Technical Analysis with Python for Algorithmic Trading
What you'll learn
- Make proper use of Technical Analysis and Technical Indicators.
- Use Technical Analysis for (Day) Trading and Algorithmic Trading.
- Convert Technical Indictors into sound Trading Strategies with Python.
- Backtest and Forward Test Trading Strategies that are based on Technical Analysis/Indicators.
- Create and backtest combined Strategies with two or many Technical Indicators.
- Create interactive Charts (Line, Volume, OHLC, etc.) with Python and Plotly.
- Visualize Technical Indicators and Trend/Support/Resistance Lines with Python and Plotly.
- Use Pandas, Numpy and Object Oriented Programming (OOP) for Technical Analysis and Trading.
- Load Financial Data from local files and the web.
- Simple Moving Average (SMA) strategies
- Exponential Moving Average (EMA) strategies
- Moving Average Convergence Divergence (MACD) strategies
- Relative Strength Index (RSI) strategies
- Stochastic Oscillator strategies
- Bollinger Bands strategies
- Pivot Point strategies
- Fibonacci Retracement strategies
- mixed strategies (combining two or many indicators)
Course content
- Preview05:16
- 05:27Tips: How to get the most out of this course
- Preview01:57
- 02:07Student FAQ
- 00:37*** LEGAL DISCLAIMER (MUST READ!) ***
- 01:32Course Materials / Download
Requirements
- 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 HD videos.
- Basic Python Coding Skills (Variables, Data Types, Lists, For Loops, Functions) -> This is not a Course for complete Python Beginners.
- Basic Coding Skills in Pandas, Numpy and Matplotlib
- Basic Knowledge of Trading / Investing would be great (not mandatory, but it helps)
Description
"(How) Can I use Technical Analysis and Technical Indicators for Trading and Investing?" - This is one of the most frequently asked questions in trading and investing.
This course clearly goes beyond rules, theories, vague forecasts, and nice-looking charts. (These are useful but traders need more than that.) This is the first 100% data-driven course on Technical Analysis. We´ll use rigorous Backtesting / Forward Testing to identify and optimize proper Trading Strategies that are based on Technical Analysis / Indicators.
This course will allow you to test and challenge your trading ideas and hypothesis. It provides Python Coding Frameworks and Templates that will enable you to code and test thousands of trading strategies within minutes. Identify the profitable strategies and scrap the unprofitable ones!
The course covers the following Technical Analysis Tools and Indicators:
Interactive Line Charts and Candlestick Charts
Interactive Volume Charts
Trend, Support and Resistance Lines
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Moving Average Convergence Divergence (MACD)
Relative Strength Index (RSI)
Stochastic Oscillator
Bollinger Bands
Pivot Point (Price Action)
Fibonacci Retracement (Price Action)
combined/mixed Strategies and more.
This is not only a course on Technical Analysis and Trading. It´s an in-depth coding course on Python and its Data Science Libraries Numpy, Pandas, Matplotlib, Plotly, and more. You will learn how to use and master these Libraries for (Financial) Data Analysis, Technical Analysis, and Trading.
Please note: This is not a course for complete Python Beginners (check out my other courses!)
What are you waiting for? Join now and start making proper use of Technical Analysis!
As always, there is no risk for you as I provide a 30-Days-Money-Back Guarantee.
Thanks and looking forward to seeing you in the Course!
Who this course is for:
- (Day) Traders and Investors who want to make proper use of Technical Analysis.
- (Day) Traders and Investors who want to professionalize their Business.
- Technical Analyst and Chartist who want to improve their work/analysis with powerful Python Coding
- Everyone who wants to do more with Technical Analysis than just telling vague stories and creating pretty charts.
Instructor
![Alexander Hagmann](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.6 Instructor Rating
- 4,501 Reviews
- 42,692 Students
- 8 Courses
Alexander is a Data Scientist and Finance Professional with more than 10 years of experience in the Finance and Investment Industry.
He is also a Bestselling Udemy Instructor for
- Data Analysis/Manipulation with Pandas
- (Financial) Data Science
- Python for Business and Finance
- Algorithmic Trading
Alexander started his career in the traditional Finance sector and moved step-by-step into Data-driven and Artificial Intelligence-driven Finance roles. He is currently working on cutting-edge Fintech projects and creates solutions for Algorithmic Trading and Robo Investing. And Alexander is excited to share his knowledge with others here on Udemy. Students who completed his courses work in the largest and most popular tech and finance companies all over the world.
Alexander´s courses have one thing in common: Content and concepts are practical and real-world proven. The clear focus is on acquiring skills and understanding concepts rather than memorizing things.
Alexander holds a Master´s degree in Finance and passed all three CFA Exams (he is currently no active member of the CFA Institute).