Building Technical Indicators In Python

Learn to use Technical Indicators in your trading Strategies using Python

What you'll learn

Learn how to use Python to implement technical indicators in trading and investing strategies.

Gain knowledge of various types of technical indicators, such as moving averages, RSI, MACD, Bollinger Bands, and more.

Develop a comprehensive understanding of the strengths and limitations of technical indicators, and when they should be used in combination with other forms of

Develop practical skills through hands-on exercises and examples to implement technical indicators in Python.

Understand the mathematical calculations and algorithms that are used to generate technical indicators.

Requirements

Basic knowledge of Python and Stock Trading

Description

This course will provide students with a comprehensive understanding of how to use technical indicators and candlestick patterns in stock trading.The course will start by covering the basics of technical indicators, and candlestick patterns including the use of third-party libraries in your strategy. Then, we will dive into the world of technical indicators and candlestick patterns.Some of the most popular technical indicators that we will cover in this course include Simple Moving Average (SMA), Exponential Moving Average (EMA), Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands, and Fibonacci Retracements. We will also cover popular candlestick patterns such as Doji, Hammer, and Shooting Star.To facilitate the implementation of these indicators and patterns, we will use popular libraries such as Talib, pandas TA, and tulip.  We will also use popular charting libraries like matplotlib, plotly & mplfinance. These libraries will enable students to write code in Python to calculate and plot these indicators and patterns on price charts and provide them with the ability to analyze and make informed trading decisions. We will also include mathematical formulas used in these indicators along with custom code in case you want to develop your own indicator.By the end of the course, students will have a strong understanding of how technical indicators and candlestick patterns work and how to use them to make profitable trades. Students will also have the necessary skills to implement these indicators and patterns using Python, and will be well-equipped to analyze market trends and make informed trading decisions.

Overview

Section 1: Introduction

Lecture 1 Introduction to Technical Indicators

Lecture 2 Popular Technical Indicator Libraries

Section 2: Technical Analysis

Lecture 3 Moving Averages

Lecture 4 Moving Average Convergence/Divergence (MACD)

Lecture 5 Bollinger Bands

Lecture 6 Average True Range (ATR) Part 1

Lecture 7 Average True Range (ATR) Part 2

Lecture 8 Relative Strength Indicator (RSI) Part 1

Lecture 9 Relative Strength Indicator (RSI) Part 2

Lecture 10 Introduction to Supertrend

Lecture 11 Supertrend using Google Sheets/Excel

Lecture 12 Supertrend using Python

Lecture 13 Introduction to Renko

Lecture 14 Renko using Brick Size

Lecture 15 Visualize Renko Chart with ATR

Lecture 16 Introduction to ADX

Lecture 17 ADX using Google Sheet/Excel

Lecture 18 ADX using Python

Section 3: Price Action

Lecture 19 Introduction to Price Action

Lecture 20 About Candlesticks

Lecture 21 Support and Resistance

Lecture 22 Introduction to Pivot Points

Lecture 23 Pivot Points with Python

Lecture 24 Introduction to Doji

Lecture 25 Doji Candles with Python

Lecture 26 Introduction to Hammer Candles

Lecture 27 Hammer Candles with Python

Lecture 28 Introduction to Shooting Star Candle

Lecture 29 Shooting Star Candle with Python

Lecture 30 Introduction to Marubozu candles

Lecture 31 Marubozu with Python

Lecture 32 Harami Candle Pattern

Lecture 33 Engulfing Pattern

Section 4: Candlestick Pattern Scanner

Lecture 34 Slope

Lecture 35 Trendline

Lecture 36 Pattern Scanner Part 1

Lecture 37 Pattern Scanner Part 2

Lecture 38 Pattern Scanner Part 3

Section 5: Strategy Development

Lecture 39 Introduction to Strategy Development

Lecture 40 SMA Strategy Backtesting

Lecture 41 Strategy Optimization

Lecture 42 Supertrend + MACD Strategy Part 1

Lecture 43 Supertrend + MACD Strategy Part 2

Traders willing to use Technical Indicators in Algo Bots,Developers willing to develop Trading Bots for others,Students learning Data Science & Algo Trading