Practical Data Science: Analyzing Stock Market Data with R

  • Course provided by Udemy
  • Study type: Online
  • Starts: Anytime
  • Price: See latest price on Udemy
Udemy

Course Description

In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are.

What We'll Cover

  1. Easily access free, stock-market data using R and the quantmod package
  2. Build great looking stock charts with quantmod
  3. Use R to manipulate time-series data
  4. Create a moving average from scratch
  5. Access technical indicators with the TTR package
  6. Create a simple trading systems by shifting time series using the binhf package
  7. A look at trend-following trading systems using moving averages
  8. A look at counter-trend trading systems using moving averages
  9. Using more sophisticated indicators (ROC, RSI, CCI, VWAP, Chaikin Volatility)
  10. Grouping stocks by theme to better understand them
  11. Finding coupling and decoupling stocks within an index

What This Class Isn't

This class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas.

Who this course is for:

  • Those looking to expand their R skills on stock market data
  • Those looking to come up with their own conclusions about the markets
  • NOT for those seeking easy stock tips or secret trading systems
  • NOT a solicitation to trade - trading is difficult, learn as much as you can before risking real money
  • NO guarantee that past historical strategies will work on future events

Instructor

Data Scientist & Quantitative Developer
  • 4.4 Instructor Rating
  • 1,327 Reviews
  • 38,518 Students
  • 12 Courses

Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML.


From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say:


"It just ain’t real 'til it reaches your customer’s plate"


I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning.


Reach me at [email protected]

