Building Technical Indicators in Python

Building Technical Indicators in Python, available at $59.99, has an average rating of 4.79, with 44 lectures, based on 7 reviews, and has 108 subscribers.

You will learn about 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. This course is ideal for individuals who are Traders willing to use Technical Indicators in Algo Bots or Developers willing to develop Trading Bots for others or Students learning Data Science & Algo Trading It is particularly useful for Traders willing to use Technical Indicators in Algo Bots or Developers willing to develop Trading Bots for others or Students learning Data Science & Algo Trading.

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Summary

Title: Building Technical Indicators in Python

Price: $59.99

Average Rating: 4.79

Number of Lectures: 44

Number of Published Lectures: 44

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: ₹799

Quality Status: approved

Status: Live

What You Will 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.

Who Should Attend

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

Target Audiences

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

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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Technical Indicators

Lecture 2: Popular Technical Indicator Libraries

Lecture 3: Installing ta-lib library

Chapter 2: Technical Analysis

Lecture 1: Moving Averages

Lecture 2: Moving Average Convergence/Divergence (MACD)

Lecture 3: Bollinger Bands

Lecture 4: Average True Range (ATR) Part 1

Lecture 5: Average True Range (ATR) Part 2

Lecture 6: Relative Strength Indicator (RSI) Part 1

Lecture 7: Relative Strength Indicator (RSI) Part 2

Lecture 8: Introduction to Supertrend

Lecture 9: Supertrend using Google Sheets/Excel

Lecture 10: Supertrend using Python

Lecture 11: Introduction to Renko

Lecture 12: Renko using Brick Size

Lecture 13: Visualize Renko Chart with ATR

Lecture 14: Introduction to ADX

Lecture 15: ADX using Google Sheet/Excel

Lecture 16: ADX using Python

Chapter 3: Price Action

Lecture 1: Introduction to Price Action

Lecture 2: About Candlesticks

Lecture 3: Support and Resistance

Lecture 4: Introduction to Pivot Points

Lecture 5: Pivot Points with Python

Lecture 6: Introduction to Doji

Lecture 7: Doji Candles with Python

Lecture 8: Introduction to Hammer Candles

Lecture 9: Hammer Candles with Python

Lecture 10: Introduction to Shooting Star Candle

Lecture 11: Shooting Star Candle with Python

Lecture 12: Introduction to Marubozu candles

Lecture 13: Marubozu with Python

Lecture 14: Harami Candle Pattern

Lecture 15: Engulfing Pattern

Chapter 4: Candlestick Pattern Scanner

Lecture 1: Slope

Lecture 2: Trendline

Lecture 3: Pattern Scanner Part 1

Lecture 4: Pattern Scanner Part 2

Lecture 5: Pattern Scanner Part 3

Chapter 5: Strategy Development

Lecture 1: Introduction to Strategy Development

Lecture 2: SMA Strategy Backtesting

Lecture 3: Strategy Optimization

Lecture 4: Supertrend + MACD Strategy Part 1

Lecture 5: Supertrend + MACD Strategy Part 2

Instructors

Satyapal Singh
Chief Executive at Kimbly Labs Pvt Ltd

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3 stars: 1 votes
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5 stars: 6 votes

Frequently Asked Questions

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