title | author | date | output | ||||||||||||||||||||||||
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Library Euronext |
Koffi Frederic SESSIE |
19 février,2024 |
|
Unlock the power of financial data from the Euronext stock exchange with the Euronext R package. Dive into the world of stocks, indices, funds, ETFs, and bonds, and harness the convenience of a user-friendly interface for seamless data retrieval. Whether you're a researcher, investor, or financial enthusiast, this package provides a valuable resource for accessing and analyzing historical data, share prices, trading volumes, and more.
Please note that the Euronext R package is a tool designed to access and retrieve public financial information from the Euronext stock exchange. The data returned by the Euronext R package originates from Euronext, and the package author is not the source of this data. All information is derived from the public domain, and users are advised to refer to the official Euronext website for specific data needs.
Get in touch with the Euronext package and elevate your understanding of financial markets through the lens of R.
The Euronext R Package is a powerful tool for accessing and retrieving financial information from the Euronext stock exchange. Whether you are interested in stocks, indexes, funds, ETFs, or bonds, this package provides a convenient interface to gather essential data for analysis and decision-making in the financial domain. With user-friendly functionalities, it simplifies the process of collecting historical data on share prices, trading volumes, and other financial indicators. Researchers, investors, and other users can extract valuable insights and make informed decisions based on the comprehensive information available. In essence, the 'Euronext' library is a valuable asset for those seeking a deeper understanding of Euronext and the financial markets in Europe.
Le package R Euronext est un outil puissant pour accéder et récupérer des informations financières de la bourse Euronext. Que vous soyez intéressé par les actions, les indices, les fonds, les ETF ou les obligations, ce package offre une interface pratique pour collecter des données essentielles pour l'analyse et la prise de décision dans le domaine financier. Avec des fonctionnalités conviviales, il simplifie le processus de collecte de données historiques sur les prix des actions, les volumes de transactions et d'autres indicateurs financiers. Les chercheurs, les investisseurs et d'autres utilisateurs peuvent extraire des informations précieuses et prendre des décisions éclairées en se basant sur les informations complètes disponibles. En somme, la bibliothèque 'Euronext' est un atout précieux pour ceux qui cherchent à approfondir leur compréhension d'Euronext et des marchés financiers en Europe.
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
You can install the development version of EURONEXT from github with:
# github dev version
## We can use devtools
# Install the development version from GitHub
devtools::install_github("Fredysessie/Euronext")
# Or use remotes
# install.packages("remotes")
remotes::install_github("Fredysessie/Euronext")
To better utilize the various functions of the 'Euronext' package, it is crucial to provide accurate information (such as ticker Name, ISIN, Symbol, or DNA) to the functions.
This function retrieves the profile of a given ticker - Equity, Index, Fund, ETF, or Bond - listed on the Euronext exchange based on its ticker Name, ISIN, Symbol, or DNA. It returns a list with details such as Name, ISIN, Symbol, and DNA information. It receives two (2) parameters:
- 'ticker' : A character string representing the company's ticker Name, ISIN, Symbol or DNA,
- 'stock_type' : The type of the ticker: 'Eq_Ind' for Stocks and Indexes, 'Fund' or "F" for Fund tickers, 'Bond' or "B" for Bond tickers, and 'Etfs' or "E" for EFTs.
Example 1.a : Retrieve the profile (characteristics) of a specified Equity, Index, Fund, ETF, or Bond listed on Euronext.
Please refer to the respective functions EN_GetISIN(), EN_GetISIN_Etf(), EN_GetISIN_F(), and EN_GetISIN_B() if you wish to obtain the DNA of a giving Equity or Index, ETF, Fund, and Bond listed on Euronext (retrieving DNA is useful in case you decide to use 'escape = TRUE' option).
# Note: For Equity, Index, Fund, and ETF, provide the giving Symbol, ISIN, Name, or DNA for best results, but for a Bond, provide its DNA and sometimes its Name for best results because a company or country can issue more than one Bond.
## Equities
# Example a : '3D SYSTEMS CORP' equity
EN_GetProfile("4ddd") # By providing Symbol
#> $Name
#> [1] "3D SYSTEMS CORP"
#>
#> $ISIN
#> [1] "US88554D2053"
#>
#> $DNA
#> [1] "US88554D2053-ETLX"
#>
#> $Symbol
#> [1] "4DDD"
# Example b : 'ALFEN' equity
EN_GetProfile("NL0012817175") # By providing ISIN
#> $Name
#> [1] "ALFEN"
#>
#> $ISIN
#> [1] "NL0012817175"
#>
#> $DNA
#> [1] "NL0012817175-XAMS"
#>
#> $Symbol
#> [1] "ALFEN"
# Example c : 'LES HOTELS BAVEREZ' equity
EN_GetProfile("LES HOTELS BAVEREZ") # By providing Name
#> $Name
#> [1] "LES HOTELS BAVEREZ"
#>
#> $ISIN
#> [1] "FR0007080254"
#>
#> $DNA
#> [1] "FR0007080254-ALXP"
#>
#> $Symbol
#> [1] "ALLHB"
# Example d : 'BE SEMICONDUCTOR' equity
EN_GetProfile("NL0012866412-XAMS") # By providing DNA
#> $Name
#> [1] "BE SEMICONDUCTOR"
#>
#> $ISIN
#> [1] "NL0012866412"
#>
#> $DNA
#> [1] "NL0012866412-XAMS"
#>
#> $Symbol
#> [1] "BESI"
## Indices
# Example a : 'AEX CONS STAPL GR' Index
EN_GetProfile("NLCSG") # By providing Symbol
#> $Name
#> [1] "AEX CONS STAPL GR"
#>
#> $ISIN
#> [1] "QS0011225420"
#>
#> $DNA
#> [1] "QS0011225420-XAMS"
#>
#> $Symbol
#> [1] "NLCSG"
# Example b : 'AEX All-Share Index' Index
EN_GetProfile("NL0000249100") # By providing ISIN
#> $Name
#> [1] "AEX ALL-SHARE"
#>
#> $ISIN
#> [1] "NL0000249100"
#>
#> $DNA
#> [1] "NL0000249100-XAMS"
#>
#> $Symbol
#> [1] "AAX"
# Example c : 'Euronext Core Europe 30 EW Decrement 5% NR' Index
EN_GetProfile("EN CE EW30 D 5% NR") # By providing Name
#> $Name
#> [1] "EN CE EW30 D 5% NR"
#>
#> $ISIN
#> [1] "NL0012483929"
#>
#> $DNA
#> [1] "NL0012483929-XAMS"
#>
#> $Symbol
#> [1] "COR30"
# Example d : 'SBF 120 NR' Index
EN_GetProfile("QS0011131842-XPAR") # By providing DNA
#> $Name
#> [1] "SBF 120 NR"
#>
#> $ISIN
#> [1] "QS0011131842"
#>
#> $DNA
#> [1] "QS0011131842-XPAR"
#>
#> $Symbol
#> [1] "PX4NR"
## ETFs
# Example a : 'Asia IG Corp US A' Etf
EN_GetProfile("$Asia IG Corp US A", stock_type = 'E') # By providing Name
#> $Name
#> [1] "$ASIA IG CORP US A"
#>
#> $ISIN
#> [1] "IE0007G78AC4"
#>
#> $DNA
#> [1] "IE0007G78AC4-XAMS"
#>
#> $Symbol
#> [1] "ASIG"
# Example b : '1X MSFT' Etf
EN_GetProfile("MSFT", stock_type = 'E') # By providing Symbol
#> $Name
#> [1] "1X MSFT"
#>
#> $ISIN
#> [1] "XS2337100320"
#>
#> $DNA
#> [1] "XS2337100320-XAMS"
#>
#> $Symbol
#> [1] "MSFT"
# Example c : '3X LONG COINBASE' Etf
EN_GetProfile("XS2399367254", stock_type = 'E') # By providing ISIN of 3X LONG COINBASE
#> $Name
#> [1] "3X LONG COINBASE"
#>
#> $ISIN
#> [1] "XS2399367254"
#>
#> $DNA
#> [1] "XS2399367254-XAMS"
#>
#> $Symbol
#> [1] "3CON"
# Example d : '3X PLTR' Etf
EN_GetProfile("XS2663694680-XAMS", stock_type = 'E') # By providing DNA
#> $Name
#> [1] "3X PLTR"
#>
#> $ISIN
#> [1] "XS2663694680"
#>
#> $DNA
#> [1] "XS2663694680-XAMS"
#>
#> $Symbol
#> [1] "3PLT"
# Funds
# Example a : 'ACOMEA PERFORMANCE' Fund
EN_GetProfile("ACAPER", stock_type = 'F') # By providing Symbol
#> $Name
#> [1] "ACOMEA PERFORMANCE"
#>
#> $ISIN
#> [1] "IT0005090912"
#>
#> $DNA
#> [1] "IT0005090912-ATFX"
#>
#> $Symbol
#> [1] "ACAPER"
# Example b : 'BNP ESGNL' Fund
EN_GetProfile("BNP ESGNL", stock_type = 'F') # By providing Name
#> $Name
#> [1] "BNP ESGNL"
#>
#> $ISIN
#> [1] "NL0012727432"
#>
#> $DNA
#> [1] "NL0012727432-XAMS"
#>
#> $Symbol
#> [1] "ESGNL"
# Example c : 'SWIF2' Fund
EN_GetProfile("NL0015000W40", stock_type = 'F') # By providing ISIN of SWIF2
#> $Name
#> [1] "SWIF2"
#>
#> $ISIN
#> [1] "NL0015000W40"
#>
#> $DNA
#> [1] "NL0015000W40-XAMS"
#>
#> $Symbol
#> [1] "SWIF2"
# Example d : 'GOLDMAN SACHS PARAPLUFONDS 2 N' Fund
EN_GetProfile("NL0000293181-XAMS", stock_type = 'F') # By providing DNA of GSDM5
#> $Name
#> [1] "GS DYN MIX FD V"
#>
#> $ISIN
#> [1] "NL0000293181"
#>
#> $DNA
#> [1] "NL0000293181-XAMS"
#>
#> $Symbol
#> [1] "GSDM5"
# Examples for Bonds
# Example a: 'A2A SLB TF 0,625%' Bond
EN_GetProfile("XS2364001078-XMOT", stock_type = 'B') # By providing DNA
#> $Name
#> [1] "A2A SLB TF 0,625%"
#>
#> $ISIN
#> [1] "IT0005386724"
#>
#> $DNA
#> [1] "XS2364001078-XMOT"
#>
#> $Issuer
#> [1] "A2A S.p.A."