Expected Outcomes

  1. Use R on stock market data for insight and ideas Download free, daily stock market data from Yahoo Plot great looking financial charts Apply basic technical analysis on stock market data Explore trading ideas and display entries and exits Gain additional insights by comparing similar stocks Course content 7 sections • 18 lectures • 4h 3m total length Expand all sections Introduction 2 lectures • 8min What is covered in this class Preview 01:36 Optional: R Console or RStudio? Preview 06:35 Downloading Free Stock Market Data with R 1 lecture • 13min Downloading free daily stock market data from Google Preview 12:47 Creating Amazing Stock Charts with quantmod 3 lectures • 31min Creating great charts with quantmod 11:23 Adding Indicators to quantmod charts 14:03 Creating an R Markdown file to display all your charts in one document 05:33 Applying Technical Analysis Indicators 6 lectures • 1hr 48min Creating a simple moving average (SMA) from scratch 19:52 Following the trend with multiple moving averages 19:53 More insights from multiple moving averages 19:13 Insight from Common indicators - ADX & VWAP 19:49 Counter-trend systems - ROC, RSI, CCI, Chaikin Volatility 18:48 Optional: Counter-trend systems - tweaks 10:38 Tracking Profit and Loss for Fun! 1 lecture • 18min Evaluating our trend-following systems 17:33 Analyzing Stocks in Groups 4 lectures • 1hr 5min Evaluating counter-trend systems 12:05 Safety in Numbers: Basket Analysis 17:13 Correlation analysis 18:25 Applying correlations to entries 17:34 Conclusions 1 lecture • 1min Closing notes 00:30 Requirements Basic understanding of R Access to R Console or RStudio Interest in stock-market data Description In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are. What We'll Cover Easily access free, stock-market data using R and the quantmod package Build great looking stock charts with quantmod Use R to manipulate time-series data Create a moving average from scratch Access technical indicators with the TTR package Create a simple trading systems by shifting time series using the binhf package A look at trend-following trading systems using moving averages A look at counter-trend trading systems using moving averages Using more sophisticated indicators ( ROC, RSI, CCI, VWAP, Chaikin Volatility ) Grouping stocks by theme to better understand them Finding coupling and decoupling stocks within an index What This Class Isn't This class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas. Who this course is for: Those looking to expand their R skills on stock market data Those looking to come up with their own conclusions about the markets NOT for those seeking easy stock tips or secret trading systems NOT a solicitation to trade - trading is difficult, learn as much as you can before risking real money NO guarantee that past historical strategies will work on future events Show more Show less Instructor Manuel Amunategui Data Scientist & Quantitative Developer 4.4 Instructor Rating 1,327 Reviews 38,518 Students 12 Courses Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML. From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say: "It just ain’t real 'til it reaches your customer’s plate" I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning. Reach me at [email protected] Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6777b5627d6240ef',m:'442d20f32225872c078f38a14ce28ba1bbc36c12-1627743755-1800-AeZIz/wG6OQtzjnb+mqjVozIPI6sJ9fEsU0/+OLI7mh5qbzy8jof78D3DZjvACpZA8QCRPnh1qAf4RxvurOehkgenu/iy7X+4IerLBaUUrGKhYXPGmqfsrFSG/KlExqdkpvxnwqiJBpPbiy9Bxp/dC0IdjrOvEe3gAhl9fyydTFkXOtgAhFAC6ThEh4W5CXNHp3bv2lxQMLGyYxYlGTVqV0=',s:[0xd1c5e2d060,0x4f86451be8],}})();
  2. Download free, daily stock market data from Yahoo Plot great looking financial charts Apply basic technical analysis on stock market data Explore trading ideas and display entries and exits Gain additional insights by comparing similar stocks Course content 7 sections • 18 lectures • 4h 3m total length Expand all sections Introduction 2 lectures • 8min What is covered in this class Preview 01:36 Optional: R Console or RStudio? Preview 06:35 Downloading Free Stock Market Data with R 1 lecture • 13min Downloading free daily stock market data from Google Preview 12:47 Creating Amazing Stock Charts with quantmod 3 lectures • 31min Creating great charts with quantmod 11:23 Adding Indicators to quantmod charts 14:03 Creating an R Markdown file to display all your charts in one document 05:33 Applying Technical Analysis Indicators 6 lectures • 1hr 48min Creating a simple moving average (SMA) from scratch 19:52 Following the trend with multiple moving averages 19:53 More insights from multiple moving averages 19:13 Insight from Common indicators - ADX & VWAP 19:49 Counter-trend systems - ROC, RSI, CCI, Chaikin Volatility 18:48 Optional: Counter-trend systems - tweaks 10:38 Tracking Profit and Loss for Fun! 1 lecture • 18min Evaluating our trend-following systems 17:33 Analyzing Stocks in Groups 4 lectures • 1hr 5min Evaluating counter-trend systems 12:05 Safety in Numbers: Basket Analysis 17:13 Correlation analysis 18:25 Applying correlations to entries 17:34 Conclusions 1 lecture • 1min Closing notes 00:30 Requirements Basic understanding of R Access to R