StocksMA is a package to facilitate access to financial and economic data of Moroccan stocks. It tries to cover potentially valuable and interesting data points.
The package include functions to extract price data from Leboursier, financial ratios(income statement, balance sheet, cash flow) from MarketWatch, and profile data from WSJ
Note: Sometimes, some functions may fail to get the data from some sources due to WAF protection.
Python3 is required.
$ pip install StocksMA- Import the package
- Get all availabale tickers
- Get price data
- Get session information
- Current Session performance
- Get intraday price data
- Get Ask Bid data
- Get balance sheet
- Get income statement
- Get cash flow
- Get quote table
- Get market status
- Get company officers
- Get company information
>> import StocksMA as stmDisplay a list of available tickers along with the complete name of the company, the results can also be returned as a DataFrame.
Args:
- as_df :bool: When the input argument is True, the function will generate a DataFrame that includes the list of available tickers along with the complete company name for each ticker.
Example:
stm.get_tickers()ADH / Douja Promotion Groupe Addoha
AFM / AFMA S.A.
AFI / Afric Industries S.A.
GAZ / Afriquia Gaz
.
.
.
AKT / AKDITAL
DYT / DISTY TECHNOLOGIES
TGC / TGCC S.A
RIS / RISMAstm.get_tickers(as_df = True)| Ticker | Name |
|---|---|
| ADH | Douja Promotion Groupe Addoha |
| AFM | AFMA S.A. |
| AFI | Afric Industries S.A. |
| GAZ | Afriquia Gaz |
| AGM | Agma S.A. |
| ... | ... |
| ZDJ | Zellidja S.A. |
| AKT | AKDITAL |
| DYT | DISTY TECHNOLOGIES |
| TGC | TGCC S.A |
| RIS | RISMA |
Get historical OHLCV data for a given symbol(s)
Args:
tickersUnion[str, List[str]]: List or str of companies names or ticker symbols(e.g. ['maroc telecom', 'MNG'] or 'CIH')start_datestr:(YYYY-MM-DD)Starting date to pull data from, limited to a maximum of six yearend_datestr:(YYYY-MM-DD)Ending date. Defaults to the current local date
Returns:
pd.DataFrame: Dataframe of historical OHLCV data
Example:
# Get price data of multiple companies
stm.get_price_data(['CIH','maroc telecom', 'involys'], start_date='2020-11-14', end_date='2022-02-14')| Close | High | Low | Open | Volume | ||
|---|---|---|---|---|---|---|
| Company | Date | |||||
| CIH P | 2020-11-16 | 248.15 | 248.15 | 248.00 | 248.00 | 8 |
| 2020-11-17 | 250.00 | 250.00 | 248.00 | 248.10 | 220 | |
| 2020-11-19 | 245.20 | 248.00 | 245.10 | 248.00 | 133 | |
| ... | ... | ... | ... | ... | ... | |
| INVOLYS P | 2022-02-08 | 131.95 | 131.95 | 131.95 | 131.95 | 5 |
| 2022-02-09 | 131.95 | 131.95 | 131.90 | 131.95 | 100 | |
| 2022-02-11 | 131.90 | 131.90 | 131.00 | 131.00 | 4 |
[840 rows x 5 columns]
# Get price data of single company
stm.get_price_data('involys', start_date='2020-11-14', end_date='2022-02-14')| Open | High | Low | Close | Volume | ||
|---|---|---|---|---|---|---|
| Company | Date | |||||
