This package contains templates for reports, and functions and workshops using in *Advanced Financial Data Analytrics * taught by Barry Quinn at Queen’s Business School.

remotes::install_github("quinfer/tsfe")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("quinfer/tsfe")

This is a basic example which shows you how to solve a common problem:

library(tsfe)
## basic example code
data("ftse350")  # This is a 2MB file so might take some time to initially load
summary(ftse350)
#>      Name              ticker            variable              date           
#>  Length:1014400     Length:1014400     Length:1014400     Min.   :2016-04-29  
#>  Class :character   Class :character   Class :character   1st Qu.:2017-06-14  
#>  Mode  :character   Mode  :character   Mode  :character   Median :2018-07-20  
#>                                                           Mean   :2018-07-13  
#>                                                           3rd Qu.:2019-08-14  
#>                                                           Max.   :2020-09-01  
#>      value          
#>  Min.   :     1.05  
#>  1st Qu.:   373.10  
#>  Median :   893.92  
#>  Mean   :  3273.80  
#>  3rd Qu.:  2210.00  
#>  Max.   :159163.60

You can start the tutorials in one of two ways. First, in RStudio 1.3 or later, you will find the ATI tutorials listed in the “Tutorial” tab in the top-right pane (by default). Find a tutorial and click “Run Tutorial” to get started. Second, you can run any tutorial from the R console by typing the following line:

learnr::run_tutorial("Workshop2","tsfe")

This should bring up a tutorial in your default web browser. You can see the full list of tutorials by running:

learnr::run_tutorial(package = "tsfe")

If you would like to access the raw RMarkdown code which created these tutorials you can do so here

This package also includes a RMarkdown template for use in the project report. Go to File>New>R Markdown… and choose from From Template then project-report. There are four sections in the report

• Introduction and literature review
• Data and methodology
• Results
• Discussion

The marks are allocated equally to each section.

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This package also includes dataset used in the course