title: "Library BRVM" date: "14 février,2024" output: html_document: toc: yes fig_caption: yes keep_md: yes fig_width: 8 fig_height: 6 word_document: toc: yes pdf_document: toc: yes latex_engine: lualatex always_allow_html: true
BRVM
Description {.tabset}
English
This R package provides a user-friendly interface for accessing data from the BRVM, which is a regional stock exchange serving multiple West African countries. With this package, users can easily retrieve historical stock price data, trading volumes, and other financial indicators for a variety of stocks traded on the BRVM.
The package is designed to simplify the process of gathering and analyzing financial data, making it easier for researchers, investors, and other users to extract insights and make informed decisions based on the information available. Overall, BRVM library is a valuable tool for anyone looking to gain a better understanding of the BRVM and the financial markets in West Africa.
Français
Ce package R fournit une interface conviviale pour accéder aux données de la BRVM, qui est une bourse régionale desservant plusieurs pays d'Afrique de l'Ouest. Avec ce package, les utilisateurs peuvent facilement récupérer des données historiques sur les prix des actions, les volumes de transactions et d'autres indicateurs financiers pour une variété d'actions négociées sur la BRVM.
Le package est conçu pour simplifier le processus de collecte et d'analyse de données financières, ce qui facilite la tâche des chercheurs, des investisseurs et d'autres utilisateurs pour extraire des informations et prendre des décisions éclairées en se basant sur les informations disponibles. Dans l'ensemble, notre package R est un outil précieux pour quiconque cherche à mieux comprendre la BRVM et les marchés financiers en Afrique de l'Ouest.
Installation guidelines
You can install using CRAN version
install.packages("BRVM")You can install the development version of BRVM from github with:
# github dev version
## We can use devtools
# install.packages("devtools")
devtools::install_github("Koffi-Fredysessie/BRVM")
# Or use remotes
# install.packages("remotes")
remotes::install_github("Koffi-Fredysessie/BRVM")Html version of the Readme
Since the size of the readme is huge due to the charts, you can visit the html version of the readme on RPubs
library(BRVM)The BRVM_ticker_desc() function
It receives no argument and returns BRVM tickers information such as its full name, sector and country.
# Display tickers of BRVM
tickers <- BRVM_ticker_desc()
tickersThe BRVM_index() function :
It receives no argument and returns a table of updated data (with as table header: indexes, previous closing, closing, change (%), Year to Date Change) on all the indices available on the BRVM exchange.
the_index <- BRVM_index()
the_indexThe BRVM_get(".symbol", ".from", ".to") function
This function will get the data of the companies listed on the BVRM stock exchange in Rich Bourse website. The function takes a single parameter, .symbol (which represents the "Ticker").
The function will automatically format tickers you enter in uppercase using toupper() and then ensure that the passed ticker is in a Google spreadsheet of allowed tickers.
- .symbol : A vector of symbols, like: c("BICC","XOM","SlbC") ;
- .from : A quoted start date, ie. "2020-01-01" or "2020/01/01". The date must be in ymd format "YYYY-MM-DD" or "YYYY/MM/DD" ;
- .to : A quoted end date, ie. "2022-01-31" or "2022/01/31". The date must be in ymd format "YYYY-MM-DD" or "YYYY/MM/DD".
#' Displaying data of SONATEL Senegal stock
BRVM_get(.symbol = "snts")
#> # A tibble: 246 × 6
#> Date Open High Low Close Volume
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2023-02-14 15275 15300 15275 15300 10529
#> 2 2023-02-15 15400 15400 15305 15305 7023
