Stock Technical Analysis with Excel
What you'll learn
- 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 momentum 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 stock trading occasions through price crossovers confirmed by bands crossovers.
- Outline long-only stock trading strategies based on single or multiple technical indicators trading openings.
- Assess stock trading strategies performance by comparing their annualized return, standard deviation and Sharpe ratio against buy and hold benchmark.
Requirements
- Spreadsheet software such as Microsoft Excel® is required.
- Practical example spreadsheet provided with the course.
- Prior basic spreadsheet software knowledge is useful but not required.
Description
Full Course Content Last Update 06/2019
Learn stock technical analysis through a practical course with Microsoft Excel® 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 experienced investor. All of this while referencing best practitioners in the field.
Become a Stock Technical Analysis Expert in this Practical Course with Excel
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 momentum 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 stock trading occasions through price crossovers confirmed by bands crossovers.
Outline long-only stock trading strategies based on single or multiple technical indicators trading openings.
Assess stock trading strategies performance by comparing their annualized return, standard deviation and Sharpe ratio against buy and hold benchmark.
Become a Stock Technical Analysis Expert and Put Your Knowledge in Practice
Learning stock technical analysis is indispensable for finance careers in areas such as equity research and equity trading. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors stock technical trading research and development.
But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500® Index ETF prices historical data for back-testing to achieve greater effectiveness.
Content and Overview
This practical course contains 43 lectures and 8 hours of content. It’s designed for all stock technical analysis knowledge levels and a basic understanding of Microsoft Excel® is useful but not required.
At first, you’ll learn how to perform stock technical analysis operations using Microsoft Excel® built-in functions and array calculations.
Next, you’ll calculate lagging stock technical indicators such as simple moving averages, exponential moving averages, Bollinger bands®, parabolic stop and reverse. After that, you’ll compute leading stock technical indicators such as average directional movement index, commodity channel index, moving averages convergence/divergence, rate of change, relative strength index, stochastic momentum index, stochastic oscillator and Williams %R.
Then, you’ll define single technical indicator based stock trading openings through price, double, bands, centerline and signal crossovers. Next, you’ll determine multiple technical indicators based trading opportunities through price crossovers which need to be confirmed by second technical indicator band crossover. Later, you’ll give shape to long-only stock trading strategies using single or multiple technical indicators trading occasions.
Finally, you’ll evaluate stock trading strategies performance with buy and hold as initial benchmark and comparing their annualized return for performance, annualized standard deviation for volatility or risk and annualized Sharpe ratio for risk adjusted return.
Who this course is for:
- Undergraduates or postgraduates at any knowledge level who want to learn about stock technical analysis using Microsoft Excel®.
- Finance professionals or academic researchers who wish to deepen their knowledge in quantitative finance.
- Experienced investors who desire to research stock technical trading strategies.
- This course is NOT about “get rich quick” trading systems or magic formulas.
Instructor
Diego Fernandez is author of high-quality online courses and ebooks at Exfinsis for anyone who wants to become an expert in financial data analysis.
His main areas of expertise are financial analysis and data science. Within financial analysis he has focused on computational finance, quantitative finance and trading strategies analysis. Within data science he has concentrated on machine learning, applied statistics and econometrics. For all of this he has become proficient in Microsoft Excel®, R statistical software® and Python programming language® analysis tools.
He has important online business development experience at fast-growing startups and blue-chip companies in several European countries. He has always exceeded expected professional objectives by starting with a comprehensive analysis of business environment and then efficiently executing formulated strategy.
He also achieved outstanding performance in his undergraduate and postgraduate degrees at world-class academic institutions. This outperformance allowed him to become teacher assistant for specialized subjects and constant student leader within study groups.
His motivation is a lifelong passion for financial data analysis which he intends to transmit in all of the courses.