# Example b: 'AAB1.50%30SEP30' Bond
EN_GetProfile("AAB1.50%30SEP30", stock_type = 'B') # By providing Name
#> $Name
#> [1] "AAB1.50%30SEP30"
#>
#> $ISIN
#> [1] "IT0005386724"
#>
#> $DNA
#> [1] "XS1298431799-XAMS"
#>
#> $Issuer
#> [1] "ABN AMRO BANK N.V."
This function retrieves the update information of a company listed on the Euronext exchange based on its ticker symbol. It returns a table with details such as its real Name, ISIN, Last traded Price, Date of last update, and other relevant informations.
Inputs :
- ticker A character string representing the company's ticker, name, or ISIN.
- stock_type The type of the ticker: 'Eq_Ind' for Stocks and Indexes, 'Fund' or "F" for Fund tickers,'Bond' or "B" for Bond tickers, and 'Etfs' or "E" for EFTs.
- escape Boolean, either TRUE or FALSE. If escape is True, it means you're providing the DNA (ISIN-Market identifier) directly. Giving T to escape is helpful to avoid time-consuming operations; otherwise, F means you need to provide the Ticker symbol, name, or ISIN and the type of market to which it belongs.
# Retrieve news for the equity "AALBERTS N.V." using its DNA
equity_news <- EN_Get_News("NL0000852564-XAMS", escape = TRUE)
print(equity_news)
Information | Detail |
---|---|
Name | AALBERTS N.V. |
Belongs to | Euronext Amsterdam |
ISIN | NL0000852564 |
Type | Stock |
Last traded Price | 37.25 |
Date of last update | 16/02/2024 - 17:35 CET |
Since Open | +0.16 (+0.43%) |
Since Previous Close | +0.47 (+1.28%) |
Valuation Close | 37.25 |
Best Bid | 36.92 |
Best Ask | 37.50 |
# Retrieve news for the index "AEX All-Share Index GR" using its symbol
index_news <- EN_Get_News("QS0011224977-XAMS", escape = TRUE)
print(index_news)
Information | Detail |
---|---|
Name | AEX All-Share Index GR |
Belongs to | Euronext Amsterdam |
ISIN | QS0011224977 |
Type | Index |
Last level | 4,552.24 |
Date of last update | 16/02/2024 - 18:05 CET |
Since Open | +44.24 (+0.98%) |
Since Previous Close | +44.59 (+0.99%) |
# Retrieve news for the bond "AAB0.45%12DEC2036" using its DNA
bond_news <- EN_Get_News("XS2093705064-XAMS", escape = TRUE)
print(bond_news)
Information | Detail |
---|---|
Name | AAB0.45%12DEC2036 |
Belongs to | Euronext Amsterdam |
ISIN | XS2093705064 |
Type | Bond |
Valuation Close | 100.00 |
This function receives as input stock_choice and then retrieves a list of companies listed on the provided Euronext stock exchanges, filtered by the initial letter of their names. It provides information such as the company name, ticker symbol, ISIN code, market, last closing price, percentage change, and a link to the company's details on the Euronext website.
- stock_choice A character string specifying the stock exchange. Options include "A" or "Amsterdam," "B" or "Brussels," "D" or "Dublin", "L" or "Lisbon," "M" or "Milan," "P" or "Paris," and "O" or "Oslo."
# The columns names of the initial dataframe is c("Date", "Name", "Ticker", "Code_ISIN", "Market", "Last_price", "Percentage change (in %)", "URL", "Ticker_adn")
# So I will only display columns "Name", "Ticker", "Code_ISIN", "Market", "Last_price" and "Percentage change (in %)"
# For Amsterdam Stock
a_result_df <- EN_Stocks_List("A")
head(a_result_df)[,c(2:6)]
Name | Ticker | Code_ISIN | Market | Last_price |
---|---|---|---|---|
AALBERTS NV | AALB | NL0000852564 | XAMS | €37.25 |
ABN AMRO BANK N.V. | ABN | NL0011540547 | XAMS | €14.985 |
ACCSYS | AXS | GB00BQQFX454 | XAMS | €0.645 |
ACOMO | ACOMO | NL0000313286 | XAMS | €17.94 |
ADUX | ADUX | FR0012821890 | XPAR, XAMS | €1.34 |
ADYEN | ADYEN | NL0012969182 | XAMS | €1 |
# For Brussels Stock
b_result_df <- EN_Stocks_List("B")[,c(2:6)]
tail(b_result_df)
Name | Ticker | Code_ISIN | Market | Last_price | |
---|---|---|---|---|---|
137 | WDP | WDP | BE0974349814 | XBRU, XAMS | €25.76 |
138 | WERELDHAVE BELGIUM | WEHB | BE0003724383 | XBRU | €47.60 |
139 | WHAT | WHATS | BE0003573814 | XBRU | €58.60 |
140 | WHITESTONE GROUP | ROCK | BE0974401334 | ALXB | €11.50 |
141 | XIOR | XIOR | BE0974288202 | XBRU | €26.15 |
142 | ZENOBE GRAMME CERT | ZEN | BE0003809267 | XBRU | €180.00 |
# For Paris Stock
p_result_df <- EN_Stocks_List("P")[,c(2:6)]
head(p_result_df)
Name | Ticker | Code_ISIN | Market | Last_price |
---|---|---|---|---|
1000MERCIS | ALMIL | FR0010285965 | ALXP | €26.40 |
2CRSI | AL2SI | FR0013341781 | ALXP | €4.83 |
A.S.T. GROUPE | ALAST | FR0000076887 | ALXP | €0.918 |
AB SCIENCE | AB | FR0010557264 | XPAR | €3.585 |
ABC ARBITRAGE | ABCA | FR0004040608 | XPAR | €3.995 |
ABEO | ABEO | FR0013185857 | XPAR | €13.45 |
# For Lisbon Stock
l_result_df <- EN_Stocks_List("L")[,c(2:6)]
head(l_result_df)
Name | Ticker | Code_ISIN | Market | Last_price |
---|---|---|---|---|
AGUAS DA CURIA | CUR | PTCUR0AP0000 | ENXL | €1.17 |
ALTRI SGPS | ALTR | PTALT0AE0002 | XLIS | €4.524 |
ATRIUM BIRE SIGI | MLATR | PTTBI0AM0006 | ENXL | NANA |
B.COM.PORTUGUES | BCP | PTBCP0AM0015 | XLIS | €0.2655 |
BENFICA | SLBEN | PTSLB0AM0010 | XLIS | €2.82 |
COFINA,SGPS | CFN | PTCFN0AE0003 | XLIS | €0.418 |
# For Milan Stock
m_result_df <- EN_Stocks_List("M")[,c(2:6)] # For Milan Stock
tail(m_result_df)
Name | Ticker | Code_ISIN | Market | Last_price | |
---|---|---|---|---|---|
1905 | ZOETIS | 4ZTS | US98978V1035 | ETLX | €175.85 |
1906 | ZOETIS | 2ZTS | US98978V1035 | MTAH | €173.20 |
1907 | ZOOM VIDEO COMM | 4ZM | US98980L1017 | ETLX | €59.43 |
1908 | ZOOM VIDEO COMM | 1ZM | US98980L1017 | BGEM | €58.78 |
1909 | ZOOM VIDEO COMM | 2ZM | US98980L1017 | MTAH | €64.31 |
1910 | ZUCCHI | ZUC | IT0005395071 | MTAA | €2.05 |
# For Dublin Stock
d_result_df <- EN_Stocks_List("D")[,c(2:6)]
tail(d_result_df)
Name | Ticker | Code_ISIN | Market | Last_price | |
---|---|---|---|---|---|
28 | ORIGIN ENT. PLC | OIZ | IE00B1WV4493 | XESM | €3.27 |
29 | OVOCA BIO PLC | OVXA | IE00B4XVDC01 | XESM | €0.01 |
30 | PERM. TSB GP. HOLD | PTSB | IE00BWB8X525 | XMSM | €1.65 |
31 | RYANAIR HOLD. PLC | RYA | IE00BYTBXV33 | XMSM | €20.20 |
32 | SMURFIT KAPPA GP | SK3 | IE00B1RR8406 | XMSM | €37.98 |
33 | UNIPHAR PLC | UPR | IE00BJ5FQX74 | XESM | €2.885 |
# For Oslo Stock
o_result_df <- EN_Stocks_List("O")[,c(2:6)]
head(o_result_df, 10)
Name | Ticker | Code_ISIN | Market | Last_price |
---|---|---|---|---|
AALBERTS NV | AALB | NL0000852564 | XAMS | €37.25 |
ABN AMRO BANK N.V. | ABN | NL0011540547 | XAMS | €14.985 |
ACCSYS | AXS | GB00BQQFX454 | XAMS | €0.645 |
ACOMO | ACOMO | NL0000313286 | XAMS | €17.94 |
ADUX | ADUX | FR0012821890 | XPAR, XAMS | €1.34 |
ADYEN | ADYEN | NL0012969182 | XAMS | €1 |
# Retrieve the ISIN for a company with ticker "abca"
EN_P_Ticker_adn("abca")
#> [1] "FR0004040608-XPAR"
# Example result for a valid ticker "AAA"
result <- EN_P_Ticker_adn("AAA")
print(result)
#> [1] "FR0000062465-XPAR"
# Example for a non-existing ticker "afsf"
print(EN_P_Ticker_adn("afsf")) # Ticker is not existing
#> [1] "Ticker not found"
