Stock Market Data Analysis & Visualization w/ Python & More

What you'll learn

Calculate leading stock technical indicators or oscillators such as average directional movement index, commodity channel index, moving averages convergence/divergenc

Assess stock trading strats 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.

Requirements

No necessary experience needed

Description

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 acad 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 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.

Detee 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 strats based on single or multiple technical indicators trading openings.

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

Who this course is for:

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 strats.

Anyone who is interested to learning stock market data analysis

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



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