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)
“(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!
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