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2023 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:07 CET","16 Feb 2024 16:30 CET","05 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","06 Dec 2023 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 10:18 CET","16 Feb 2024 15:04 CET","16 Feb 2024 17:35 CET","16 Feb 2024 14:40 CET","16 Feb 2024 17:26 CET","15 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","05 Feb 2024 16:30 CET","27 Feb 2023 16:30 CET","16 Feb 2024 16:30 CET","17 Nov 2022 01:00 CET","25 Sep 2023 11:30 CEST","15 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","12 Feb 2024 11:30 CET","16 Feb 2024 16:38 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 14:16 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:29 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 09:00 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 15:47 CET","16 Feb 2024 17:04 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","15 Feb 2024 11:30 CET","16 Feb 2024 17:29 CET","15 Sep 2023 09:00 CEST","07 Feb 2024 10:43 CET","09 Nov 2023 09:00 CET","16 Feb 2024 14:51 CET","05 Feb 2024 11:30 CET","16 Feb 2024 16:58 CET","16 Feb 2024 17:37 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:30 CET","12 Dec 2023 10:23 CET","16 Feb 2024 17:28 CET","16 Feb 2024 17:29 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","30 Jan 2024 11:30 CET","16 Feb 2024 16:41 CET","16 Feb 2024 17:07 CET","16 Feb 2024 16:32 CET","16 Feb 2024 17:35 CET","15 Feb 2024 16:30 CET","16 Feb 2024 17:29 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","29 Jan 2024 13:32 CET","30 Aug 2023 16:30 CEST","16 Sep 2022 16:30 CEST","16 Feb 2024 17:18 CET","21 Dec 2023 11:30 CET","13 Feb 2024 16:30 CET","28 Sep 2022 11:30 CEST","21 Dec 2016 15:00 CET","16 Feb 2024 17:35 CET","16 Feb 2024 15:32 CET","16 Feb 2024 17:35 CET","16 Feb 2024 09:13 CET","16 Feb 2024 16:30 CET","16 Feb 2024 16:30 CET","15 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","13 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET"," ","13 Sep 2023 16:30 CEST","16 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:38 CET","19 Jan 2024 09:00 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:48 CET","16 Feb 2024 16:41 CET","30 Jan 2024 11:30 CET","16 Feb 2024 17:14 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","28 Sep 2023 17:07 CEST","16 Feb 2024 17:36 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","13 Feb 2024 16:30 CET","14 Dec 2022 09:00 CET","16 Feb 2024 17:35 CET","07 Feb 2024 16:20 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","02 Nov 2023 16:30 CET"," ","16 Feb 2024 17:36 CET","16 Feb 2024 16:30 CET","11 Aug 2021 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CET","16 Feb 2024 17:29 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:28 CET","16 Feb 2024 17:35 CET","24 May 2022 11:30 CEST","12 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:30 CET","16 Jan 2024 11:30 CET","31 Jan 2024 16:30 CET","16 Feb 2024 11:30 CET","16 Feb 2024 12:27 CET","15 Feb 2024 16:58 CET","16 Feb 2024 16:52 CET","16 Feb 2024 16:55 CET","16 Feb 2024 11:15 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 14:11 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:10 CET","16 Feb 2024 17:35 CET","15 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET"," ","11 Sep 2023 16:30 CEST"," ","16 Feb 2024 17:35 CET","16 Apr 2021 02:00 CEST","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 13:00 CET","16 Feb 2024 15:48 CET","16 Feb 2024 16:44 CET","16 Feb 2024 17:21 CET","17 Jan 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","14 Feb 2024 11:32 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:25 CET","16 Feb 2024 16:30 CET","18 Mar 2013 15:00 CET","16 Feb 2024 17:26 CET","16 Feb 2024 09:00 CET","16 Feb 2024 14:14 CET","24 Dec 2020 11:30 CET","16 Feb 2024 17:35 CET","23 May 2022 11:30 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 16:58 CET","16 Feb 2024 16:45 CET","16 Feb 2024 09:00 CET","16 Feb 2024 16:11 CET","16 Feb 2024 17:35 CET","30 Sep 2020 02:00 CEST","16 Feb 2024 17:38 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:25 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","16 Feb 2024 16:30 CET","13 Feb 2024 11:30 CET","16 Feb 2024 17:29 CET","02 Feb 2024 11:30 CET","23 Jan 2024 16:30 CET","16 Feb 2024 17:22 CET","16 Feb 2024 10:59 CET","17 Oct 2023 16:30 CEST","31 Jan 2024 11:30 CET","15 Feb 2024 16:30 CET","15 Feb 2024 16:30 CET","24 Jan 2024 11:30 CET","16 Feb 2024 16:54 CET","16 Feb 2024 17:35 CET","09 Feb 2024 11:30 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:43 CET","20 May 2022 16:30 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 13:42 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","09 Feb 2024 16:30 CET","16 Feb 2024 10:14 CET","31 Aug 2021 02:00 CEST","16 Feb 2024 17:17 CET","06 Oct 2023 09:00 CEST","01 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","08 Jun 2021 11:30 CEST","16 Feb 2024 11:30 CET","16 Feb 2024 16:40 CET","16 Feb 2024 17:22 CET","16 Feb 2024 17:22 CET","04 Jan 2024 11:30 CET","16 Feb 2024 11:30 CET","05 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","08 Apr 2021 02:00 CEST","06 Apr 2020 02:00 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","08 Nov 2023 11:30 CET","12 Feb 2024 16:30 CET","16 Feb 2024 17:36 CET","14 Aug 2023 11:30 CEST","16 Feb 2024 17:35 CET","12 Feb 2024 13:36 CET","16 Feb 2024 17:19 CET","16 Feb 2024 17:35 CET","16 Feb 2024 15:36 CET","05 Aug 2019 02:00 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 09:28 CET","16 Feb 2024 16:30 CET","25 Oct 2023 16:30 CEST","16 Feb 2024 09:00 CET","16 Feb 2024 14:48 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","23 Jan 2024 11:48 CET","28 Dec 2023 13:14 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:36 CET","16 Feb 2024 17:22 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 09:00 CET","16 Feb 2024 13:49 CET","16 Feb 2024 17:37 CET","03 Jul 2023 09:00 CEST","16 Feb 2024 16:35 CET","16 Feb 2024 16:15 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:33 CET","16 Feb 2024 15:41 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:25 CET","16 Feb 2024 17:35 CET"," ","16 Feb 2024 17:38 CET","16 Feb 2024 16:03 CET","15 Feb 2024 16:30 CET","16 Feb 2024 17:38 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:29 CET","09 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","08 Feb 2024 16:30 CET","16 Feb 2024 16:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:37 CET","16 Feb 2024 16:30 CET","16 Feb 2024 09:00 CET","16 Feb 2024 17:35 CET","14 Feb 2024 11:30 CET","13 Feb 2024 11:30 CET","14 Feb 2024 11:30 CET","08 Dec 2023 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","27 Jan 2020 11:30 CET","16 Feb 2024 15:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 14:15 CET"," ","16 Feb 2024 17:25 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:17 CET","16 Feb 2024 13:04 CET","18 Jan 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","28 Nov 2012 10:24 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","02 Jul 2021 02:00 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","15 Jan 2024 11:38 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","30 Jan 2024 11:30 CET","16 Feb 2024 17:35 CET","15 Feb 2024 16:24 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:37 CET","16 Feb 2024 16:19 CET","16 Feb 2024 11:30 CET","16 Feb 2024 16:51 CET","16 Feb 2024 17:35 CET","16 Feb 2024 14:29 CET","16 Feb 2024 11:32 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","15 Jan 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:37 CET","16 Feb 2024 17:16 CET","02 Jan 2024 13:59 CET","16 Feb 2024 17:29 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:36 CET","16 Feb 2024 16:58 CET","16 Feb 2024 17:39 CET","16 Feb 2024 16:48 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:37 CET","16 Feb 2024 17:29 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","27 Sep 2023 16:30 CEST","16 Feb 2024 17:29 CET","16 Feb 2024 16:45 CET","16 Feb 2024 13:24 CET","16 Feb 2024 17:35 CET","09 Feb 2024 11:30 CET","16 Feb 2024 17:10 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","29 Mar 2023 02:00 CEST","16 Feb 2024 17:13 CET","16 Feb 2024 15:23 CET","16 Feb 2024 16:38 CET","16 Feb 2024 15:19 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:36 CET","16 