Pairs Trading Analysis with R
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Pairs Trading Analysis with R

Learn pairs trading analysis from basic to expert level through a practical course with R statistical software.
4.6 (5 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
32 students enrolled
Created by Diego Fernandez
Last updated 7/2017
English
Curiosity Sale
Current price: $10 Original price: $50 Discount: 80% off
30-Day Money-Back Guarantee
Includes:
  • 5.5 hours on-demand video
  • 7 Articles
  • 7 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Read or download MSCI® Countries Indexes ETF prices data and perform pairs trading analysis operations by installing related packages and running script code on RStudio IDE.
  • Identify pairs of international countries stock indexes prices with similar behavior based on fundamental factors of countries with relevant commodities sector and from specific region.
  • Test pairs short term statistical relationship through their price returns correlation coefficient.
  • Assess single pairs spread co-integration or long term statistical relationship through Engle-Granger test.
  • Evaluate if individual price time series are non-stationary and their spread is stationary through Augmented Dickey-Fuller, Phillips-Perron and Hurst exponent tests.
  • Measure multiple pairs spread vectors co-integration or long term statistical relationship through Johansen test.
  • Calculate trading strategies for co-integrated pairs spreads.
  • Generate entry or exit trading signals based on rolling spread normalized time series or z-score crossing certain bands thresholds.
  • Produce long or short trading positions associated to trading signals.
  • Assess trading strategies performance against buy and hold benchmarks using annualized return, annualized standard deviation, annualized Sharpe ratio metrics and cumulative returns, maximum drawdown charts.
View Curriculum
Requirements
  • R statistical software is required. Downloading instructions included.
  • RStudio Integrated Development Environment (IDE) is recommended. Downloading instructions included.
  • Practical example data and R script code files provided with the course.
  • Prior basic R statistical software knowledge is useful but not required.
Description

Learn pairs trading analysis through a practical course with R statistical software using MSCI® countries indexes ETFs 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 your research as experienced investor. All of this while exploring the wisdom of Nobel Prize winners and best practitioners in the field.

Become a Pairs Trading Analysis Expert in this Practical Course with R

  • Read or download MSCI® Countries Indexes ETF prices data and perform pairs trading analysis operations by installing related packages and running script code on RStudio IDE.
  • Identify pairs of international countries stock indexes prices with similar behavior based on fundamental factors of countries with relevant commodities sector and from specific region.
  • Test pairs short term statistical relationship through their price returns correlation coefficient.
  • Assess single pairs spread co-integration or long term statistical relationship through Engle-Granger test.
  • Evaluate if individual price time series are non-stationary and their spread is stationary through Augmented Dickey-Fuller, Phillips-Perron and Hurst exponent tests.
  • Measure multiple pairs spread vectors co-integration or long term statistical relationship through Johansen test.
  • Calculate trading strategies for co-integrated pairs spreads.
  • Generate entry or exit trading signals based on rolling spread normalized time series or z-score crossing certain bands thresholds.
  • Produce long or short trading positions associated to trading signals.
  • Assess trading strategies performance against buy and hold benchmarks using annualized return, annualized standard deviation, annualized Sharpe ratio metrics and cumulative returns, maximum drawdown charts.

Become a Pairs Trading Analysis Expert and Put Your Knowledge in Practice

Learning pairs trading analysis is indispensable for finance careers in areas such as quantitative research, quantitative development, and quantitative trading mainly within investment banks and hedge funds. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors quantitative trading research and development.

But as learning curve can become steep as complexity grows, this course helps by leading you step by step using MSCI® Countries Indexes ETF prices historical data for back-testing to achieve greater effectiveness. 

Content and Overview

This practical course contains 49 lectures and 5 hours of content. It’s designed for all pairs trading analysis knowledge levels and a basic understanding of R statistical software is useful but not required.

At first, you’ll learn how to read or download MSCI® Countries Indexes ETF prices historical data to perform pairs trading analysis operations by installing related packages and running script code on RStudio IDE.

Then, you’ll identify pairs for international countries stock indexes prices with similar behavior based on fundamental factors of countries with relevant commodities sector and from specific region. After that, you’ll test pairs short term statistical relationship through their price returns correlation coefficient.

Next, you’ll asses single pairs spread co-integration or long term statistical relationship through Engle-Granger test. Later, you’ll evaluate whether individual price time series are non-stationary and their spread is stationary using Augmented Dickey-Fuller, Phillips-Perron and Hurst exponent tests. Then, you’ll evaluate multiple pairs spread vectors co-integration or long term statistical relationship through Johansen test.

After that, you’ll calculate co-integrated pair spreads trading strategies.  Next, you’ll generate entry or exit trading signals based on rolling spread normalized time series or z-score crossing certain bands thresholds. Later, you’ll produce long or short trading positions based on previously generated trading signals.