#> 3 2023-02-16 15350 15350 15300 15300 22423
#> 4 2023-02-17 15400 15400 15300 15300 18325
#> 5 2023-02-20 15305 15395 15305 15395 4011
#> 6 2023-02-21 15395 15400 15395 15400 6237
#> 7 2023-02-22 15400 15440 15400 15440 4015
#> 8 2023-02-23 15440 15440 15400 15400 71763
#> 9 2023-02-24 15500 15690 15500 15690 22593
#> 10 2023-02-27 15700 15945 15700 15945 47984
#> # ℹ 236 more rows
symbols <- c("BiCc","XOM","SlbC") # We use here three tickers
data_tbl <- BRVM_get(.symbol = symbols, .from = "2020-01-01", .to = Sys.Date() - 1)
# Display the first twenty observations of the table
head(data_tbl, 20)
#> # A tibble: 20 × 7
#> Date Open High Low Close Volume Ticker
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 2020-01-10 6500 6500 6500 6500 24 BICC
#> 2 2020-01-13 6370 6500 6370 6500 29 BICC
#> 3 2020-01-14 6495 6495 6495 6495 10 BICC
#> 4 2020-01-29 6010 6010 6010 6010 24 BICC
#> 5 2020-01-30 6000 6000 6000 6000 50 BICC
#> 6 2020-02-04 5800 5800 5800 5800 12 BICC
#> 7 2020-02-07 5650 5650 5650 5650 5 BICC
#> 8 2020-02-10 5500 5500 5500 5500 5 BICC
#> 9 2020-02-14 5300 5300 5300 5300 9 BICC
#> 10 2020-02-17 4910 4910 4910 4910 210 BICC
#> 11 2020-02-18 4910 4910 4910 4910 50 BICC
#> 12 2020-02-20 4895 4895 4895 4895 5 BICC
#> 13 2020-02-21 4895 4895 4890 4890 13 BICC
#> 14 2020-02-25 4525 4525 4525 4525 16 BICC
#> 15 2020-02-26 4435 4435 4430 4430 21 BICC
#> 16 2020-02-27 4345 4760 4335 4760 1809 BICC
#> 17 2020-03-03 4745 4750 4745 4750 11 BICC
#> 18 2020-03-05 4700 4700 4700 4700 5 BICC
#> 19 2020-03-06 4695 4695 4695 4695 6 BICC
#> 20 2020-03-11 4345 4450 4345 4450 135 BICC
# Display the last twenty elements of the table
tail(data_tbl, 20)
#> # A tibble: 20 × 7
#> Date Open High Low Close Volume Ticker
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 2023-12-14 88200 90000 88200 90000 4 SLBC
#> 2 2023-12-15 90000 90000 90000 90000 5 SLBC
#> 3 2023-12-18 89000 90000 89000 89000 1 SLBC
#> 4 2023-12-19 89000 89000 85000 85000 716 SLBC
#> 5 2023-12-20 79000 90000 85000 89900 10 SLBC
#> 6 2023-12-22 90000 90000 89900 90000 1 SLBC
#> 7 2023-12-26 83300 90000 83300 88495 3 SLBC
#> 8 2023-12-27 88500 88500 88495 88500 1 SLBC
#> 9 2023-12-28 83300 88500 83300 87000 13 SLBC
#> 10 2024-01-02 87000 90000 87000 90000 2 SLBC
#> 11 2024-01-04 89500 90000 89500 89500 5 SLBC
#> 12 2024-01-11 88000 89500 88000 88000 160 SLBC
#> 13 2024-01-12 88000 89500 88000 89500 11 SLBC
#> 14 2024-01-15 89500 89500 88000 88000 13 SLBC
#> 15 2024-01-16 89500 89500 88000 89500 4 SLBC
#> 16 2024-01-19 89500 89500 88050 88050 14 SLBC
#> 17 2024-01-23 88950 88950 88050 88950 5 SLBC
#> 18 2024-01-25 88935 88950 88940 88940 2 SLBC
#> 19 2024-02-09 82270 88940 82270 88500 29 SLBC
#> 20 2024-02-13 88495 88500 88495 88495 1 SLBCThe BRVM_get1("ticker ", "Period", "from", "to") function
This function will get data of the companies listed on the BVRM stock exchange through the sikafinance site.
The function takes in a single parameter of ticker and will auto-format the tickers you input into all upper case by using toupper()
- ticker : A vector of ticker, like: c("BICC","XOM","SlbC", "BRvm10");
- Period : Numeric number indicating time period. Valid entries are 0, 1, 5, 30, 91, and 365 representing respectively 'daily', 'one year', 'weekly', 'monthly', 'quarterly' and 'yearly';
- from : A quoted start date, ie. "2020-01-01" or "2020/01/01". The date must be in ymd format "YYYY-MM-DD" or "YYYY/MM/DD";
- to : A quoted end date, ie. "2022-01-31" or "2022/01/31". The date must be in ymd format "YYYY-MM-DD" or "YYYY/MM/DD"
** NB : There is a small difference between the BRVM_get and BRVM_get1 functions.
- With BRVM_get it is only possible to download tickers' daily data.
- But with BRVM_get1, you can download daily, weekly, monthly, annual tickers’ data, indices and even market capitalization.
