators trading occasions.

Finally, you'll evaluate stock trading strategies performance with buy and hold as initial benchmark and comparing their annualized return for performance, annualized standard deviation for volatility or risk and annualized Sharpe ratio for risk adjusted return.