Stock Market Data Analysis Visualization w Python More

Stock Market Data Analysis & Visualization w/ Python & More, available at $49.99, has an average rating of 3.1, with 32 lectures, based on 25 reviews, and has 299 subscribers.

You will learn about Calculate leading stock technical indicators or oscillators such as average directional movement index, commodity channel index, and more! Define multiple technical indicators based stock trading occasions through price crossovers confirmed by bands crossovers. Assess stock trading strategies performance by comparing their annualized return, standard deviation and Sharpe ratio against buy and hold Compute lagging stock technical indicators or overlays such as moving averages, Bollinger bands, parabolic stop and reverse. This course is ideal for individuals who are Undergraduates or postgraduates at any knowledge level who want to learn about stock market data analysis and visualisation using Python programming language. or Experienced investors who desire to research stock technical trading strategies. or Anyone who is interested to learning stock market data analysis or Finance professionals or academic researchers who wish to deepen their knowledge in quantitative finance. It is particularly useful for Undergraduates or postgraduates at any knowledge level who want to learn about stock market data analysis and visualisation using Python programming language. or Experienced investors who desire to research stock technical trading strategies. or Anyone who is interested to learning stock market data analysis or Finance professionals or academic researchers who wish to deepen their knowledge in quantitative finance.

Enroll now: Stock Market Data Analysis & Visualization w/ Python & More

Summary

Title: Stock Market Data Analysis & Visualization w/ Python & More

Price: $49.99

Average Rating: 3.1

Number of Lectures: 32

Number of Published Lectures: 32

Number of Curriculum Items: 32

Number of Published Curriculum Objects: 32

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Calculate leading stock technical indicators or oscillators such as average directional movement index, commodity channel index, and more!

Define multiple technical indicators based stock trading occasions through price crossovers confirmed by bands crossovers.

Assess stock trading strategies performance by comparing their annualized return, standard deviation and Sharpe ratio against buy and hold

Compute lagging stock technical indicators or overlays such as moving averages, Bollinger bands, parabolic stop and reverse.

Who Should Attend

Undergraduates or postgraduates at any knowledge level who want to learn about stock market data analysis and visualisation using Python programming language.

Experienced investors who desire to research stock technical trading strategies.

Anyone who is interested to learning stock market data analysis

Finance professionals or academic researchers who wish to deepen their knowledge in quantitative finance.

Target Audiences

Undergraduates or postgraduates at any knowledge level who want to learn about stock market data analysis and visualisation using Python programming language.

Experienced investors who desire to research stock technical trading strategies.

Anyone who is interested to learning stock market data analysis

Finance professionals or academic researchers who wish to deepen their knowledge in quantitative finance.

Learn stock technical analysis through a practical course with Python programming language using S&P 500? Index ETF historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work, or do research as an experienced investor. All of this while referencing the best practitioners in the field.

Become a Stock Technical Analysis Expert in this Practical Course with Python

Read or download S&P 500? Index ETF prices data and perform technical analysis operations by installing related packages and running code on Python IDE.

Compute lagging stock technical indicators or overlays such as moving averages, Bollinger bands, parabolic stop, and reverse.

Calculate leading stock technical indicators or oscillators such as average directional movement index, commodity channel index, moving averages convergence/divergence, rate of change, relative strength index, stochastic oscillator, and Williams %R.

Determine single technical indicator-based stock trading opportunities through price, double, bands, centerline, and signal crossovers.

Define multiple technical indicators based on stock trading occasions through price crossovers confirmed by bands crossovers.

Outline long (buy) or short (sell) stock trading strategies based on single or multiple technical indicators trading openings.

Evaluate stock trading strategies performances by comparing them against the buy and hold benchmark.

Course Curriculum

Chapter 1: Course Overview

Lecture 1: Project Preview

Chapter 2: Mammoth Interactive Courses Introduction

Lecture 1: 00 About Mammoth Interactive

Lecture 2: 01 How To Learn Online Effectively

Chapter 3: Introduction to Python (Prerequisite)

Lecture 1: 00. Intro To Course And Python

Lecture 2: 01. Variables

Lecture 3: 02. Type Conversion Examples

Lecture 4: 03. Operators

Lecture 5: 04. Collections

Lecture 6: 05. List Examples

Lecture 7: 06. Tuples Examples

Lecture 8: 07. Dictionaries Examples

Lecture 9: 08. Ranges Examples

Lecture 10: 09. Conditionals

Lecture 11: 10. If Statement Examples

Lecture 12: 11. Loops

Lecture 13: 12. Functions

Lecture 14: 13. Parameters And Return Values Examples

Lecture 15: 14. Classes And Objects

Lecture 16: 15. Inheritance Examples

Lecture 17: 16. Static Members Examples

Lecture 18: 17. Summary And Outro

Chapter 4: Compare Stocks and Returns

Lecture 1: 01 Fetch Stock Data

Lecture 2: 02 Visualize Stock Data Features

Lecture 3: 03 Calculate Daily Return

Lecture 4: 04 Compare Returns Of Different Stocks

Lecture 5: 05 Compare Closing Prices

Lecture 6: Source Files

Chapter 5: Calculate and Visualize Risk

Lecture 1: 01 Visualize Standard Deviation And Expected Returns

Lecture 2: 02 Calculate Value At Risk

Lecture 3: 03 Monte Carlo Analysis To Estimate Risk

Lecture 4: 04 Visualize Price Distribution

Lecture 5: Source Files

Instructors

Mammoth Interactive
Top-Rated Instructor, 3.3 Million+ Students

John Bura
Best Selling Instructor Web/App/Game Developer 1Mil Students

Rating Distribution

1 stars: 4 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 8 votes

5 stars: 11 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!