| INVOLYS P | 2020-11-16 | 119.50 | 121.00 | 119.50 | 121.00 | 11 |
| 2020-11-17 | 118.60 | 121.00 | 118.60 | 121.00 | 22 | |
| 2020-11-19 | 121.00 | 121.00 | 121.00 | 121.00 | 1 | |
| ... | ... | ... | ... | ... | ... | |
| 2022-02-09 | 131.95 | 131.95 | 131.90 | 131.95 | 100 | |
| 2022-02-11 | 131.00 | 131.90 | 131.00 | 131.90 | 4 |
[253 rows x 5 columns]
Get data related to the current trading session of a given symbol
Args:
companystr: Company name or ticker symbol(e.g. 'maroc telecom', 'MNG')
Returns:
pd.DataFrame: Dataframe of session data
Example:
stm.get_session_info('involys')| Name | Name_2 | ISIN | Number of Shares | Close | Previous Close | Market Cap | Quotation Datetime | Change Volume | Change | Volume in Shares | Volume | Open | Low | High | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | INVOLYS P | INVOLYS | MA0000011579 | 382716 | 109.950 | 109.95 | 42079624.20 | 18/03/2022 à 15:16 | 0.00 | 0.00 | 5387 | 49 | 109.400 | 109.400 | 109.950 |
Get the current session's best performing indices
Returns:
pd.DataFrame: Dataframe of the best performing indices, their current price, and the variation of their price
Example:
stm.get_best_performers()| Name | Price | Variation | |
|---|---|---|---|
| 0 | ATLANTASANAD P | 126.1 | 5.97 |
| 1 | PROMOPHARM | 1017 | 3.99 |
| 2 | COSUMAR | 212.5 | 3.66 |
| 3 | Auto Hall P | 82 | 3.54 |
| 4 | TAQA Morocco P | 1050 | 2.94 |
| 5 | Alliances P | 59.8 | 2.75 |
| 6 | SNEP P | 804.8 | 2.52 |
| 7 | Zellidja P | 89.5 | 2.46 |
| 8 | BCP P | 255 | 2.41 |
| 9 | Attijariwafa Bk N | 434 | 2.12 |
| 10 | Sonasid P | 745 | 1.35 |
| 11 | Afriquia Gaz P | 4600 | 0.66 |
| 12 | LafargeHolcim P | 1670 | 0.6 |
| 13 | Managem P | 2200 | 0.05 |
| 14 | Lesieur Cristal | 180 | 0 |
Get the current session's worst performing indices
Returns:
pd.DataFrame: Dataframe of the worst performing indices, their current price, and the variation of their price
Example:
stm.get_worst_performers()| Name | Price | Variation | |
|---|---|---|---|
| 0 | Med Paper P | 23.51 | -5.92 |
| 1 | Delta Holding P | 28.1 | -5.55 |
| 2 | Afric Indus. | 345 | -4.96 |
| 3 | BMCI P | 472 | -4.84 |
| 4 | Sanlam Maroc N | 1402 | -3.97 |
| 5 | EQDOM P | 1199 | -3.77 |
| 6 | SMI P | 1450 | -3.33 |
| 7 | Ennakl N | 32.49 | -2.72 |
| 8 | Colorado P | 50.96 | -2 |
| 9 | Ste Boissons P | 2500 | -1.96 |
| 10 | TotalEnergie MM P | 1700 | -1.9 |
| 11 | Aradei Capital P | 440.05 | -1.77 |
| 12 | Cartier Saada P | 28 | -1.55 |
| 13 | TGCC P | 135 | -1.46 |
| 14 | Addoha P | 7.63 | -1.29 |
| 15 | Aluminium Maroc P | 1531 | -1.23 |
| 16 | Central.Danone P/N | 550 | -0.9 |
| 17 | Risma P | 118 | -0.84 |
| 18 | CTM P | 645.1 | -0.75 |
| 19 | Resid Dar Saada P | 23.8 | -0.71 |
| 20 | SODEP P | 256.2 | -0.7 |
| 21 | Maroc Telecom | 119 | -0.58 |
| 22 | BoA P | 186 | -0.53 |
| 23 | INVOLYS P | 101.6 | -0.39 |
| 24 | Immr Invest P | 106.85 | -0.14 |