#' Displaying data of SONATEL Senegal stock
BRVM_get1("snts")
#> # A tibble: 63 × 5
#> Date Open High Low Close
#> <date> <int> <int> <int> <int>
#> 1 2023-11-17 17095 17150 17095 17150
#> 2 2023-11-20 17160 17160 17090 17090
#> 3 2023-11-21 17090 17195 17090 17195
#> 4 2023-11-22 17000 17245 17000 17245
#> 5 2023-11-23 17000 17295 17000 17295
#> 6 2023-11-24 17200 17295 17200 17295
#> 7 2023-11-27 17000 17295 17000 17295
#> 8 2023-11-28 17295 17295 17200 17200
#> 9 2023-11-29 17200 17200 17200 17200
#> 10 2023-11-30 17195 17200 17195 17200
#> # ℹ 53 more rows
# Get daily data of all indexes
all_ind <- BRVM_get1("ALL INDEXES", Period = 0, from = "2020-01-04", to = "2023-03-24")
# display the first two tens elements of the table
head(all_ind, 20)
#> # A tibble: 20 × 7
#> Date Open High Low Close Volume Ticker
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 2022-12-26 293. 293. 293. 293. 0 BRVMAG
#> 2 2022-12-27 292. 292. 292. 292. 0 BRVMAG
#> 3 2022-12-28 285. 285. 285. 285. 0 BRVMAG
#> 4 2022-12-29 285. 285. 285. 285. 0 BRVMAG
#> 5 2022-12-30 284. 284. 284. 284. 0 BRVMAG
#> 6 2023-01-02 283. 283. 283. 283. 0 BRVMAG
#> 7 2023-01-03 281. 281. 281. 281. 0 BRVMAG
#> 8 2023-01-04 275. 275. 275. 275. 0 BRVMAG
#> 9 2023-01-05 279. 279. 279. 279. 0 BRVMAG
#> 10 2023-01-06 269. 269. 269. 269. 0 BRVMAG
#> 11 2023-01-09 276. 276. 276. 276. 0 BRVMAG
#> 12 2023-01-10 276. 276. 276. 276. 0 BRVMAG
#> 13 2023-01-11 276. 276. 276. 276. 0 BRVMAG
#> 14 2023-01-12 275. 275. 275. 275. 0 BRVMAG
#> 15 2023-01-13 275. 275. 275. 275. 0 BRVMAG
#> 16 2023-01-16 273. 273. 273. 273. 0 BRVMAG
#> 17 2023-01-17 273. 273. 273. 273. 0 BRVMAG
#> 18 2023-01-18 271. 271. 271. 271. 0 BRVMAG
#> 19 2023-01-19 281. 281. 281. 281. 0 BRVMAG
#> 20 2023-01-20 281. 281. 281. 281. 0 BRVMAG
# display the two tens of the last elements of the table
tail(all_ind, 20)
#> # A tibble: 20 × 7
#> Date Open High Low Close Volume Ticker
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 2020-02-26 4281311 4281311 4281311 4281311 0 CAPIB
#> 2 2020-02-27 4314933 4314933 4314933 4314933 0 CAPIB
#> 3 2020-02-28 4346515 4346515 4346515 4346515 0 CAPIB
#> 4 2020-03-02 4424073 4424073 4424073 4424073 0 CAPIB
#> 5 2020-03-03 4379647 4379647 4379647 4379647 0 CAPIB
#> 6 2020-03-04 4369550 4369550 4369550 4369550 0 CAPIB
#> 7 2020-03-05 4342229 4342229 4342229 4342229 0 CAPIB
#> 8 2020-03-06 4359879 4359879 4359879 4359879 0 CAPIB
#> 9 2020-03-09 4338293 4338293 4338293 4338293 0 CAPIB
#> 10 2020-03-10 4357221 4357221 4357221 4357221 0 CAPIB
#> 11 2020-03-11 4332656 4332656 4332656 4332656 0 CAPIB
#> 12 2020-03-12 4318096 4318096 4318096 4318096 0 CAPIB
#> 13 2020-03-13 4318112 4318112 4318112 4318112 0 CAPIB
#> 14 2020-03-16 4285184 4285184 4285184 4285184 0 CAPIB
#> 15 2020-03-17 4301727 4301727 4301727 4301727 0 CAPIB
#> 16 2020-03-18 4288582 4288582 4288582 4288582 0 CAPIB
#> 17 2020-03-19 4207231 4207231 4207231 4207231 0 CAPIB
#> 18 2020-03-20 4209788 4209788 4209788 4209788 0 CAPIB
#> 19 2020-03-23 4154445 4154445 4154445 4154445 0 CAPIB
#> 20 2020-03-24 4144325 4144325 4144325 4144325 0 CAPIB
# To get yearly data
yearly_data <- BRVM_get1(c("brvmtr", "BiCc", "BOAS"), Period = 365 )
# display the first two tens elements of the table
head(yearly_data, 20)
#> # A tibble: 20 × 6
#> Date Open High Low Close Ticker