Feb 2024 17:27 CET","30 Jul 2020 02:00 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 14:12 CET","03 Nov 2023 16:30 CET","16 Feb 2024 17:38 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:10 CET","16 Feb 2024 15:30 CET","16 Feb 2024 17:35 CET","12 Feb 2024 11:30 CET","16 Feb 2024 13:27 CET","16 Feb 2024 17:25 CET","14 Feb 2024 11:30 CET","18 Jan 2024 16:30 CET","16 Feb 2024 12:56 CET","16 Feb 2024 17:03 CET","16 Feb 2024 15:06 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","09 Jun 2022 16:30 CEST","07 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:19 CET","16 Feb 2024 17:35 CET","17 Jan 2024 16:30 CET","16 Feb 2024 16:30 CET","16 Feb 2024 14:17 CET","14 Feb 2024 11:13 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","30 Jan 2024 17:35 CET","15 Feb 2024 16:37 CET","16 Feb 2024 13:55 CET","14 Nov 2023 15:29 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:39 CET","16 Feb 2024 17:09 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:54 CET","16 Feb 2024 14:14 CET","16 Feb 2024 09:00 CET","16 Feb 2024 16:59 CET","15 Feb 2024 17:25 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:16 CET","16 Feb 2024 17:12 CET","07 Nov 2023 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 09:00 CET","16 Feb 2024 17:35 CET","16 Feb 2024 15:14 CET","16 Feb 2024 09:00 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","29 Jun 2021 02:00 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:29 CET","16 Feb 2024 17:35 CET","02 Nov 2022 11:30 CET","15 Feb 2024 17:29 CET","16 Feb 2024 17:26 CET","16 Feb 2024 17:10 CET","18 Apr 2023 16:45 CEST","16 Feb 2024 13:46 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:02 CET","16 Feb 2024 17:35 CET","14 Jun 2022 02:00 CEST","16 Feb 2024 17:37 CET"," ","16 Feb 2024 14:52 CET","16 Feb 2024 16:50 CET","16 Feb 2024 17:36 CET","14 Feb 2024 11:30 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:09 CET","29 Jan 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:37 CET","24 Mar 2023 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","07 Apr 2021 13:45 CEST","21 Dec 2023 09:29 CET","25 Mar 2009 01:00 CET","16 Feb 2024 16:30 CET","05 Aug 2016 15:00 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","16 Feb 2024 16:43 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:21 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:25 CET","16 Feb 2024 17:35 CET","22 Mar 2021 16:30 CET","13 Nov 2019 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 15:46 CET","16 Feb 2024 16:30 CET","27 Dec 2016 15:30 CET","02 Jan 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 15:01 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","16 Feb 2024 16:07 CET","16 Feb 2024 17:36 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:26 CET","07 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:37 CET","16 Feb 2024 14:07 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 14:17 CET","16 Feb 2024 13:59 CET"," "," ","02 Jan 2024 16:30 CET","13 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 09:01 CET","05 Jan 2024 12:47 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:38 CET","16 Feb 2024 11:30 CET","29 Dec 2023 13:45 CET","16 Feb 2024 16:58 CET","14 Dec 2023 13:15 CET","16 Feb 2024 17:35 CET"," ","16 Feb 2024 17:14 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:39 CET","16 Nov 2023 17:35 CET","16 Feb 2024 16:19 CET","16 Feb 2024 16:07 CET","16 Feb 2024 17:21 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","15 Feb 2024 10:30 CET","16 Feb 2024 17:28 CET","29 Aug 2022 16:30 CEST","16 Feb 2024 16:51 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:28 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","07 Feb 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","13 Feb 2024 16:30 CET","13 Feb 2024 11:30 CET","07 Feb 2024 16:30 CET","15 Feb 2024 13:57 CET","15 Feb 2024 16:30 CET","16 Feb 2024 11:16 CET","16 Feb 2024 17:35 CET","12 Feb 2024 16:30 CET","16 Feb 2024 11:30 CET","16 Feb 2024 17:38 CET","15 Feb 2024 11:30 CET","16 Feb 2024 13:04 CET","16 Feb 2024 09:00 CET","16 Feb 2024 15:07 CET","16 Feb 2024 09:40 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:21 CET","16 Feb 2024 17:35 CET"," ","16 Feb 2024 17:35 CET","16 Dec 2021 01:00 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:54 CET","16 Feb 2024 16:30 CET","16 Feb 2024 17:20 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","12 Sep 2023 16:30 CEST","16 Feb 2024 17:35 CET","31 Jan 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:37 CET","16 Feb 2024 11:34 CET","16 Feb 2024 17:35 CET","14 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 12:10 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:27 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:22 CET","16 Feb 2024 14:53 CET","30 Jul 2020 02:00 CEST","16 Feb 2024 17:39 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 16:59 CET","11 Dec 2023 11:30 CET","16 Feb 2024 16:54 CET","16 Feb 2024 11:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 11:30 CET","25 Oct 2019 11:30 CEST","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","26 Jan 2024 16:30 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:35 CET","16 Feb 2024 17:27 CET","15 Feb 2024 16:30 CET","04 Aug 2015 16:20 CEST"]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th>Name<\/th>\n <th>Ticker<\/th>\n <th>Code_ISIN<\/th>\n <th>Market<\/th>\n <th>Last_price<\/th>\n <th>Percentage change (in %)<\/th>\n <th>URL<\/th>\n <th>Ticker_adn<\/th>\n <th>Date<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"dom":"BRrltpi","scrollX":true,"scrollY":"350px","lengthMenu":[[10,50,100,-1],["10","50","100","All"]],"ColReorder":true,"rowReorder":false,"buttons":["copy","print",{"extend":"collection","buttons":["csv","excel","pdf"],"columnDefs":[{"targets":[0,2,3,4,5,6,7,8],"className":"dt-center"}],"text":"Download"},["colvis"]],"columnDefs":[{"className":"dt-right","targets":5}],"order":[],"autoWidth":false,"orderClasses":false,"responsive":true},"selection":{"mode":"multiple","selected":null,"target":"row","selectable":null}},"evals":[],"jsHooks":[]}</script>
It receives no argument and retrieves information about all indices available on Euronext.
# Get list of Indices available on Euronext
all_indices = EN_Indices_List()
dim(all_indices)
tail(all_indices)
#> [1] 1263 8
Name | Isin | Symbol | Last | Percentage change (in %) | Date_Time | YTD% | Ticker_adn |
---|---|---|---|---|---|---|---|
SBF Top 50 ESG EW GR | FR0013371432 | ESF5G | €1269.06 | +0.45% | 16 Feb 2024 | +0.59% | FR0013371432-ESF5G |
SBF Top 50 ESG EW NR | FR0013371424 | ESF5N | €1209.36 | +0.45% | 16 Feb 2024 | +0.54% | FR0013371424-ESF5N |
SBF Top 80 EW | FR0013017936 | SBF80 | €1263.47 | +0.54% | 16 Feb 2024 | +0.91% | FR0013017936-SBF80 |
SBF Top 80 EW Decrement 50 Points | FR0013017969 | SBF8D | €1014.72 | +0.52% | 16 Feb 2024 | +0.35% | FR0013017969-SBF8D |
SBF Top 80 EW GR | FR0013017951 | SBF8G | €1609.10 | +0.53% | 16 Feb 2024 | +1.03% | FR0013017951-SBF8G |
SBF Top 80 EW NR | FR0013017944 | SBF8N | €1505.70 | +0.53% | 16 Feb 2024 | +0.99% | FR0013017944-SBF8N |
EN_Etfs_List receives as input tot_page which is the total number of pages to retrieve. In contrast, EN_Etfs_List_bis receives as input target_page which represents the target page. For example, the function EN_Etfs_List_bis(5), retrieves only the fifth page of the Etfs list, allowing more granular control of the data retrieval process (ordered list of 100 Etfs), whereas EN_Etfs_List(5) would return an ordered list of 500 Etfs listed on Euronext (on each page there are 100 Etfs, so for 5 pages 5*100 = 500).