Get intraday price data of a given symbol
Args:
companystr: Company name or ticker symbol(e.g. 'maroc telecom', 'MNG')
Returns:
pd.DataFrame: Dataframe of intraday price data
Example:
stm.get_data_intraday('CIH')| prices | |
|---|---|
| Datetime | |
| 2022-03-18 09:30:00 | 130.20 |
| 2022-03-18 10:02:00 | 131.00 |
| 2022-03-18 10:06:00 | 131.00 |
| 2022-03-18 10:07:00 | 131.00 |
| 2022-03-18 10:17:00 | 131.15 |
| 2022-03-18 10:24:00 | 131.15 |
| 2022-03-18 10:30:00 | 131.15 |
| 2022-03-18 10:41:00 | 131.40 |
| 2022-03-18 11:07:00 | 131.40 |
| 2022-03-18 11:15:00 | 131.40 |
| 2022-03-18 12:24:00 | 131.45 |
| 2022-03-18 12:31:00 | 131.40 |
| 2022-03-18 13:25:00 | 131.20 |
| 2022-03-18 14:48:00 | 131.25 |
| 2022-03-18 15:07:00 | 131.40 |
| 2022-03-18 15:19:00 | 131.25 |
| 2022-03-18 15:30:00 | 131.40 |
Get ask bid data of a given symbol
Args:
companystr: Company name or ticker symbol(e.g. 'maroc telecom', 'MNG')
Returns:
pd.DataFrame: Dataframe of ask bid data
Example:
stm.get_ask_bid('CIH')| bidValue | bidQte | askValue | askQte | bidOrder | askOrder | |
|---|---|---|---|---|---|---|
| 0 | 340.1 | 3 | 350.0 | 248 | 1 | 2 |
| 1 | 340.0 | 950 | 352.0 | 702 | 2 | 1 |
| 2 | 337.1 | 4 | 354.5 | 10 | 1 | 1 |
| 3 | 336.2 | 10 | 354.9 | 3 | 1 | 1 |
| 4 | 335.0 | 10 | 355.0 | 290 | 1 | 2 |
| 5 | 334.0 | 4 | 356.0 | 200 | 1 | 2 |
| 6 | 332.0 | 6 | 357.9 | 2 | 2 | 1 |
| 7 | 330.5 | 10 | 358.0 | 482 | 1 | 2 |
| 8 | 330.0 | 274 | 359.0 | 59 | 3 | 1 |
| 9 | 321.5 | 300 | 359.4 | 20 | 1 | 1 |
Get balance sheet data of a given symbol
Args:
companystr: Ticker symbol(e.g. 'IAM', 'MNG')frequencystr: Display either quarter or annual data. Defaults to "annual".
Returns:
pd.DataFrame: Dataframe of balance sheet data
Example:
# Annual balance sheet
stm.get_balance_sheet('ATW', frequency='annual')| 2017 | 2018 | 2019 | 2020 | 2021 | ||
|---|---|---|---|---|---|---|
| Item | ||||||
| Assets | Total Cash & Due from Banks | 18.22B | 18.54B | 24.73B | 26.33B | 25.74B |
| Cash & Due from Banks Growth | - | 1.71% | 33.42% | 6.48% | -2.26% | |
| Investments - Total | 116.38B | 119.86B | 123.75B | 137.55B | 158.73B | |
| Investments Growth | - | 2.99% | 3.25% | 11.15% | 15.40% | |
| Trading Account Securities | - | - | 54.32B | 58.67B | 69.91B | |
| ... | ... | ... | ... | ... | ... | |
| Liabilities & Shareholders' Equity | Total Shareholders' Equity / Assets | 8.40% | 8.73% | 8.94% | 8.41% | 8.80% |
| Return On Average Total Equity | - | - | - | - | 10.26% | |
| Accumulated Minority Interest | 6.44B | 5.95B | 6.3B | 6.49B | 7.34B | |
| Total Equity | 46.06B | 50.47B | 53.93B | 54.29B | 59.79B | |
| Liabilities & Shareholders' Equity | 471.47B | 509.93B | 532.6B | 568.11B | 596.33B |
[74 rows x 5 columns]
# Quarter balance sheet
stm.get_balance_sheet('ATW', frequency='quarter')| 30-Jun-2021 | 30-Sep-2021 | 31-Dec-2020 | 31-Dec-2021 | 31-Mar-2021 | ||
|---|---|---|---|---|---|---|
| Item | ||||||
