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Introduction
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.
For now, you can install from GitHub until it is on CRAN (It is on the way)
# 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")
Examples
First, let’s load in the BRVM package:
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() tickers
Warning: package 'kableExtra' was built under R version 4.2.3
| Ticker | Company name | Sector | Country |
|---|---|---|---|
| ABJC | SERVAIR ABIDJAN COTE D’IVOIRE | DISTRIBUTION | IVORY COAST |
| BICC | BICI COTE D’IVOIRE | FINANCE | IVORY COAST |
| BNBC | BERNABE COTE D’IVOIRE | DISTRIBUTION | IVORY COAST |
| BOAB | BANK OF AFRICA BENIN | FINANCE | BENIN |
| BOABF | BANK OF AFRICA BURKINA FASO | FINANCE | BURKINA FASO |
| BOAC | BANK OF AFRICA COTE D’IVOIRE | FINANCE | IVORY COAST |
| BOAM | BANK OF AFRICA MALI | FINANCE | MALI |
| BOAN | BANK OF AFRICA NIGER | FINANCE | NIGER |
| BOAS | BANK OF AFRICA SENEGAL | FINANCE | SENEGAL |
| CABC | SICABLE COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| CBIBF | CORIS BANK INTERNATIONAL BURKINA FASO | FINANCE | BURKINA FASO |
| CFAC | CFAO MOTORS COTE D’IVOIRE | DISTRIBUTION | IVORY COAST |
| CIEC | CIE COTE D’IVOIRE | PUBLIC SERVICE | IVORY COAST |
| ECOC | ECOBANK COTE D’IVOIRE | FINANCE | IVORY COAST |
| ETIT | Ecobank Transnational Incorporated TOGO | FINANCE | TOGO |
| FTSC | FILTISAC COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| NEIC | NEI-CEDA COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| NSBC | NSIA BANQUE COTE D’IVOIRE | FINANCE | IVORY COAST |
| NTLC | NESTLE COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| ONTBF | ONATEL BURKINA FASO | PUBLIC SERVICE | BURKINA FASO |
| ORAC | ORANGE COTE D’IVOIRE | PUBLIC SERVICE | IVORY COAST |
| ORGT | ORAGROUP TOGO | FINANCE | TOGO |
| PALC | PALM COTE D’IVOIRE | AGRICULTURE | IVORY COAST |
| PRSC | TRACTAFRIC MOTORS COTE D’IVOIRE | DISTRIBUTION | IVORY COAST |
| SAFC | SAFCA COTE D’IVOIRE | FINANCE | IVORY COAST |
| SCRC | SUCRIVOIRE COTE D’IVOIRE | AGRICULTURE | IVORY COAST |
| SDCC | SODE COTE D’IVOIRE | PUBLIC SERVICE | IVORY COAST |
| SDSC | BOLLORE TRANSPORT & LOGISTICS COTE D’IVOIRE | TRANSPORT | IVORY COAST |
| SEMC | CROWN SIEM COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| SGBC | SOCIETE GENERALE COTE D’IVOIRE | FINANCE | IVORY COAST |
| SHEC | VIVO ENERGY COTE D’IVOIRE | DISTRIBUTION | IVORY COAST |
| SIBC | SOCIETE IVOIRIENNE DE BANQUE COTE D’IVOIRE | FINANCE | IVORY COAST |
| SICC | SICOR COTE D’IVOIRE | AGRICULTURE | IVORY COAST |
| SIVC | AIR LIQUIDE COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| SLBC | SOLIBRA COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| SMBC | SMB COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| SNTS | SONATEL SENEGAL | PUBLIC SERVICE | SENEGAL |
| SOGC | SOGB COTE D’IVOIRE | AGRICULTURE | IVORY COAST |
| SPHC | SAPH COTE D’IVOIRE | AGRICULTURE | IVORY COAST |
| STAC | SETAO COTE D’IVOIRE | OTHER | IVORY COAST |
| STBC | SITAB COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| SVOC | MOVIS COTE D’IVOIRE | TRANSPORT | IVORY COAST |
| TTLC | TOTAL COTE D’IVOIRE | DISTRIBUTION | IVORY COAST |
| TTLS | TOTAL SENEGAL | DISTRIBUTION | SENEGAL |
| TTRC | TRITURAF Ste en Liquid | INDUSTRY | IVORY COAST |
| UNLC | UNILEVER COTE D’IVOIRE | INDUSTRY | IVORY COAST |
| UNXC | UNIWAX COTE D’IVOIRE | INDUSTRY | IVORY COAST |
The 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.