Finally, you’ll measure trading strategies performance against individual paired stock indexes buy and hold benchmarks through annualized return, annualized standard deviation, annualized Sharpe ratio and cumulative returns, maximum drawdown charts

Who is the target audience?
  • Undergraduates or postgraduates who want to learn about pairs trading analysis using R statistical software.
  • Finance professionals or academic researchers who wish to deepen their knowledge in quantitative finance.
  • Experienced investors who desire to research pairs trading strategies.
  • This course is NOT about “get rich quick” trading strategies or magic formulas.
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Curriculum For This Course
49 Lectures
05:21:53
+
Course Overview
7 Lectures 26:16

In this lecture you will view course disclaimer and learn which are its objectives, how you will benefit from it, its previous requirements and my profile as instructor.

Preview 04:38

In this lecture you will learn that it is recommended to view course in an ascendant manner as each section builds on last one and also does its complexity. You will also study course structure and main sections (pairs identification, pairs spread co-integration, pairs trading signals, pairs strategies performance comparison).

Preview 02:14

In this lecture you will learn pairs trading analysis definition, R statistical software and RStudio Integrated Development Environment (IDE) downloading websites.

Pairs Trading Analysis
04:17

In this lecture you will learn pairs trading analysis data reading or downloading into RStudio Integrated Development Environment (IDE), data sources, R script code files originally in .TXT format that need to be converted in .R format with pairs trading analysis computation instructions, R packages installation (tseries, quantmod, PerformanceAnalytics, roll, urca) and related code (library(), read.csv(), xts(), getSymbols() functions).

Pairs Trading Analysis Data
14:58

Before starting course please download .TXT data file in .CSV format as additional resources.

Course Data File
00:03

Before starting course please download .TXT R script file as additional resources.

Course Script Code File
00:03

You can download .PDF section slides file as additional resources.

Course Overview Slides
00:02
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Pairs Identification
10 Lectures 50:59

You can download .PDF section slides file as additional resources.

Pairs Identification Slides
00:02

In this lecture you will learn section lectures’ details and main themes to be covered related to pairs identification (single and multiple pairs identification).

Preview 08:38

In this lecture you will learn single pair identification definition and main calculations (dailyReturn(), cor(), plot(), as.zoo(), par(), axis(), legend() functions).

Single Pair Identification 1
08:05

In this lecture you will learn single pair identification definition and main calculations (dailyReturn(), cor(), plot(), as.zoo(), par(), axis(), legend() functions).

Single Pair Identification 2
06:23

In this lecture you will learn single pair identification definition and main calculations (dailyReturn(), cor(), plot(), as.zoo(), par(), axis(), legend() functions).

Single Pair Identification 3
05:06

In this lecture you will learn single pair identification definition and main calculations (dailyReturn(), cor(), plot(), as.zoo(), par(), axis(), legend() functions).

Single Pair Identification 4
05:17

In this lecture you will learn single pair identification definition and main calculations (dailyReturn(), cor(), plot(), as.zoo(), par(), axis(), legend() functions).

Single Pair Identification 5
05:11

In this lecture you will learn single pair identification definition and main calculations (dailyReturn(), cor(), plot(), as.zoo(), par(), axis(), legend() functions).

Single Pair Identification 6
04:39

In this lecture you will learn multiple pairs identification definition and main calculations (cbind(), colnames(), cor() functions).

Multiple Pairs Identification 1
03:59

In this lecture you will learn multiple pairs identification definition and main calculations (cbind(), colnames(), cor() functions).

Multiple Pairs Identification 2
03:39
+
Pairs Spread Co-Integration
16 Lectures 01:29:38

You can download .PDF section slides file as additional resources.

Pairs Spread Co-Integration Slides
00:02

In this lecture you will learn section lectures’ details and main themes to be covered related to pairs spread co-integration (single pair spreads, single pair spreads co-integration and multiple pairs spread co-integration). 

Pairs Spread Co-Integration Overview
07:11

In this lecture you will learn single pair spread definition and main calculations (lm(), lm$coefficients[], plot(), abline(), mean(),  functions). 

Single Pair Spread 1
05:06

In this lecture you will learn single pair spread definition and main calculations (lm(), lm$coefficients[], plot(), abline(), mean(),  functions). 

Single Pair Spread 2
04:17

In this lecture you will learn single pair spread definition and main calculations (lm(), lm$coefficients[], plot(), abline(), mean(),  functions). 

Single Pair Spread 3
03:59

In this lecture you will learn single pair spread definition and main calculations (lm(), lm$coefficients[], plot(), abline(), mean(),  functions). 

Single Pair Spread 4
03:23

In this lecture you will learn single pair spread definition and main calculations (lm(), lm$coefficients[], plot(), abline(), mean(),  functions). 

Single Pair Spread 5
03:34

In this lecture you will learn single pair spread definition and main calculations (lm(), lm$coefficients[], plot(), abline(), mean(),  functions). 