| Assets | Total Cash & Due from Banks | 23.41B | 20.2B | 26.33B | 25.74B | 22.79B |
| Cash & Due from Banks Growth | 2.74% | -13.73% | - | 27.43% | -13.47% | |
| Investments - Total | 148.98B | 155.57B | 137.55B | 158.73B | 141.76B | |
| Investments Growth | 5.10% | 4.42% | - | 2.04% | 3.06% | |
| Trading Account Securities | 63.98B | 64.94B | 58.67B | 69.91B | 61.8B | |
| ... | ... | ... | ... | ... | ... | |
| Liabilities & Shareholders' Equity | Total Shareholders' Equity / Assets | 8.47% | 8.73% | 8.41% | 8.80% | 8.48% |
| Return On Average Total Equity | - | - | - | 10.26% | - | |
| Accumulated Minority Interest | 6.88B | 7.13B | 6.49B | 7.34B | 6.69B | |
| Total Equity | 56B | 58.29B | 54.29B | 59.79B | 54.45B | |
| Liabilities & Shareholders' Equity | 579.79B | 586.09B | 568.11B | 596.33B | 562.95B |
[74 rows x 5 columns]
Get income statement data of a given symbol
Args:
companystr: Ticker symbol(e.g. 'IAM', 'MNG')frequencystr: Display either quarter or annual data. Defaults to "annual".
Returns:
pd.DataFrame: Dataframe of income statement data
Example:
# Annual income statement
stm.get_income_statement('IAM', frequency='annual')| Item | 2017 | 2018 | 2019 | 2020 | 2021 |
|---|---|---|---|---|---|
| Sales/Revenue | 34.96B | 36.03B | 36.52B | 36.77B | 35.79B |
| Sales Growth | - | 3.06% | 1.35% | 0.69% | -2.66% |
| Cost of Goods Sold (COGS) incl. D&A | 15.69B | 15.72B | 16.19B | 15.93B | 15.05B |
| COGS Growth | - | 0.24% | 2.95% | -1.57% | -5.56% |
| COGS excluding D&A | 9.08B | 8.9B | 8.77B | 8.42B | 7.99B |
| Non Operating Income/Expense | (57M) | 201M | (49M) | (1.49B) | (165M) |
| ... | ... | ... | ... | ... | ... |
| Equity in Affiliates (Pretax) | - | - | - | - | - |
| Interest Expense | 586M | 642M | 756M | 888M | 826M |
| Interest Expense Growth | - | 9.56% | 17.76% | 17.46% | -6.98% |
| EBITDA | 17.03B | 17.87B | 15.65B | 19.53B | 18.63B |
| EBITDA Growth | - | 4.93% | -12.44% | 24.80% | -4.62% |
| EBITDA Margin | - | - | - | - | 52.05% |
# Quarter income statement
stm.get_income_statement('IAM', frequency='quarter')| Item | 31-Dec-2019 | 30-Jun-2020 | 31-Dec-2020 | 30-Jun-2021 | 31-Dec-2021 |
|---|---|---|---|---|---|
| Sales/Revenue | 18.67B | 18.32B | 18.45B | 17.78B | 18.01B |
| Sales Growth | - | -1.87% | 0.67% | -3.61% | 1.29% |
| Cost of Goods Sold (COGS) incl. D&A | 11.53B | 4.92B | 7.74B | 7.9B | 7.57B |
| COGS Growth | - | -57.33% | 57.23% | 2.02% | -4.08% |
| COGS excluding D&A | 4.42B | 4.16B | 4.26B | 4.09B | 3.91B |
| Depreciation & Amortization Expense | 7.12B | 759M | 3.48B | 3.81B | 3.67B |
| ... | ... | ... | ... | ... | ... |
| EBITDA | 9.49B | 6.6B | 9.66B | 9.37B | 9.68B |
| EBITDA Growth | - | -30.48% | 46.52% | -3.07% | 3.38% |
| EBITDA Margin | - | - | - | - | 53.76% |
Get cash flow data of a given symbol
Args:
companystr: Ticker symbol(e.g. 'IAM', 'MNG')frequencystr: Display either quarter or annual data. Defaults to "annual".
