Submission: stockAnalyzer (R)

Submitting Author: Kangyu (Mark) Wang (@ZIBOWANGKANGYU), Sicheng (Marc) Sun (@MarcSunUBC), Tingyu Zhang (@Tammy1128), William Xu (@williamxu7) Repository: stockAnalyzer Version submitted: 1.1.0 Editor: Tiffany Timbers (@ttimbers) Reviewers: TBD

Archive: TBD Version accepted: TBD

Paste the full DESCRIPTION file inside a code block below:

Package: stockAnalyzer
Type: Package
Title: Provide Basic Time Series Modelling Functionalities to Analyze Historical Stock Prices
Version: 1.1.0
Author: Kangyu (Mark) Wang, Sicheng (Marc) Sun, Tingyu Zhang, William Xu
Maintainer: Mark Wang <changguang@outlook.com>
Description: This is an R package that provides basic time series modelling functionalities to analyze historical stock prices. 
    Investment in the stock market requires not only knowledge about the listed companies, but also basic summary statistics and modellings of individual stock prices. 
    Given time-series stock price data, this package provides key summary statistics, applies moving average and exponential smoothing models to the data, and visualizes in-sample moving average as well as exponential smoothing fits. 
    The library has five functions, namely `summaryStats`, `movingAverage`, `exponentialSmoothing`, `visMovingAverage`, and `visExpSmoothing`. 
    A convenient use case for this package is to combine it with the `quantmod` library, which can provide well-formated stock price data from Yahoo Finance dataset with customized date range setting.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Imports:
    quantmod (>= 0.4.18),
    xts (>= 0.12.1),
    zoo (>= 1.8-8),
    dplyr (>= 1.0.2),
    ggplot2 (>= 3.3.2),
    rlang (>= 0.4.7),
    tibble (>= 3.0.3),
    utils
Suggests: 
    testthat (>= 3.0.0),
    knitr (>= 1.30),
    rmarkdown
Config/testthat/edition: 3

Scope

Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):
- [ ] data retrieval
- [ ] data extraction
- [ ] data munging
- [ ] data deposition
- [ ] workflow automation
- [ ] version control
- [ ] citation management and bibliometrics
- [ ] scientific software wrappers
- [ ] field and lab reproducibility tools
- [ ] database software bindings
- [ ] geospatial data
- [ ] text analysis
- [X] data visualization
Explain how and why the package falls under these categories (briefly, 1-2 sentences):

The stockAnalyzer package analyzes the data and provides visualizations for stock data, matching with the data visualization category.

Who is the target audience and what are scientific applications of this package?

The target audiences are people interested in the stock market and want to use this package to analyze and visualize stock data patterns.

Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

A similar R package called RQuantLib is used for quantitative analysis and risk management of financial assets. The difference between this package and our package is that our package involves statistical analysis of the stock data, provides data visualization and is much easier for users to implement.

(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

N/A

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Technical checks

Confirm each of the following by checking the box.

[x] I have read the guide for authors and rOpenSci packaging guide.

This package:

[x] does not violate the Terms of Service of any service it interacts with.
[ ] has a CRAN and OSI accepted license.
[x] contains a README with instructions for installing the development version.
[x] includes documentation with examples for all functions, created with roxygen2.
[x] contains a vignette with examples of its essential functions and uses.
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Package Review

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The package includes all the following forms of documentation:

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[x] Installation instructions: for the development version of package and any non-standard dependencies in README
[x] Vignette(s) demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
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For packages co-submitting to JOSS

[ ] The package has an obvious research application according to JOSS's definition

The package contains a paper.md matching JOSS's requirements with:

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[ ] A statement of need clearly stating problems the software is designed to solve and its target audience.

[ ] References: with DOIs for all those that have one (e.g. papers, datasets, software).

Functionality

[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
[x] Performance: Any performance claims of the software been confirmed.
[x] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines

Estimated hours spent reviewing: 1

[x] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Would be helpful if there was a convenience wrapper to call the view function by stock name only, eg visMovingAverage("AAPL") which would automatically download the data if it doesn't exist yet.
visMovingAverage and visExpSmoothing could both have default args set eg window = 300, col_name = "Close".
Calling exponentialSmoothing(AAPL, paste("expsmoothing", colnames(AAPL), sep="_") , 0.3) with all these args is a bit clunky, could probably simplify this so the user only needs to specify a prefix.
Could consider using an interactive plot with plotly for example. When looking at the plots I found I constantly wanted to be able to zoom in and move around.
Ability to specify periods with date ranges, eg startdate = "2021-01-03" or similar could be helpful.
Optionally, visMovingAverage could accpet a vector for the window eg c(10, 50, 200) to display multiple moving averages?

Overall these are all very minor suggestions, the package was very easy to install and use by following the documentation examples. A couple simple "convenience" type wrapper functions could make this a very fast/simple/helpful package!

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

Briefly describe any working relationship you have (had) with the package authors.
[X] As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

[X] A statement of need clearly stating problems the software is designed to solve and its target audience in README
[X] Installation instructions: for the development version of package and any non-standard dependencies in README
[X] Vignette(s) demonstrating major functionality that runs successfully locally
[X] Function Documentation: for all exported functions
[X] Examples (that run successfully locally) for all exported functions
[X] Community guidelines including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

For packages co-submitting to JOSS

[ ] The package has an obvious research application according to JOSS's definition

The package contains a paper.md matching JOSS's requirements with:

[ ] A short summary describing the high-level functionality of the software

[ ] Authors: A list of authors with their affiliations

[ ] A statement of need clearly stating problems the software is designed to solve and its target audience.

[ ] References: with DOIs for all those that have one (e.g. papers, datasets, software).

Functionality

[X] Installation: Installation succeeds as documented.
[X] Functionality: Any functional claims of the software been confirmed.
[X] Performance: Any performance claims of the software been confirmed.
[X] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[X] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines

Estimated hours spent reviewing: 1.5 hours

[X] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Could the functions in the packages have arguments that control time ranges such as start_date and end_date.
For summaryStats() function, it would be more clear when output states the min and max of the time variable.
It would be useful if there is a function that returns available symbols and their time range.
When a user finds a help document by ?movingAverage, there is no description of a unit of window argument. It would be helpful if help document states the unit of window argument such as day, week, or month.
For a clear understanding of the plot, could visualization functions includes symbol name into plot title. (e.g. "AAPL Stock Price History with Exponential Smoothing")
An argument newColname in summaryStats() function looks little bit complicated. Could function change this argument as user-friendly?

Expect the minor issues above, the package is well-made and easy to use.

Thank you @jaymegordo and @rissangs for your detailed reviews! Thanks for putting efforts on it! Good luck on the final block!

UBC-MDS / software-review-2021