# Get 1st 500 Etfs in alphabetic order
dt_ <- EN_Etfs_List()
tail(dt_[, c(2:9)])
# The number of columns and rows
dim(dt_)
Name | Ticker | Code_ISIN | Market | Bid | Ask | Last_price | Percentage_change | |
---|---|---|---|---|---|---|---|---|
495 | AMUNDI UK Gov Infl | GILI | LU1407893301 | XPAR | - | - | €160.72 | -0.49 |
496 | AMUNDI US CORP SRI | UCRP | LU1806495575 | XPAR | - | - | $55.901 | -0.25 |
497 | AMUNDI US MIN VO | MIVU | LU1589349734 | XPAR | - | - | €83.572 | 0.18 |
498 | AMUNDI US MIN VO | MIVU | LU1589349734 | XAMS | - | - | $89.95 | 0.18 |
499 | AMUNDI US STEEPEN | STPU | LU2018762653 | XPAR | - | - | €87.156 | -0.15 |
500 | AMUNDI US TIPS | UIFL | LU1525419294 | XPAR | - | - | $58.178 | -0.14 |
#> [1] 500 11
# By default, EN_Etfs_List_bis() returns the list of 100 Etfs in alphabetic order
dt_1 <- EN_Etfs_List_bis()
# The number of columns and rows
dim(dt_1)
# Head
dt_1.h <- head(dt_1[, c(2:9)])
#> [1] 100 11
Name | Ticker | Code_ISIN | Market | Bid | Ask | Last_price | Percentage_change |
---|---|---|---|---|---|---|---|
$Asia IG Corp US A | ASIG | IE0007G78AC4 | XAMS | - | - | $4.8035 | -0.18 |
-1X SHORT DIS | SDIS | XS2337085422 | XAMS | - | - | €5.8727 | 0.09 |
-1X SHORT PLTR | SPLR | XS2337086669 | XAMS | - | - | €1.2385 | -0.67 |
-1X SHORT PLUG | SPLU | XS2336362079 | XAMS | - | - | €4.2378 | -1.79 |
-3X ARK INNOVATION | SARKK | XS2399368906 | XAMS | - | - | €0.4817 | 2.77 |
-3x China Tech | SKWE | XS2399370126 | XAMS | - | - | €0.2784 | -4.46 |
EN_Bonds_List receives as input tot_page which is the total number of pages to retrieve. In contrast, EN_Bonds_List_bis receives as input target_page which represents the target page. For example, the function EN_Bonds_List_bis(5), retrieves only the fifth page of the Bonds list, allowing more granular control of the data retrieval process (ordered list of 100 Bonds), whereas EN_Bonds_List(5) would return an ordered list of 500 Bonds listed on Euronext (on each page there are 100 Bonds, so for 5 pages 5*100 = 500).
# Get 1st 500 Bonds in alphabetic order
dt_b <- EN_Bonds_List()
head(dt_b[, c(2:9)])
tail(dt_b[, c(2:9)])
Name | Issuer | Code_ISIN | Market | Maturity | Coupon | Last_price | Percentage change |
---|---|---|---|---|---|---|---|
2019 PB RMBS TV EU | 2019 POPOLARE BARI RMBS | IT0005386724 | XMOT | 2069-05-31 | 0.0% | - | - |
2019 PB RMBS TV EU | 2019 POPOLARE BARI RMBS | IT0005386724 | XMOT | 2069-05-31 | 0.0% | - | - |
2019 PB RMBS TV EU | 2019 POPOLARE BARI RMBS | IT0005386724 | XMOT | 2069-05-31 | 0.0% | - | - |
2I RETE GAS TF 2,1 | 2I RETE GAS | IT0005386724 | XMOT | 2025-09-11 | 0.0% | - | - |
2IRG 1.608% CALL 3 | 2I RETE GAS | IT0005386724 | ETLX | 2027-10-31 | 0.0% | 93.65 | -0.62% |
2IRG 1.75% CALL 28 | 2I RETE GAS | IT0005386724 | ETLX | 2026-08-28 | 0.0% | - | - |
Name | Issuer | Code_ISIN | Market | Maturity | Coupon | Last_price | Percentage change | |
---|---|---|---|---|---|---|---|---|
495 | ALLY FINANCIAL 8% | ALLY FINANCIAL INC | NO0012698358 | ETLX | 2031-11-01 | 0.0% | 109.11 | -0.06% |
496 | ALPERIA GREEN TF 5 | Alperia S.p.A | NO0012698358 | ETLX | 2028-07-05 | 0.0% | 99.85 | 0.14% |
497 | ALPHATHAI8%28JAN25 | ALPHA THAI BENELUX SA | NO0012698358 | VPXB | 2025-01-28 | 8.0% | - | - |
498 | ALSTO0.125%27JUL27 | ALSTOM | NO0012698358 | XPAR | 2027-07-27 | 0.125% | - | - |
499 | ALSTOM0%11JAN29 | ALSTOM | NO0012698358 | XPAR | 2029-01-11 | 0.0% | 99.22 | 0.30% |
500 | ALSTOM0.25%14OCT26 | ALSTOM | NO0012698358 | XPAR | 2026-10-14 | 0.25% | - | - |
dt_b1 <- EN_Bonds_List_bis() #By default returns the list of 100 Bonds in alphabetic order
head(dt_b1[, c(2:9)])
tail(dt_b1[, c(2:9)])
Name | Issuer | Code_ISIN | Market | Maturity | Coupon | Last_price | Percentage change |
---|---|---|---|---|---|---|---|
2019 PB RMBS TV EU | 2019 POPOLARE BARI RMBS | IT0005386724 | XMOT | 2069-05-31 | 0.0% | - | - |
2019 PB RMBS TV EU | 2019 POPOLARE BARI RMBS | IT0005386724 | XMOT | 2069-05-31 | 0.0% | - | - |
2019 PB RMBS TV EU | 2019 POPOLARE BARI RMBS | IT0005386724 | XMOT | 2069-05-31 | 0.0% | - | - |
2I RETE GAS TF 2,1 | 2I RETE GAS | IT0005386724 | XMOT | 2025-09-11 | 0.0% | - | - |
2IRG 1.608% CALL 3 | 2I RETE GAS | IT0005386724 | ETLX | 2027-10-31 | 0.0% | 93.65 | -0.62% |
2IRG 1.75% CALL 28 | 2I RETE GAS | IT0005386724 | ETLX | 2026-08-28 | 0.0% | - | - |
Name | Issuer | Code_ISIN | Market | Maturity | Coupon | Last_price | Percentage change | |
---|---|---|---|---|---|---|---|---|
95 | AAB1.95%7DEC2048 | ABN AMRO BANK N.V. | IT0005386724 | XAMS | 2048-12-07 | 1.95% | - | - |
96 | AAB2.29%29JUL30 | ABN AMRO BANK N.V. | IT0005386724 | XAMS | 2030-07-29 | 2.29% | - | - |
97 | AAB2.375%1JUN2027 | ABN AMRO BANK N.V. | IT0005386724 | XAMS | 2027-06-01 | 2.375% | - | - |
98 | AAB2.47%13DEC29 | ABN AMRO BANK N.V. | IT0005386724 | XAMS | 2029-12-13 | 2.47% | - | - |
99 | AAB2.47%13DEC29RS | ABN AMRO BANK N.V. | IT0005386724 | XAMS | 2029-12-13 | 2.47% | - | - |
100 | AAB3%1JUN2032 | ABN AMRO BANK N.V. | IT0005386724 | XAMS | 2032-06-01 | 3.0% | - | - |
The function takes a single parameter, 'ticker,' which can be the symbol, name, or ISIN of a given stock or index, and then returns its DNA.
Example 6.a : Get DNA (ISIN-Market identifier) of a given Stock or Index listed on Euronext by providing the Symbol or Name, or ISIN of a Stock or an Index.
To efficiently use the 'Euronext' package, it is important to understand how to handle Ticker Names, ISIN, and DNA, as many functions in the package rely on these. Note: There is a small difference between ISIN and DNA. Here's a simple example: the ticker "4DDD" has the ISIN "US88554D2053," and its DNA is "US88554D2053-ETLX." As you can see, the DNA is composed of the ISIN and the market identifier "ETLX," preceded by "-".
Please refer to the respective functions EN_Stocks_List(), EN_Indices_List(), EN_Etfs_List() or EN_Etfs_List_bis(), EN_Funds_List(), and EN_Bonds_List() or EN_Bonds_List_bis() if you wish to obtain a list of available Stocks, Indices, ETFs, Funds, and Bonds on Euronext.
# Get DNA of ticker "4DDD"
EN_GetISIN("4DDD")
#> [1] "US88554D2053-ETLX"
# Get DNA for the ticker name "ADS MARITIME HOLD"
EN_GetISIN("ADS MARITIME HOLD")
#> [1] "CY0108052115-MERK"
# Get DNA for ATENOR company by providing its ISIN
EN_GetISIN("BE0003837540")
#> [1] "BE0003837540-XBRU"
Example 6.b : Get DNA (ISIN-Market identifier) of a given fund listed on Euronext by providing its symbol, name, or ISIN.
# Get Fund 'ACOMEA GLOBALE' DNA
aco_dna <- EN_GetISIN_F("ACOMEA GLOBALE")
# In case you want the ISI only
sub("-.*", "", aco_dna) #To get only the ISIN
#> [1] "IT0005091100"
# Get Fund 'ASNU SMALL MIDCAPF' DNA
asnu_dna <- EN_GetISIN_F("ASN5")
print(asnu_dna)
#> [1] "NL0014270217-XAMS"
# Get Fund 'COMPAM ACTIVE GLOB' DNA
EN_GetISIN_F("LU1275425897")
#> [1] "LU1275425897-ATFX"
Example 6.c : Get DNA (ISIN-Market identifier) of a given ETF listed on Euronext by providing its Symbol or Name, or ISIN of a Stock or an Index.