Console or RStudio Interest in stock-market data Description In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are. What We'll Cover Easily access free, stock-market data using R and the quantmod package Build great looking stock charts with quantmod Use R to manipulate time-series data Create a moving average from scratch Access technical indicators with the TTR package Create a simple trading systems by shifting time series using the binhf package A look at trend-following trading systems using moving averages A look at counter-trend trading systems using moving averages Using more sophisticated indicators ( ROC, RSI, CCI, VWAP, Chaikin Volatility ) Grouping stocks by theme to better understand them Finding coupling and decoupling stocks within an index What This Class Isn't This class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas. Who this course is for: Those looking to expand their R skills on stock market data Those looking to come up with their own conclusions about the markets NOT for those seeking easy stock tips or secret trading systems NOT a solicitation to trade - trading is difficult, learn as much as you can before risking real money NO guarantee that past historical strategies will work on future events Show more Show less Instructor Manuel Amunategui Data Scientist & Quantitative Developer 4.4 Instructor Rating 1,327 Reviews 38,518 Students 12 Courses Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML. From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say: "It just ain’t real 'til it reaches your customer’s plate" I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning. Reach me at [email protected] Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6777b5627d6240ef',m:'442d20f32225872c078f38a14ce28ba1bbc36c12-1627743755-1800-AeZIz/wG6OQtzjnb+mqjVozIPI6sJ9fEsU0/+OLI7mh5qbzy8jof78D3DZjvACpZA8QCRPnh1qAf4RxvurOehkgenu/iy7X+4IerLBaUUrGKhYXPGmqfsrFSG/KlExqdkpvxnwqiJBpPbiy9Bxp/dC0IdjrOvEe3gAhl9fyydTFkXOtgAhFAC6ThEh4W5CXNHp3bv2lxQMLGyYxYlGTVqV0=',s:[0xd1c5e2d060,0x4f86451be8],}})();
  3. Plot great looking financial charts Apply basic technical analysis on stock market data Explore trading ideas and display entries and exits Gain additional insights by comparing similar stocks Course content 7 sections • 18 lectures • 4h 3m total length Expand all sections Introduction 2 lectures • 8min What is covered in this class Preview 01:36 Optional: R Console or RStudio? Preview 06:35 Downloading Free Stock Market Data with R 1 lecture • 13min Downloading free daily stock market data from Google Preview 12:47 Creating Amazing Stock Charts with quantmod 3 lectures • 31min Creating great charts with quantmod 11:23 Adding Indicators to quantmod charts 14:03 Creating an R Markdown file to display all your charts in one document 05:33 Applying Technical Analysis Indicators 6 lectures • 1hr 48min Creating a simple moving average (SMA) from scratch 19:52 Following the trend with multiple moving averages 19:53 More insights from multiple moving averages 19:13 Insight from Common indicators - ADX & VWAP 19:49 Counter-trend systems - ROC, RSI, CCI, Chaikin Volatility 18:48 Optional: Counter-trend systems - tweaks 10:38 Tracking Profit and Loss for Fun! 1 lecture • 18min Evaluating our trend-following systems 17:33 Analyzing Stocks in Groups 4 lectures • 1hr 5min Evaluating counter-trend systems 12:05 Safety in Numbers: Basket Analysis 17:13 Correlation analysis 18:25 Applying correlations to entries 17:34 Conclusions 1 lecture • 1min Closing notes 00:30 Requirements Basic understanding of R Access to R Console or RStudio Interest in stock-market data Description In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are. What We'll Cover Easily access free, stock-market data using R and the quantmod package Build great looking stock charts with quantmod Use R to manipulate time-series data Create a moving average from scratch Access technical indicators with the TTR package Create a simple trading systems by shifting time series using the binhf package A look at trend-following trading systems using moving averages A look at counter-trend trading systems using moving averages Using more sophisticated indicators ( ROC, RSI, CCI, VWAP, Chaikin Volatility ) Grouping stocks by theme to better understand them Finding coupling and decoupling stocks within an index What This Class Isn't This class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas. Who this course is for: Those looking to expand their R skills on stock market data Those looking to come up with their own conclusions about the markets NOT for those seeking easy stock tips or secret trading systems NOT a solicitation to trade - trading is difficult, learn as much as you can before risking real money NO guarantee that past historical strategies will work on future events Show more Show less Instructor Manuel Amunategui Data Scientist & Quantitative Developer 4.4 Instructor Rating 1,327 Reviews 38,518 Students 12 Courses Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML. From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say: "It just ain’t real 'til it reaches your customer’s plate" I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning. Reach me at [email protected] Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6777b5627d6240ef',m:'442d20f32225872c078f38a14ce28ba1bbc36c12-1627743755-1800-AeZIz/wG6OQtzjnb+mqjVozIPI6sJ9fEsU0/+OLI7mh5qbzy8jof78D3DZjvACpZA8QCRPnh1qAf4RxvurOehkgenu/iy7X+4IerLBaUUrGKhYXPGmqfsrFSG/KlExqdkpvxnwqiJBpPbiy9Bxp/dC0IdjrOvEe3gAhl9fyydTFkXOtgAhFAC6ThEh4W5CXNHp3bv2lxQMLGyYxYlGTVqV0=',s:[0xd1c5e2d060,0x4f86451be8],}})();
