Description of Learning Track: Technical Analysis Using Quantitative Methods
A series of curated courses to help you develop proficiency in Technical Analysis in trading using quantitative methods as well as help understand the creation of quantitative trading strategies.
Get started with Python programming, apply more than 15 technical indicators to generate trading signals, identify trends, perform swing trading, create trading strategies and backtest to improve your likelihood of success. Learn Candlestick patterns, charts, volatility and how to measure it better.
What will you learn in Learning Track: Technical Analysis Using Quantitative Methods?
- Code various trading strategies using Python, Sentiment Indicators, etc.
- Data types, sources, usage, importing and visualization.
- Identify single and multiple candlestick patterns like Marubozu, Hammer, Hanging Man, Shooting Star, Doji, Engulfing, Piercing and Dark Cloud Cover.
- Apply technical indicators such as moving average, RSI, MACD, Chaikin Oscillator, etc. and analyse price charts.
- Swing trading using technical indicators such as MACD and Williams Fractals.
- Predict trends, analyse risks, and analyse the performance of trading strategies.
- Define volatility and measure volatility using ATR, standard deviation and beta.
- Practice the concepts learnt through a capstone project.
- Backtesting as well as calculating transaction costs and slippage.
- Paper trade and live trade your strategy.
Who Learning Track: Technical Analysis Using Quantitative Methods is for?
One is expected to have a basic knowledge of financial markets, placing trading orders, concepts and terminologies. A hands-on experience in trading and using trading platforms is recommended.
Familiarity in Python, using it, and Python libraries would be an added advantage. It is recommended that you commit to the learning and practice regularly on the hands-on learning exercises provided in the learning track.