# Get ETF 'AAPL' DNA
EN_GetISIN_Etf("AAPL")
#> [1] "XS2337099563-XAMS"
# Get ETF '-1X SHORT DIS' DNA
EN_GetISIN_Etf("-1X SHORT DIS")
#> [1] "XS2337085422-XAMS"
# Get ETF '3x Long Coinbase' DNA
EN_GetISIN_Etf("XS2399367254")
#> [1] "XS2399367254-XAMS"
Example 6.d : Get DNA (ISIN-Market identifier) of a given Bond listed on Euronext by providing its Symbol or Name, or ISIN of a Stock or an Index.
#To get only the DNA of all same bonds issued
the_dna1 <- EN_GetISIN_B("ABN AMRO BANK N.V.")
print(the_dna1)
#> [1] "XS1344751968-XAMS"
the_isin1 <- sub("-.*", "", the_dna1) #To get only the ISINs
print(the_isin1)
#> [1] "XS1344751968"
#To get only the DNA of Bond 'A2A GREEN BOND TF'
the_dna2 = EN_GetISIN_B("A2A GREEN BOND TF")
the_isin2 =sub("-.*", "", the_dna2) #To get only the ISIN
print(the_isin2)
#> [1] "XS2403533263"
This function retrieves the historical performance data of a company listed on the Euronext exchange based on its ticker symbol. It returns a table with details such as the highest and lowest stock prices, date of the highest and lowest prices, and other relevant information. It receives three (3) parameters such us :
- 'ticker' : A character string representing the company's ticker symbol,
- 'stock_type' : The type of the ticker: 'Eq_Ind' for Stocks and Indexes, 'Fund' or "F" for Fund tickers, 'Bond' or "B" for Bond tickers, and 'Etfs' or "E" for EFTs.
- 'escape' : Boolean, either TRUE or FALSE. If escape is True, it means you're providing the DNA (ISIN-Market identifier) directly. Giving T to escape is helpful to avoid time-consuming operations; otherwise, F means you need to provide the Ticker symbol, name, or ISIN and the type of market to which it belongs. By default, escape = 'FALSE'
# Get Performance of Ticker ABCA
dt = EN_Ticker_Performance("ABCA")
print(dt)
D-1 | 1W | 1M | 3M | 6M | YTD | 52W | 2Y | 3Y | 5Y | MAX | |
---|---|---|---|---|---|---|---|---|---|---|---|
Highest | 4.02 | 4.47 | 4.815 | 5.12 | 6.12 | 4.87 | 6.60 | 7.78 | 8.15 | 8.15 | 14.85 |
Date of the highest | 15/02/2024 - 17:35 | 12/02/2024 | 16/01/2024 | 29/11/2023 | 01/09/2023 | 09/01/2024 | 21/02/2023 | 19/04/2022 | 22/03/2021 | 22/03/2021 | 25/02/2000 |
Lowest | 3.82 | 3.82 | 3.82 | 3.82 | 3.82 | 3.82 | 3.82 | 3.82 | 3.82 | 3.82 | 1.50 |
Date of the lowest | 15/02/2024 - 09:03 | 15/02/2024 | 15/02/2024 | 15/02/2024 | 15/02/2024 | 15/02/2024 | 15/02/2024 | 15/02/2024 | 15/02/2024 | 15/02/2024 | 11/10/2002 |
% | 2.29 | -7.20 | -17.12 | -20.10 | -32.86 | -16.86 | -39.19 | -43.89 | -46.23 | -34.72 | -58.81 |
Change | 0.09 | -0.31 | -0.825 | -1.005 | -1.955 | -0.81 | -2.575 | -3.125 | -3.435 | -2.125 | -5.705 |
Turnover | 541341.62 | 2763810.55 | 7234093.76 | 13.451M | 23.218M | 9101300.43 | 47.985M | 105.182M | 181.866M | 313.130M | 1.371B |
Volume | 137671 | 679069 | 1708262 | 2981586 | 4791306 | 2102301 | 8863320 | 17.091M | 27.699M | 47.498M | 82.247B |
Avg Vol | 137671 | 113178 | 71178 | 45871 | 36575 | 61832 | 34488 | 33187 | 35787 | 36992 | 12.685M |
Avg Price | 3.93 | 4.07 | 4.23 | 4.51 | 4.85 | 4.33 | 5.41 | 6.15 | 6.57 | 6.59 | 0.02 |
Nb days | 1 | 6 | 24 | 65 | 131 | 34 | 257 | 515 | 774 | 1284 | 6484 |
# Get Performance of ETF AAPL
dt_ = EN_Ticker_Performance("AAPL", stock_type = "E")
print(dt_)
D-1 | 1W | 1M | 3M | 6M | YTD | 52W | 2Y | 3Y | 5Y | MAX | |
---|---|---|---|---|---|---|---|---|---|---|---|
Highest | 6.767 | 6.989 | 7.241 | 7.271 | 7.271 | 7.241 | 7.271 | 7.271 | 7.271 | 7.271 | 7.271 |
Date of the highest | 15/02/2024 - 11:02 | 12/02/2024 | 06/02/2024 | 15/12/2023 | 15/12/2023 | 06/02/2024 | 15/12/2023 | 15/12/2023 | 15/12/2023 | 15/12/2023 | 15/12/2023 |
Lowest | 6.715 | 6.715 | 6.625 | 6.532 | 6.281 | 6.532 | 5.35 | 4.700 | 4.030 | 4.030 | 4.030 |
Date of the lowest | 15/02/2024 - 16:58 | 15/02/2024 | 17/01/2024 | 08/01/2024 | 27/10/2023 | 08/01/2024 | 02/03/2023 | 06/01/2023 | 07/06/2021 | 07/06/2021 | 07/06/2021 |
% | -1.02 | -1.96 | 1.43 | -1.73 | 5.13 | -1.95 | 19.61 | 14.07 | 66.14 | 66.14 | 66.14 |
Change | -0.069 | -0.136 | 0.096 | -0.120 | 0.331 | -0.135 | 1.113 | 0.838 | 2.703 | 2.703 | 2.703 |
Turnover | 1685.48 | 9440.18 | 26667.44 | 30329.86 | 58828.23 | 28765.10 | 147664.42 | 370788.36 | 448038.65 | 448038.65 | 448038.65 |
Volume | 250 | 1367 | 3846 | 4385 | 8672 | 4159 | 24103 | 66059 | 80750 | 80750 | 80750 |
Avg Vol | 250 | 228 | 160 | 69 | 67 | 122 | 94 | 129 | 104 | 63 | 12 |
Avg Price | 6.74 | 6.91 | 6.93 | 6.92 | 6.78 | 6.92 | 6.13 | 5.61 | 5.55 | 5.55 | 5.55 |