Returns:
pd.DataFrame: Dataframe of cash flow data
Example:
# Annual cash flow
stm.get_cash_flow('IAM', frequency='annual')| 2017 | 2018 | 2019 | 2020 | 2021 | ||
|---|---|---|---|---|---|---|
| Item | ||||||
| Operating Activities | Net Income before Extraordinaries | 10.31B | 11.05B | 8.23B | 12.02B | 11.57B |
| Net Income Growth | - | 7.20% | -25.52% | 46.01% | -3.70% | |
| Depreciation, Depletion & Amortization | 6.61B | 6.82B | 7.42B | 7.51B | 7.06B | |
| ... | ... | ... | ... | ... | ... | |
| Net Operating Cash Flow | 14.13B | 13.95B | 14.81B | 10.48B | 12.87B | |
| Net Operating Cash Flow Growth | - | -1.32% | 6.22% | -29.28% | 22.80% | |
| Net Operating Cash Flow / Sales | 40.42% | 38.71% | 40.57% | 28.49% | 35.95% | |
| Investing Activities | Capital Expenditures | (8.37B) | (8.08B) | (7.95B) | (4.14B) | (5.29B) |
| Capital Expenditures Growth | - | 3.52% | 1.56% | 47.91% | -27.75% | |
| Capital Expenditures / Sales | -23.94% | -22.41% | -21.77% | -11.26% | -14.78% | |
| ... | ... | ... | ... | ... | ... | |
| Net Investing Cash Flow | (8.07B) | (8.37B) | (8.83B) | (4.23B) | (5.31B) | |
| Net Investing Cash Flow Growth | - | -3.77% | -5.42% | 52.03% | -25.42% | |
| Net Investing Cash Flow / Sales | -23.07% | -23.23% | -24.17% | -11.51% | -14.83% | |
| Financing Activities | Cash Dividends Paid - Total | (5.6B) | (5.73B) | (6B) | (4.87B) | (3.53B) |
| Common Dividends | (5.6B) | (5.73B) | (6B) | (4.87B) | (3.53B) | |
| Preferred Dividends | - | - | - | - | - | |
| ... | ... | ... | ... | ... | ... | |
| Free Cash Flow | 5.76B | 5.87B | 6.87B | 6.34B | 7.58B | |
| Free Cash Flow Growth | - | 1.89% | 16.91% | -7.72% | 19.57% | |
| Free Cash Flow Yield | - | - | - | - | 3.30 |
# Quarter cash flow
stm.get_cash_flow('IAM', frequency='quarter')| 31-Dec-2019 | 30-Jun-2020 | 31-Dec-2020 | 30-Jun-2021 | 31-Dec-2021 | ||
|---|---|---|---|---|---|---|
| Item | ||||||
| Operating Activities | Net Income before Extraordinaries | 2.37B | 5.84B | 6.18B | 5.56B | 6.02B |
| Net Income Growth | - | 146.35% | 5.93% | -10.11% | 8.26% | |
| Depreciation, Depletion & Amortization | 3.81B | (759M) | 8.27B | 3.81B | 3.25B | |
| ... | ... | ... | ... | ... | ... | |
| Net Operating Cash Flow | 8.95B | 1.86B | 8.62B | 5.81B | 7.05B | |
| Net Operating Cash Flow Growth | - | -79.27% | 364.44% | -32.56% | 21.31% | |
| Net Operating Cash Flow / Sales | 47.94% | 10.13% | 46.73% | 32.69% | 39.16% | |
| Investing Activities | Capital Expenditures | (3.73B) | (2.29B) | (1.85B) | (2.74B) | (2.55B) |
| Capital Expenditures Growth | - | 38.69% | 18.93% | -47.57% | 6.65% | |
| Capital Expenditures / Sales | -19.98% | -12.48% | -10.05% | -15.39% | -14.18% | |
| ... | ... | ... | ... | ... | ... | |
| Net Investing Cash Flow | (3.56B) | (2.4B) | (1.84B) | (2.76B) | (2.55B) | |
| Net Investing Cash Flow Growth | - | 32.71% | 23.40% | -50.11% | 7.37% | |