  4. Apply basic technical analysis on stock market data Explore trading ideas and display entries and exits Gain additional insights by comparing similar stocks Course content 7 sections • 18 lectures • 4h 3m total length Expand all sections Introduction 2 lectures • 8min What is covered in this class Preview 01:36 Optional: R Console or RStudio? Preview 06:35 Downloading Free Stock Market Data with R 1 lecture • 13min Downloading free daily stock market data from Google Preview 12:47 Creating Amazing Stock Charts with quantmod 3 lectures • 31min Creating great charts with quantmod 11:23 Adding Indicators to quantmod charts 14:03 Creating an R Markdown file to display all your charts in one document 05:33 Applying Technical Analysis Indicators 6 lectures • 1hr 48min Creating a simple moving average (SMA) from scratch 19:52 Following the trend with multiple moving averages 19:53 More insights from multiple moving averages 19:13 Insight from Common indicators - ADX & VWAP 19:49 Counter-trend systems - ROC, RSI, CCI, Chaikin Volatility 18:48 Optional: Counter-trend systems - tweaks 10:38 Tracking Profit and Loss for Fun! 1 lecture • 18min Evaluating our trend-following systems 17:33 Analyzing Stocks in Groups 4 lectures • 1hr 5min Evaluating counter-trend systems 12:05 Safety in Numbers: Basket Analysis 17:13 Correlation analysis 18:25 Applying correlations to entries 17:34 Conclusions 1 lecture • 1min Closing notes 00:30 Requirements Basic understanding of R Access to R Console or RStudio Interest in stock-market data Description In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are. What We'll Cover Easily access free, stock-market data using R and the quantmod package Build great looking stock charts with quantmod Use R to manipulate time-series data Create a moving average from scratch Access technical indicators with the TTR package Create a simple trading systems by shifting time series using the binhf package A look at trend-following trading systems using moving averages A look at counter-trend trading systems using moving averages Using more sophisticated indicators ( ROC, RSI, CCI, VWAP, Chaikin Volatility ) Grouping stocks by theme to better understand them Finding coupling and decoupling stocks within an index What This Class Isn't This class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas. Who this course is for: Those looking to expand their R skills on stock market data Those looking to come up with their own conclusions about the markets NOT for those seeking easy stock tips or secret trading systems NOT a solicitation to trade - trading is difficult, learn as much as you can before risking real money NO guarantee that past historical strategies will work on future events Show more Show less Instructor Manuel Amunategui Data Scientist & Quantitative Developer 4.4 Instructor Rating 1,327 Reviews 38,518 Students 12 Courses Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML. From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say: "It just ain’t real 'til it reaches your customer’s plate" I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning. Reach me at [email protected] Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6777b5627d6240ef',m:'442d20f32225872c078f38a14ce28ba1bbc36c12-1627743755-1800-AeZIz/wG6OQtzjnb+mqjVozIPI6sJ9fEsU0/+OLI7mh5qbzy8jof78D3DZjvACpZA8QCRPnh1qAf4RxvurOehkgenu/iy7X+4IerLBaUUrGKhYXPGmqfsrFSG/KlExqdkpvxnwqiJBpPbiy9Bxp/dC0IdjrOvEe3gAhl9fyydTFkXOtgAhFAC6ThEh4W5CXNHp3bv2lxQMLGyYxYlGTVqV0=',s:[0xd1c5e2d060,0x4f86451be8],}})();
  5. Explore trading ideas and display entries and exits Gain additional insights by comparing similar stocks Course content 7 sections • 18 lectures • 4h 3m total length Expand all sections Introduction 2 lectures • 8min What is covered in this class Preview 01:36 Optional: R Console or RStudio? Preview 06:35 Downloading Free Stock Market Data with R 1 lecture • 13min Downloading free daily stock market data from Google Preview 12:47 Creating Amazing Stock Charts with quantmod 3 lectures • 31min Creating great charts with quantmod 11:23 Adding Indicators to quantmod charts 14:03 Creating an R Markdown file to display all your charts in one document 05:33 Applying Technical Analysis Indicators 6 lectures • 1hr 48min Creating a simple moving average (SMA) from scratch 19:52 Following the trend with multiple moving averages 19:53 More insights from multiple moving averages 19:13 Insight from Common indicators - ADX & VWAP 19:49 Counter-trend systems - ROC, RSI, CCI, Chaikin Volatility 18:48 Optional: Counter-trend systems - tweaks 10:38 Tracking Profit and Loss for Fun! 1 lecture • 18min Evaluating our trend-following systems 17:33 Analyzing Stocks in Groups 4 lectures • 1hr 5min Evaluating counter-trend systems 12:05 Safety in Numbers: Basket Analysis 17:13 Correlation analysis 18:25 Applying correlations to entries 17:34 Conclusions 1 lecture • 1min Closing