Nb days | 1 | 6 | 24 | 64 | 130 | 34 | 256 | 514 | 773 | 1283 | 6483 |
# Get Performance of Bond issued by A2A S.p.A.
dt1 = EN_Ticker_Performance("XS1195347478-ETLX", escape = TRUE)
print(dt1)
D-1 | 1W | 1M | 3M | 6M | YTD | 52W | 2Y | 3Y | 5Y | MAX | |
---|---|---|---|---|---|---|---|---|---|---|---|
Highest | 98.20 | 99.25 | 99.25 | 99.25 | 99.25 | 99.25 | 99.25 | 99.28 | 102.85 | 107.14 | 108.98 |
Date of the highest | 02/01/2024 - 09:32 | 11/01/2024 | 11/01/2024 | 11/01/2024 | 11/01/2024 | 11/01/2024 | 11/01/2024 | 09/08/2022 | 03/02/2022 | 11/09/2019 | 14/07/2016 |
Lowest | 98.20 | 98.45 | 98.45 | 97.21 | 97.02 | 98.20 | 96.30 | 95.38 | 95.38 | 95.38 | 94.28 |
Date of the lowest | 02/01/2024 - 09:32 | 11/01/2024 | 11/01/2024 | 22/11/2023 | 06/11/2023 | 02/01/2024 | 24/02/2023 | 20/10/2022 | 20/10/2022 | 20/10/2022 | 24/06/2015 |
% | -0.06 | 0.05 | 0.16 | 0.95 | 1.10 | 0.14 | 1.11 | -4.52 | -7.80 | -4.63 | -2.91 |
Change | -0.06 | 0.05 | 0.16 | 0.93 | 1.07 | 0.14 | 1.08 | -4.66 | -8.33 | -4.78 | -2.95 |
Turnover | 98200.00 | - | - | 590560.00 | 883180.00 | 394800.00 | 3128140.00 | 6824010.00 | 7029220.00 | 8402410.00 | 18.669M |
Volume | 100000 | 300000 | 300000 | 900000 | 1200000 | 700000 | 3500000 | 7300000 | 7500000 | 8800000 | 19.000M |
Avg Vol | 100000 | 50000 | 12500 | 13636 | 9091 | 20588 | 13410 | 13985 | 9579 | 6748 | 2899 |
Avg Price | 0.01 | - | - | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 |
Nb days | 1 | 6 | 24 | 66 | 132 | 34 | 261 | 522 | 783 | 1304 | 6553 |
# Get Performance of ACOMEA EMERGING Q2 Fund
dt2 = EN_Ticker_Performance("IT0005091126", 'F', escape = FALSE)
print(dt2)
D-1 | 1W | 1M | 3M | 6M | YTD | 52W | 2Y | 3Y | 5Y | MAX | |
---|---|---|---|---|---|---|---|---|---|---|---|
Highest | 10.679 | 9.955 | 9.955 | 9.955 | 9.955 | 9.955 | 10.679 | 10.847 | 12.185 | 12.185 | 12.185 |
Date of the highest | 06/07/2023 - 15:01 | 07/12/2023 | 07/12/2023 | 07/12/2023 | 07/12/2023 | 07/12/2023 | 06/07/2023 | 01/06/2022 | 12/11/2021 | 12/11/2021 | 12/11/2021 |
Lowest | 10.679 | 9.955 | 9.955 | 9.955 | 9.955 | 9.955 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Date of the lowest | 06/07/2023 - 15:01 | 07/12/2023 | 07/12/2023 | 07/12/2023 | 07/12/2023 | 07/12/2023 | 24/03/2023 | 24/03/2023 | 24/03/2023 | 24/03/2023 | 24/03/2023 |
% | 6.59 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | -4.38 | -16.07 | -5.80 | 26.76 | 28.07 |
Change | 0.66 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | -0.459 | -1.919 | -0.617 | 2.115 | 2.196 |
Turnover | 5125.92 | - | - | 447.98 | 447.98 | - | 7428.04 | 291434.81 | 329300.08 | 781736.51 | 1027788.16 |
Volume | 480 | 45 | 45 | 90 | 90 | 45 | 750 | 26941 | 30249 | 86089 | 118276 |
Avg Vol | 480 | 8 | 2 | 1 | 1 | 1 | 3 | 53 | 39 | 68 | 18 |
Avg Price | 10.68 | - | - | 4.98 | 4.98 | - | 9.90 | 10.82 | 10.89 | 9.08 | 8.69 |
Nb days | 1 | 6 | 24 | 64 | 130 | 34 | 255 | 512 | 769 | 1275 | 6496 |
# Get Performance of AEX All-Share Index
dt3 = EN_Ticker_Performance("AEX All-Share Index GR", escape = FALSE)
print(dt3)
D-1 | 1W | 1M | 3M | 6M | YTD | 52W | 2Y | 3Y | 5Y | MAX | |
---|---|---|---|---|---|---|---|---|---|---|---|
Highest | 4,518.02 | 4,553.63 | 4,553.63 | 4,553.63 | 4,553.63 | 4,553.63 | 4,553.63 | 4,553.63 | 4,553.63 | 4,553.63 | 4,553.63 |
Date of the highest | 15/02/2024 - 09:29 | 12/02/2024 | 12/02/2024 | 12/02/2024 | 12/02/2024 | 12/02/2024 | 12/02/2024 | 12/02/2024 | 12/02/2024 | 12/02/2024 | 12/02/2024 |
Lowest | 4,485.06 | 4,453.24 | 4,053.49 | 3,970.81 | 3,719.88 | 4,053.49 | 3,696.85 | 3,164.52 | 3,164.52 | 2,001.91 | 1,271.98 |
Date of the lowest | 15/02/2024 - 09:00 | 13/02/2024 | 17/01/2024 | 17/11/2023 | 23/10/2023 | 17/01/2024 | 20/03/2023 | 13/10/2022 | 13/10/2022 | 16/03/2020 | 04/06/2012 |
% | 0.65 | 1.22 | 10.30 | 13.35 | 14.81 | 8.89 | 13.09 | 18.90 | 25.98 | 64.86 | 250.16 |
Change | 28.97 | 54.97 | 424.92 | 536.13 | 587.12 | 371.52 | 527.02 | 723.55 | 938.90 | 1,791.03 | 3,252.21 |
Turnover | - | - | - | - | - | - | - | - | - | - | - |
Volume | - | - | - | - | - | - | - | - | - | - | - |
Avg Vol | - | - | - | - | - | - | - | - | - | - | - |
Nb days | 1 | 6 | 24 | 64 | 130 | 34 | 256 | 514 | 773 | 1283 | 6483 |
As its name suggests, this function retrieves data from the ticker(s) and displays it in graphical form. It offers a convenient method to obtain a quick overview of price trends, facilitating further analysis.
This function accepts up to seven arguments:
- ticker: is the name of the ticker(s)
- from: A quotation start date, i.e. "2020-01-01" or "2020/01/01". The date must be in ymd format "YYYY-MM-DD" or "YYYY/MM/DD".
- until : A quoted end date, i.e. "2022-01-31" or "2022/01/31". The date must be in ymd format "YYYY-MM-DD" or "YYYY/MM/DD".
- 'stock_type': Ticker type: 'Eq_Ind' for stocks and indices, 'Fund' or "F" for fund tickers, 'Bond' or "B" for bond tickers, and 'Etfs' or "E" for EFTs.
- escape': Boolean, either TRUE or FALSE. If escape is True, this means you're supplying the ISIN-Market identifier (ADN) directly. Giving T to escape is useful to avoid tedious operations; otherwise, F means you must provide the Ticker symbol, the name or ISIN and the type of market to which it belongs. By default, escape = 'FALSE'.
- up.col : is the color of the rise
- down.col : is the color of the fall
# The default colors for the up and down are 'darkgreen' and 'red', respectively.
chart <- EN_Overview_plot("4ddd")
# chart
ov_plot <- EN_Overview_plot(c("NL0010614533", "QS0011211206", "QS0011095914", "QS0011146899"), up.col = "blue")
# ov_plot
This EN_plot() function is distinct from the EN_Overview_plot() function, although they share similar parameters (ticker, from, to, stock_type, escape, up.col, down.col) Note: Important to note that when using EN_plot(),only historical data from the past two years is available. This differs from EN_Overview_plot(), where data is available from the inception year of the company's listing.
#It is also possible to plot stock data chart for more than one ticker
#Let's plot '3D SYSTEMS CORP' chart
chart1 <- EN_plot("AAX")
# chart1
# You can change up and down colors
# Etf AAPL
# EN_plot("aapl", stock_type = 'E', up.col = "blue", down.col = "pink")
# It is also possible to plot stock data chart for more than one ticker
# Let's plot some equities chart
chart2 <- EN_plot(c("AAX", "QS0011016480", "AEX2S", "ADIDAS", "ADOBE", "ALFEN BEHEER", "1GOOGL"))
# chart2
# It is also possible to plot stock data chart for more than one ticker
# Let's plot three ETFs chart
chart3 <- EN_plot(c("IE0007G78AC4", "MANA", "3TSM"), stock_type = 'E')
# chart3
This function retrieves detailed information for a given stock ticker on the Euronext exchange. It includes information such as currency, last traded price, valuation close, volume, turnover, transactions, VWAP (Volume Weighted Average Price), open, high, low, threshold, previous close, 52-week range, and market capitalization. The data is returned as a data frame.
Inputs :
- ticker A character string representing the company's ticker, name, or ISIN.
- stock_type The type of the ticker: 'Eq_Ind' for Stocks and Indexes, 'Fund' or "F" for Fund tickers,'Bond' or "B" for Bond tickers, and 'Etfs' or "E" for EFTs.
- escape Boolean, either TRUE or FALSE. If escape is True, it means you're providing the DNA (ISIN-Market identifier) directly. Giving T to escape is helpful to avoid time-consuming operations; otherwise, F means you need to provide the Ticker symbol, name, or ISIN and the type of market to which it belongs.
# Retrieve news for the equity "AALBERTS N.V." using its DNA
equity_infos <- EN_Ticker_infos("NL0000852564-XAMS", escape = TRUE)
print(equity_infos)
Information | Detail | Update date/Time |
---|---|---|
Currency | EUR | |
Last Traded | 37.25 | [16/02/2024 17:35] |
Valuation Close | 37.25 | [16/02/2024] |
Volume | 164,119 | [16/02/2024 17:35] |
Turnover | 6,108,815 | |
Transactions | 1,511 | |
VWAP | 37.2219 | |
Open | 37.09 | |
High | 37.53 | [11:32] |
Low | 36.97 | [14:33] |
Threshold | 39.11 - 35.39 | [16/02/2024 17:35] |
Previous Close | 36.78 | [15/02/2024] |
52 Week | 28.83 - 48.53 | |
Market Cap | 4.119B |
# Retrieve news for the index "AEX All-Share Index GR" using its symbol
index_infos <- EN_Ticker_infos("QS0011224977-XAMS", escape = TRUE)
print(index_infos)
Information | Detail | Update date/Time |
---|---|---|
Open | 4,508.00 | |
High | 4,552.25 | [17:51] |
Low | 4,508.00 | [09:00] |
Previous Close | 4,507.65 | [15/02/2024] |
52 Week | 3,696.85 - 4,553.63 |
# Retrieve news for the bond "AAB0.45%12DEC2036" using its DNA
bond_infos <- EN_Ticker_infos("XS2093705064-XAMS", escape = TRUE)
print(bond_infos)
Information | Detail | Update date/Time |
---|---|---|
Currency | % | |
Last Traded | - | |
Valuation Close | 100.00 | [16/02/2024] |
Open | - | |
High | - | - |
Low | - | - |
Threshold | 103.00 - 97.00 | [03/04/2023 03:01] |
Previous Close | - | |
52 Week | - - |
The EN_intraday_Data() function fetches intraday price data for a specified stock on Euronext. It allows you to retrieve either today's intraday prices or the previous day's intraday prices, with "Today" being the default option. The function returns a data frame containing the intraday stock information.