| Indexes | Previous closing | Closing | Change (%) | Year to Date Change |
|---|---|---|---|---|
| BRVM-30 | 99.71 | 99.75 | 0.04 | 0.00 |
| BRVM – AGRICULTURE | 281.76 | 281.25 | -0.18 | -0.66 |
| BRVM – OTHER SECTOR | 1295.58 | 1357.27 | 4.76 | -7.32 |
| BRVM – COMPOSITE | 199.37 | 199.46 | 0.05 | 0.85 |
| BRVM – DISTRIBUTION | 346.02 | 345.33 | -0.20 | 0.69 |
| BRVM – FINANCE | 74.53 | 75.03 | 0.67 | -0.66 |
| BRVM – INDUSTRY | 98.33 | 98.10 | -0.23 | 0.92 |
| BRVM – PRESTIGE | 102.61 | 102.56 | -0.05 | 0.00 |
| BRVM – PRINCIPAL | 94.56 | 94.62 | 0.06 | 0.00 |
| BRVM – PUBLIC SERVICES | 480.97 | 479.60 | -0.28 | 2.23 |
| BRVM – TRANSPORT | 345.28 | 341.70 | -1.04 | 0.35 |
The 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")
[1] "SNTS"
# A tibble: 251 × 6 Date Open High Low Close Volume <date> <dbl> <dbl> <dbl> <dbl> <dbl> 1 2022-04-06 15800 15895 15750 15800 7436 2 2022-04-07 15800 15900 15750 15900 1265 3 2022-04-08 15900 15995 15800 15900 1164 4 2022-04-11 15895 15900 15800 15800 4252 5 2022-04-12 15800 15800 15780 15800 6561 6 2022-04-13 15800 15865 15795 15850 5409 7 2022-04-14 15855 15900 15850 15900 16957 8 2022-04-15 15995 15995 15900 15900 791 9 2022-04-19 15900 15995 15895 15900 31217 10 2022-04-20 15900 15995 15895 15990 32322 # ℹ 241 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)
[1] "BICC" "SLBC"
# 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 2023-02-15 80000 80000 79000 79000 2 SLBC 2 2023-02-17 78000 78000 78000 78000 5 SLBC 3 2023-02-21 80000 80000 80000 80000 5 SLBC 4 2023-02-23 80000 80000 80000 80000 18 SLBC 5 2023-02-24 80000 80000 80000 80000 6 SLBC 6 2023-02-27 80000 80000 80000 80000 98 SLBC 7 2023-02-28 80000 80000 80000 80000 11 SLBC 8 2023-03-02 80000 80000 80000 80000 11 SLBC 9 2023-03-08 80000 80000 80000 80000 2 SLBC 10 2023-03-09 80000 80000 80000 80000 2 SLBC 11 2023-03-13 80005 80005 80000 80000 12 SLBC 12 2023-03-14 80000 80000 80000 80000 1 SLBC 13 2023-03-20 80000 80000 80000 80000 3 SLBC 14 2023-03-21 80000 80000 80000 80000 4 SLBC 15 2023-03-27 78000 80000 78000 80000 169 SLBC 16 2023-03-28 80000 80000 80000 80000 435 SLBC 17 2023-03-30 80000 80000 80000 80000 3 SLBC 18 2023-03-31 80000 80000 80000 80000 1 SLBC 19 2023-04-04 80000 86000 80000 86000 3 SLBC 20 2023-04-05 85950 86000 85950 86000 6 SLBC
The 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")
[1] "Make sure you have an active internet connection"
# Get daily data of all indexes
all_ind <- BRVM_get1("ALL INDEXES", Period = 0, from = "2020-01-04", to = "2023-03-24")
[1] "We obtained BRVM10 data from 2019-12-26 to 2023-01-04" [1] "We obtained BRVMAG data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMC data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMAS data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMDI data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMFI data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMIN data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMSP data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMTR data from 2019-12-26 to 2023-03-24" [1] "We obtained BRVMPR data from 2023-01-01 to 2023-03-24" [1] "We obtained BRVMPA data from 2023-01-04 to 2023-03-24" [1] "We obtained BRVM30 data from 2023-01-01 to 2023-03-24" [1] "We obtained CAPIB data from 2020-01-02 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 2022-12-26 169. 