This package contains templates for reports, and functions and workshops using in Time series financial econometrics taught by Barry Quinn at Queen’s Management School.
remotes::install_github("barryquinn1/tsfe")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("barryquinn1/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. :159163.60You 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.
|
criterion |
description_Expectation not met |
description_Approaching Expectation |
description_Meets Expectation |
description_Exceeds Expectation |
value_Expectation not met |
value_Approaching Expectation |
value_Meets Expectation |
value_Exceeds Expectation |
|---|---|---|---|---|---|---|---|---|
|
Intro+Lit |
The introduction needs a lot more work. A poor and incomplete review of the literature which doesn’t show any critical ability. |
The introduction broadly sets out the problem but could be much improved. The literature review requires more content and critical comment. |
An adequate introduction which broadly sets out the problem. A good literature review that sets out some of the relevant literature but need more critique. |
A very good introduction which is easy to read and introduces the problem well, setting out the overall project aim. A very good literature review, detailing the relevant literature and critiquing it. |
5 |
15 |
20 |
25 |
|
Data+methods |
A poor model is used with very little critical comment. |
Appropriate model and estimation techniques are used but little critique is used. |
A good model construct and use of the standard estimation techniques. There is some critique of the methods. |
A very good model construction with critical comments of its use. Estimation techniques are well laid out and critiqued, with some improvements mentioned. |
5 |
15 |
20 |
25 |
|
Results |
Results are not well defined and the use of tables and graphs needs much more work. |
Poor use of graphs and tables. Inferences are poor and are not well related to previous empirical research. |
There is appropriate use of both tables and graphs. The inferences on results are good but have sparse critical comments. Improvement could be made with more contextual comment about previous empirical results. |
Very good use is made of both tables and graphs. The most interesting features of the results are well identified with inferences related to overall project aims. A excellent critique of your results using previous empirical research. |
5 |
15 |
20 |
25 |
|
Discussion |
Poor and incomplete inferences and conclusions from the previous sections |
Some inference from the previous sections. |
Good use of critical inferences with some reference to how findings are related to the existing literature. |
Excellent use of critical inferences with well thought out critique given the literature described in the previous sections. |
5 |
15 |
20 |
25 |
|
Originality |
Lacking methodological application. Adequately argued. Basic understanding and knowledge. Gaps or inaccuracies but not damaging.Little relevance material and/or inaccurate answer or incomplete. Disorganised and irrelevant material and misunderstanding. Minimal or no relevant material. |
Very good knowledge and understanding of module content. Well argued answers. Evidence of originality and critical judgement. Sound methodology. Critical judgement and some grasp of complex issuesGood knowledge and understanding of the module content. Reasonably well-argued. Largely descriptive or narrative in focus. Methodological application is not consistent or thorough. |
Very good knowledge and understanding of module content. Well argued answers. Evidence of originality and critical judgement. Sound methodology. Critical judgement and some grasp of complex issu |
Thorough and systematic knowledge and understanding of the module content. A clear grasp of the issues involved, with evidence of innovative and the original use of learning resources. Knowledge beyond module content. Clear evidence of independent thought and originality. Methodological rigour. High critical judgement and a confident grasp of complex issues |
5 |
18 |
28 |
40 |
This package also includes dataset used in the course