Single Pair Spread 6
04:01

In this lecture you will learn single pair spread co-integration definition and main calculations (adf.test(), diff(), complete.cases(), pp.test(), HurstIndex() functions).

Single Pair Spread Co-Integration 1
11:47

In this lecture you will learn single pair spread co-integration definition and main calculations (adf.test(), diff(), complete.cases(), pp.test(), HurstIndex() functions).

Single Pair Spread Co-Integration 2
05:45

In this lecture you will learn single pair spread co-integration definition and main calculations (adf.test(), diff(), complete.cases(), pp.test(), HurstIndex() functions).

Single Pair Spread Co-Integration 3
05:23

In this lecture you will learn single pair spread co-integration definition and main calculations (adf.test(), diff(), complete.cases(), pp.test(), HurstIndex() functions).

Single Pair Spread Co-Integration 4
05:45

In this lecture you will learn single pair spread co-integration definition and main calculations (adf.test(), diff(), complete.cases(), pp.test(), HurstIndex() functions).

Single Pair Spread Co-Integration 5
05:38

In this lecture you will learn single pair spread co-integration definition and main calculations (adf.test(), diff(), complete.cases(), pp.test(), HurstIndex() functions).

Single Pair Spread Co-Integration 6
05:13

In this lecture you will learn multiple pairs spread co-integration definition and main calculations (ca.jo(), summary(), plot(), abline(), adf.test(), pp.test(), HurstIndex() functions).

Multiple Pairs Spread Co-Integration 1
10:53

In this lecture you will learn multiple pairs spread co-integration definition and main calculations (ca.jo(), summary(), plot(), abline(), adf.test(), pp.test(), HurstIndex() functions).

Multiple Pairs Spread Co-Integration 2
07:41
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Pairs Trading Strategies
10 Lectures 01:37:43

You can download .PDF section slides file as additional resources.

Pairs Trading Strategies Slides
00:02

In this lecture you will learn section lectures’ detail and main themes to be covered related to pairs trading strategies (single pair spreads z-score and trading signals).

Pairs Trading Strategies Overview
10:09

In this lecture you will learn single pair spread z-score definition and main calculations (roll_lm(), plot(), abline(), roll_scale() functions).

Single Pair Spread Z-Score 1
10:18

In this lecture you will learn single pair spread z-score definition and main calculations (roll_lm(), plot(), abline(), roll_scale() functions).

Single Pair Spread Z-Score 2
09:44

In this lecture you will learn single pair spread z-score definition and main calculations (roll_lm(), plot(), abline(), roll_scale() functions).

Single Pair Spread Z-Score 3
08:59

In this lecture you will learn single pair spread z-score definition and main calculations (roll_lm(), plot(), abline(), roll_scale() functions).

Single Pair Spread Z-Score 4
09:33

In this lecture you will learn single pair trading signals definition and main calculations (Lag(), ifelse(), is.na(), for(){}, cbind(), colnames(), View() functions).

Single Pair Trading Signals 1
13:51

In this lecture you will learn single pair trading signals definition and main calculations (Lag(), ifelse(), is.na(), for(){}, cbind(), colnames(), View() functions).

Single Pair Trading Signals 2
10:50

In this lecture you will learn single pair trading signals definition and main calculations (Lag(), ifelse(), is.na(), for(){}, cbind(), colnames(), View() functions).

Single Pair Trading Signals 3
12:03

In this lecture you will learn single pair trading signals definition and main calculations (Lag(), ifelse(), is.na(), for(){}, cbind(), colnames(), View() functions).

Single Pair Trading Signals 4
12:14
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Pairs Strategies Performance Comparison
6 Lectures 57:13

You can download .PDF section slides file as additional resources.

Pairs Strategies Performance Comparison Slides
00:02

In this lecture you will learn section lectures’ detail and main themes to be covered related to pairs strategies performance comparison.

Pairs Strategies Performance Comparison Overview
12:28

In this lecture you will learn single pair strategy performance definition and main calculations (ifelse(), cbind(), colnames(), table.AnnualizedReturns(), charts.PerformanceSummary() functions).

Single Pair Strategy Performance 1
12:28

In this lecture you will learn single pair strategy performance definition and main calculations (ifelse(), cbind(), colnames(), table.AnnualizedReturns(), charts.PerformanceSummary() functions).

Single Pair Strategy Performance 2
09:48

In this lecture you will learn single pair strategy performance definition and main calculations (ifelse(), cbind(), colnames(), table.AnnualizedReturns(), charts.PerformanceSummary() functions).

Single Pair Strategy Performance 3
11:24

In this lecture you will learn single pair strategy performance definition and main calculations (ifelse(), cbind(), colnames(), table.AnnualizedReturns(), charts.PerformanceSummary() functions).

Single Pair Strategy Performance 4
11:03
About the Instructor
Diego Fernandez
3.8 Average rating
434 Reviews
2,994 Students
21 Courses
Exfinsis

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.