| Net Investing Cash Flow / Sales | -19.08% | -13.08% | -9.95% | -15.50% | -14.18% | |
| Financing Activities | Cash Dividends Paid - Total | (271M) | - | (4.87B) | - | (3.53B) |
| Common Dividends | (271M) | - | (4.87B) | - | (3.53B) | |
| Preferred Dividends | - | - | - | - | - | |
| ... | ... | ... | ... | ... | ... | |
| Free Cash Flow | 5.22B | (431M) | 6.77B | 3.08B | 4.5B | |
| Free Cash Flow Growth | - | -108.25% | 1,669.84% | -54.52% | 46.18% | |
| Free Cash Flow Yield | - | - | - | - | 3.30 |
Get important data about a given symbol
Args:
companystr: Ticker symbol(e.g. 'IAM', 'MNG')
Returns:
pd.DataFrame: Dataframe of data about the ticker
Example:
stm.get_quote_table('ATW')| Key Data | Value | |
|---|---|---|
| 0 | Open | 473.00 |
| 1 | Day Range | 464.00 - 473.00 |
| 2 | 52 Week Range | N/A |
| 3 | Market Cap | 93.69B |
| 4 | Shares Outstanding | 215.14M |
| 5 | Public Float | 69.09M |
| 6 | Beta | N/A |
| 7 | Rev. per Employee | 1.933M |
| 8 | P/E Ratio | 18.04 |
| 9 | EPS | 25.72 |
| 10 | Yield | 3.23% |
| 11 | Dividend | 6.75 |
| 12 | Ex-Dividend Date | Jul 5, 2021 |
| 13 | Short Interest | N/A |
| 14 | % of Float Shorted | N/A |
| 15 | Average Volume | 160.21K |
Get status of the Moroccan market Returns:
str: Status of the market(Open/Closed)
Example:
stm.get_market_status()ClosedGet company officers of a given symbol
Args:
companystr: Ticker symbol(e.g. 'IAM', 'MNG')
Returns:
pd.DataFrame: Dataframe of names and roles of the officers
Example:
stm.get_company_officers('MNG')| Name | Role | |
|---|---|---|
| 0 | Imad Toumi | Chairman & Chief Executive Officer |
| 1 | Mouna Mahfoud | Executive Director-Finance |
| 2 | Naoual Zine | General Manager-Reminex & Projects |
| 3 | Lhou Maacha | Executive Director-Exploration |
| 4 | Youssef el Hajjam | General Manager-Bases Metal Operations |
| 5 | Karim Khettouch | Director |
| 6 | Samir Oudghiri Idrissi | Director |
| 7 | Bassim Jaï Hokimi | Director |
| 8 | Hassan Ouriagli | Director |
| 9 | Amina Benkhadra | Director |
| 10 | Noufissa Kessar | Director |
| 11 | Mohamed Amine Afsahi | Executive Director-Marketing & Commercial |
| 12 | Laila Karam | Investor Relations Contact |
| 13 | Zakaria Rbii | Executive Director-HR, Communication & Develop... |
| 14 | Frédéric Bernard Tona | Independent Director |
Get information related to the company's location, adresse...
Args:
companystr: Ticker symbol(e.g. 'IAM', 'MNG')
Returns:
pd.DataFrame: Dataframe of information related to the company (e.g. Name, Adresse, Phone...)
Example:
stm.get_company_info('MNG')| Item | Value | |
|---|---|---|
| 0 | Name | Managem |
| 1 | Adresse | Twin Center, Tower A Angle Boulevards Zerktoun... |
| 2 | Phone | +212 522 956-565 |
| 3 | Industry | General Mining |
| 4 | Sector | Basic Materials/Resources |
| 5 | Description | Managem SA engages in mining and hydrometallur... |
This project is licensed under the terms of the MIT license.