#> <date> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 2004-02-19 76.8 89.2 72.9 89.2 BRVMTR
#> 2 2005-01-03 89.2 107. 70.7 104. BRVMTR
#> 3 2006-01-02 104. 158. 104. 153. BRVMTR
#> 4 2007-01-02 153. 275. 149. 249. BRVMTR
#> 5 2008-01-02 249. 386. 226. 296. BRVMTR
#> 6 2009-01-02 275. 296. 227. 236. BRVMTR
#> 7 2010-01-04 236. 259. 224. 238. BRVMTR
#> 8 2011-01-03 238. 249. 204. 239 BRVMTR
#> 9 2012-01-02 239 349. 201. 349. BRVMTR
#> 10 2013-01-02 349. 794. 339. 789. BRVMTR
#> 11 2014-01-02 789. 1213. 601. 1213. BRVMTR
#> 12 2015-01-02 1213. 1525. 653. 1525. BRVMTR
#> 13 2016-01-04 1525. 1525. 1216. 1432. BRVMTR
#> 14 2017-01-02 1432. 1433. 764. 1203. BRVMTR
#> 15 2018-01-02 1114. 1193. 966. 966. BRVMTR
#> 16 2019-06-03 403. 429. 311. 367. BRVMTR
#> 17 2020-01-01 367. 475. 292. 379. BRVMTR
#> 18 2021-01-04 376. 622. 325 622. BRVMTR
#> 19 2022-01-03 667. 667. 295. 342. BRVMTR
#> 20 2023-01-02 341. 414. 307. 331. BRVMTR
# display the two tens of the last elements of the table
tail(yearly_data, 20)
#> # A tibble: 20 × 6
#> Date Open High Low Close Ticker
#> <date> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 2016-01-04 10000 10700 8566 9890 BICC
#> 2 2017-01-05 9750 10000 6440 8490 BICC
#> 3 2018-01-02 8700 8750 3795 7900 BICC
#> 4 2019-01-04 7550 7550 3710 6800 BICC
#> 5 2020-01-01 6800 6890 2855 6680 BICC
#> 6 2021-01-04 6680 7525 4280 7400 BICC
#> 7 2022-01-03 7250 7250 5550 6850 BICC
#> 8 2023-01-02 6500 7495 5785 7490 BICC
#> 9 2024-01-04 7450 7485 6900 7445 BICC
#> 10 2014-12-10 1613 3225 1613 3225 BOAS
#> 11 2015-01-02 3370 4300 2900 3950 BOAS
#> 12 2016-01-04 3700 4101 2000 2350 BOAS
#> 13 2017-01-02 2325 3875 2035 2500 BOAS
#> 14 2018-01-02 2400 3250 1700 2020 BOAS
#> 15 2019-01-02 1900 2000 1500 1545 BOAS
#> 16 2020-01-01 1550 1700 1295 1495 BOAS
#> 17 2021-01-04 1480 2750 1340 2350 BOAS
#> 18 2022-01-03 2350 2780 2200 2450 BOAS
#> 19 2023-01-02 2580 3650 2175 3200 BOAS
#> 20 2024-01-01 3200 3400 3000 3050 BOASThe BRVM.index() function :
It receives no argument and returns the name of all indexes available on BRVM Stock Exchange.
BRVM.index()
#> [1] "BRVMAG" "BRVMC" "BRVMAS" "BRVMDI" "BRVMFI" "BRVMIN" "BRVMSP" "BRVMTR"
#> [9] "BRVMPR" "BRVMPA" "BRVM30"The BRVM_bySector(".sectors") function :
This function will take in the name of sector(s) and returns data for companies belonging to that/those sector(s)
- .sectors : A vector of sectors you wish to have returned.
# Get informations about brvm sectors like other and agriculture sectors
BRVM_bySector(.sectors = c("Other", "Agriculture"))
#> # A tibble: 6 × 8
#> Ticker `Company name` Volume `Previous price` Open Close `Change (%)` Sector
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 STAC SETAO COTE D'I… 0 855 0 855 0 Other
#> 2 PALC PALM COTE D'IV… 171 6550 6550 6800 0 Agric…
#> 3 SCRC SUCRIVOIRE COT… 321 470 470 470 -5.05 Agric…
#> 4 SICC SICOR COTE D'I… 0 3600 0 3600 0 Agric…
#> 5 SOGC SOGB COTE D'IV… 3956 3050 3050 3050 -0.97 Agric…
#> 6 SPHC SAPH COTE D'IV… 169 2245 2100 2245 -0.22 Agric…The BRVM_stock_market(".weekday") function :
This function receives as input a day of the week (working day) and returns the official quotation revews of that day.
- .weekday : A quoted date, ie. "2022-01-31" or "2022/01/31". The date must be in ymd format "YYYY-MM-DD" or "YYYY/MM/DD". Must not be a weekend or a holiday.
# The BOC of 2022-02-23
BRVM_stock_market("2022-02-23")