Inputs :
- ticker: A character string representing the stock ticker or name.
- day_type : A character string specifying the type of intraday price to fetch. Options are "Today" or "Previous" day. Default is "Today." You can also use 'T' for 'Today' or 'P' for 'Previous'.
- stock_type : The type of the ticker, which can be 'Eq_Ind' for Stocks and Indexes, 'Fund' or "F" for Fund tickers, 'Bond' or "B" for Bond tickers, and 'Etfs' or "E" for ETFs. escape: A Boolean value (either TRUE or FALSE). If escape is set to True, it indicates that the DNA (ISIN-Market identifier) is provided directly. Using True for escape can help avoid time-consuming operations. If escape is set to False, the function expects the Ticker symbol, name, or ISIN, along with the type of market to which it belongs.
- nbitems: An integer specifying the number of items to fetch. Default is 30 (also the maximum).
# Get recent intraday prices of ABCA share for 10 items
intra_ = EN_intraday_Data("ABCA", day_type = 'T', nbitems = 10)
print(intra_)
Tradeid | Time | Price | Volume | Type |
---|---|---|---|---|
1OK98JYWA | 17:35:01 | 3.995 | 13 | Auction |
1OK98JYW9 | 17:35:01 | 3.995 | 105 | Auction |
1OK98JYW8 | 17:35:01 | 3.995 | 46 | Auction |
1OK98JYW7 | 17:35:01 | 3.995 | 34 | Auction |
1OK98JYW6 | 17:35:01 | 3.995 | 186 | Auction |
1OK98JYW5 | 17:35:01 | 3.995 | 21 | Auction |
1OK98JYW4 | 17:35:01 | 3.995 | 73 | Auction |
1OK98JYW3 | 17:35:01 | 3.995 | 93 | Auction |
1OK98JYW2 | 17:35:01 | 3.995 | 185 | Auction |
1OK98JYW1 | 17:35:01 | 3.995 | 47 | Auction |
intra_1 = EN_intraday_Data("IT0005091126", 'F', escape = FALSE, day_type = 'T')
print(intra_1)
Tradeid | Time | Price | Volume | Type |
---|---|---|---|---|
5FC6J23R | 15:00:48 | 9.955 | 45 | OffBook On Exchange |
Example 10.c : Get Previous intraday prices of ETF AAPL by providing directly the ISIN-Market identifier
intra_2 = EN_intraday_Data("XS2337099563-XAMS", escape = TRUE, day_type = 'Previous')
print(intra_2)
Tradeid | Time | Price | Volume | Type |
---|---|---|---|---|
- | 09:04:21 | 6.7904 | 1 | Valuation Trade |
intra_3 = EN_intraday_Data("AEX All-Share Index GR", day_type = 'P')
print(intra_3)
Tradeid | Time | Price | Volume | Type |
---|---|---|---|---|
- | 18:05:02 | 4,552.24 | - | Closing Reference index |
- | 18:00:01 | 4,552.24 | - | Closing Reference index |
- | 18:00:00 | 4,552.25 | - | Real-time index |
- | 17:59:30 | 4,552.24 | - | Real-time index |
- | 17:59:00 | 4,552.25 | - | Real-time index |
- | 17:58:46 | 4,552.24 | - | Real-time index |
- | 17:51:15 | 4,552.25 | - | Real-time index |
- | 17:42:30 | 4,552.24 | - | Real-time index |
- | 17:42:15 | 4,552.23 | - | Real-time index |
- | 17:42:00 | 4,552.24 | - | Real-time index |
The En_Market.Sumarry() function retrieve from Euronext the summaries of a giving Stock Market.
Input :
- stock_choice: A character string specifying the market of interest. Available options include "a" or "amsterdam" for Amsterdam, "b" or "brussels" for Brussels, "d" or "dublin" for Dublin, "l" or "lisbon" for Lisbon, "m" or "milan" for Milan, "p" or "paris" for Paris, and "o" or "oslo" for Oslo.
Return Value : A list containing summary data for the selected market, including information on stock indices and currency rates. The list includes the following components:
-
Indices_summary: A data frame summarizing stock market indices for the selected market. It includes columns for the index name, last price, and percentage change. If the summary is not available, this component will be set to NA.
-
EU_indices: A data frame summarizing EURONEXT indices for the selected market. It includes columns for the instrument name, last price, and percentage change. If the summary is not available, this component will be set to NA.
-
Currency_rate: A data frame summarizing currency exchange rates for the selected market. It includes columns for the instrument name, last price, and percentage change. If the summary is not available, this component will be set to NA.
# Retrieve summary data for 'Paris stock'
En_Market.Sumarry("p")
#> [1] "Summary data for 'Amsterdam stock indices'"
Index | Last price | Change (%) |
---|---|---|
CAC 40 | 7768.18 | 0.32 |
CAC ALL SHARES | 9461.65 | 0.36 |
CAC NEXT 20 | 11131.35 | 0.89 |
CAC SMALL | 11790.97 | -0.28 |
SBF 120 | 5883.26 | 0.36 |
#> [1] "Summary data for 'EURONEXT indices'"
Instrument name | Last price | Day change relative (%) |
---|---|---|
EURONEXT 100 | 1447.13 | 0.47 |
CLIMATE EUROPE | 1860.64 | 0.63 |
LOW CARBON 100 | 159.57 | 0.73 |
NEXT BIOTECH | 2260.42 | 0.05 |
ESG 80 | 1996.90 | 0.44 |
#> [1] "Summary data for 'Currency rate'"
Instrument name | Last price | Day change relative (%) |
---|---|---|
EUR / USD | 1.07762 | 0.04 |
EUR / GBP | 0.85510 | 0.03 |
EUR / JPY | 161.90000 | 0.25 |
EUR / CHF | 0.95169 | 0.39 |
GBP / USD | 1.26015 | 0.00 |
Purpose : Retrieves order book data for a given stock or ETF ticker on the Euronext exchange.
Inputs: • ticker: A character string representing the company's (equity or ETF) ticker, name, or ISIN. • stock_type: The type of the ticker. It can be 'Equity' for stocks or 'Etf' for ETFs.
Output : Returns a data frame containing order book data with columns representing buy (bid) and sell (ask) orders, including order quantity and price.
# Get order book data for ABC ARBITRAGE ticker
ABCA_OB <- EN_Get_OB("ABCA")
print(ABCA_OB)
B_order | B_quantity | Bid_Price | Ask_Price | A_quantity | A_order |
---|---|---|---|---|---|
1 | 500 | 3.94 | 4 | 500 | 1 |
2 | 7033 | 3.91 | 4.02 | 614 | 2 |
1 | 100 | 3.9 | 4.05 | 868 | 3 |
1 | 100 | 3.895 | 4.06 | 150 | 1 |
1 | 195 | 3.88 | 4.08 | 122 | 1 |
1 | 10 | 3.87 | 4.1 | 650 | 2 |
6 | 1496 | 3.85 | 4.11 | 1452 | 12 |
1 | 39 | 3.835 | 4.145 | 724 | 2 |
6 | 1101 | 3.82 | 4.15 | 500 | 1 |
1 | 37 | 3.815 | 4.195 | 2500 | 1 |
21 | 10611 | - | - | 8080 | 26 |
# Get order book data for MSFT ETF
MSFT_OB <- EN_Get_OB("MSFT", stock_type = 'Etf')
print(MSFT_OB)
B_order | B_quantity | Bid_Price | Ask_Price | A_quantity | A_order |
---|---|---|---|---|---|
1 | 580 | 7.5 | NA | NA | NA |
1 | 1 | 5 | NA | NA | NA |
2 | 581 | - | - | 0 | 0 |
Purpose : Retrieves order book data from Euronext for a given stock or ETF ticker and plots its chart. *Inputs *:
- ticker: The ticker symbol for which the order book chart will be plotted.
- bid.col: Color for bid prices in the chart. Default is '#00FF00' (green).
- ask.col: Color for ask prices in the chart. Default is '#FF0000' (red).
- plot_type: Type of visualization ('depth' or 'barh'). Default is 'depth'
- stock_type: The type of the ticker. It can be 'Equity' for stocks or 'Etf' for ETFs.
Output : Returns a Highchart plot displaying the order book for the provided ticker.
# Plot order book chart for ABC ARBITRAGE ticker using default colors
ABCA_OB_chart <- EN_OrderBook.Chart("FR0004040608", plot_type = 'barh')
ABCA_OB_chart
# Plot order book Market Depth chart for LEBON ticker with default colors ie "darkgreen" and "red"
ALBON_OB_chart <- EN_OrderBook.Chart("ALBON")
ALBON_OB_chart
# In case you want to change colors
# ALBON_OB_chart <- EN_OrderBook.Chart("ALBON", bid.col = 'cyan', ask.col ='gold')
Authors :
Creator : Koffi Frederic Sessie
cph (Copyright Holder) : Koffi Frederic Sessie
License : MIT 2024, Koffi Frederic SESSIE. All rights reserved.