notes 00:30 Requirements Basic understanding of R Access to R Console or RStudio Interest in stock-market data Description In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are. What We'll Cover Easily access free, stock-market data using R and the quantmod package Build great looking stock charts with quantmod Use R to manipulate time-series data Create a moving average from scratch Access technical indicators with the TTR package Create a simple trading systems by shifting time series using the binhf package A look at trend-following trading systems using moving averages A look at counter-trend trading systems using moving averages Using more sophisticated indicators ( ROC, RSI, CCI, VWAP, Chaikin Volatility ) Grouping stocks by theme to better understand them Finding coupling and decoupling stocks within an index What This Class Isn't This class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas. Who this course is for: Those looking to expand their R skills on stock market data Those looking to come up with their own conclusions about the markets NOT for those seeking easy stock tips or secret trading systems NOT a solicitation to trade - trading is difficult, learn as much as you can before risking real money NO guarantee that past historical strategies will work on future events Show more Show less Instructor Manuel Amunategui Data Scientist & Quantitative Developer 4.4 Instructor Rating 1,327 Reviews 38,518 Students 12 Courses Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML. From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say: "It just ain’t real 'til it reaches your customer’s plate" I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning. Reach me at [email protected] Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6777b5627d6240ef',m:'442d20f32225872c078f38a14ce28ba1bbc36c12-1627743755-1800-AeZIz/wG6OQtzjnb+mqjVozIPI6sJ9fEsU0/+OLI7mh5qbzy8jof78D3DZjvACpZA8QCRPnh1qAf4RxvurOehkgenu/iy7X+4IerLBaUUrGKhYXPGmqfsrFSG/KlExqdkpvxnwqiJBpPbiy9Bxp/dC0IdjrOvEe3gAhl9fyydTFkXOtgAhFAC6ThEh4W5CXNHp3bv2lxQMLGyYxYlGTVqV0=',s:[0xd1c5e2d060,0x4f86451be8],}})();
  6. Gain additional insights by comparing similar stocks Course content 7 sections • 18 lectures • 4h 3m total length Expand all sections Introduction 2 lectures • 8min What is covered in this class Preview 01:36 Optional: R Console or RStudio? Preview 06:35 Downloading Free Stock Market Data with R 1 lecture • 13min Downloading free daily stock market data from Google Preview 12:47 Creating Amazing Stock Charts with quantmod 3 lectures • 31min Creating great charts with quantmod 11:23 Adding Indicators to quantmod charts 14:03 Creating an R Markdown file to display all your charts in one document 05:33 Applying Technical Analysis Indicators 6 lectures • 1hr 48min Creating a simple moving average (SMA) from scratch 19:52 Following the trend with multiple moving averages 19:53 More insights from multiple moving averages 19:13 Insight from Common indicators - ADX & VWAP 19:49 Counter-trend systems - ROC, RSI, CCI, Chaikin Volatility 18:48 Optional: Counter-trend systems - tweaks 10:38 Tracking Profit and Loss for Fun! 1 lecture • 18min Evaluating our trend-following systems 17:33 Analyzing Stocks in Groups 4 lectures • 1hr 5min Evaluating counter-trend systems 12:05 Safety in Numbers: Basket Analysis 17:13 Correlation analysis 18:25 Applying correlations to entries 17:34 Conclusions 1 lecture • 1min Closing notes 00:30 Requirements Basic understanding of R Access to R Console or RStudio Interest in stock-market data Description In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are. What We'll Cover Easily access free, stock-market data using R and the quantmod package Build great looking stock charts with quantmod Use R to manipulate time-series data Create a moving average from scratch Access technical indicators with the TTR package Create a simple trading systems by shifting time series using the binhf package A look at trend-following trading systems using moving averages A look at counter-trend trading systems using moving averages Using more sophisticated indicators ( ROC, RSI, CCI, VWAP, Chaikin Volatility ) Grouping stocks by theme to better understand them Finding coupling and decoupling stocks within an index What This Class Isn't This class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas. Who this course is for: Those looking to expand their R skills on stock market data Those looking to come up with their own conclusions about the markets NOT for those seeking easy stock tips or secret trading systems NOT a solicitation to trade - trading is difficult, learn as much as you can before risking real money NO guarantee that past historical strategies will work on future events Show more Show less Instructor Manuel Amunategui Data Scientist & Quantitative Developer 4.4 Instructor Rating 1,327 Reviews 38,518 Students 12 Courses Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML. From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say: "It just ain’t real 'til it reaches your customer’s plate" I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning. Reach me at [email protected] Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? 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