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
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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.
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Compute lagging stock technical indicators or overlays such as moving averages, Bollinger bands, parabolic stop, and reverse.
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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.
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Determine single technical indicator-based stock trading opportunities through price, double, bands, centerline, and signal crossovers.
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Define multiple technical indicators based on stock trading occasions through price crossovers confirmed by bands crossovers.
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Outline long (buy) or short (sell) stock trading strategies based on single or multiple technical indicators trading openings.
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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
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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!
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