169. 169. 169. 0 BRVM10 2 2022-12-27 169. 169. 169. 169. 0 BRVM10 3 2022-12-28 167. 167. 167. 167. 0 BRVM10 4 2022-12-29 167. 167. 167. 167. 0 BRVM10 5 2022-12-30 166. 166. 166. 166. 0 BRVM10 6 2023-01-02 166. 166. 166. 166. 0 BRVM10 7 2023-01-03 166. 166. 166. 166. 0 BRVM10 8 2023-01-04 166. 166. 166. 166. 0 BRVM10 9 2022-09-26 163. 163. 163. 163. 0 BRVM10 10 2022-09-27 162. 162. 162. 162. 0 BRVM10 11 2022-09-28 162. 162. 162. 162. 0 BRVM10 12 2022-09-29 163. 163. 163. 163. 0 BRVM10 13 2022-09-30 164. 164. 164. 164. 0 BRVM10 14 2022-10-03 162. 162. 162. 162. 0 BRVM10 15 2022-10-04 162. 162. 162. 162. 0 BRVM10 16 2022-10-05 161. 161. 161. 161. 0 BRVM10 17 2022-10-06 161. 161. 161. 161. 0 BRVM10 18 2022-10-07 161. 161. 161. 161. 0 BRVM10 19 2022-10-10 160. 160. 160. 160. 0 BRVM10 20 2022-10-11 160. 160. 160. 160. 0 BRVM10
# 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 2003-04-11 74.0 88.6 73.6 88.6 BRVMTR 2 2004-01-02 88.6 89.2 72.9 89.2 BRVMTR 3 2005-01-03 89.2 107. 70.7 104. BRVMTR 4 2006-01-02 104. 158. 104. 153. BRVMTR 5 2007-01-02 153. 275. 149. 249. BRVMTR 6 2008-01-02 249. 386. 226. 296. BRVMTR 7 2009-01-02 275. 296. 227. 236. BRVMTR 8 2010-01-04 236. 259. 224. 238. BRVMTR 9 2011-01-03 238. 249. 204. 239 BRVMTR 10 2012-01-02 239 349. 201. 349. BRVMTR 11 2013-01-02 349. 794. 339. 789. BRVMTR 12 2014-01-02 789. 1213. 601. 1213. BRVMTR 13 2015-01-02 1213. 1525. 653. 1525. BRVMTR 14 2016-01-04 1525. 1525. 1216. 1432. BRVMTR 15 2017-01-02 1432. 1433. 764. 1203. BRVMTR 16 2018-01-02 1114. 1193. 966. 966. BRVMTR 17 2019-06-03 403. 429. 311. 367. BRVMTR 18 2020-01-01 367. 475. 292. 379. BRVMTR 19 2021-01-04 376. 622. 325 622. BRVMTR 20 2022-01-03 667. 667. 295. 342. 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 2014-01-02 5650 7848 5650 7800 BICC 2 2015-01-02 8385 10750 7800 10100 BICC 3 2016-01-04 10000 10700 8566 9890 BICC 4 2017-01-05 9750 10000 6440 8490 BICC 5 2018-01-02 8700 8750 3795 7900 BICC 6 2019-01-04 7550 7550 3710 6800 BICC 7 2020-01-01 6800 6890 2855 6680 BICC 8 2021-01-04 6680 7525 4280 7400 BICC 9 2022-01-03 7250 7250 5550 6850 BICC 10 2023-01-02 6500 6850 5785 6275 BICC 11 2014-12-10 1613 3225 1613 3225 BOAS 12 2015-01-02 3370 4300 2900 3950 BOAS 13 2016-01-04 3700 4101 2000 2350 BOAS 14 2017-01-02 2325 3875 2035 2500 BOAS 15 2018-01-02 2400 3250 1700 2020 BOAS 16 2019-01-02 1900 2000 1500 1545 BOAS 17 2020-01-01 1550 1700 1295 1495 BOAS 18 2021-01-04 1480 2750 1340 2350 BOAS 19 2022-01-03 2350 2780 2200 2450 BOAS 20 2023-01-02 2580 2585 2175 2265 BOAS
The 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"
Authors :
Creator : Koffi Frederic Sessie
cph (Copyright Holder) : Koffi Frederic Sessie
License : MIT 2023, BRVM authors. All rights reserved.
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