Module Information

Description: Equities Assets class for QuantJourney Framework

The Equities module is a crucial component of the QuantJourney Framework, specifically tailored for handling and managing equity data for quantitative analysis and algorithmic trading in hedge funds. This module emphasizes the importance of accessing a wide range of equity data, including historical and intraday market data, corporate actions, and financial news, through various data sources like EOD Historical Data, Yahoo Finance, and OANDA.

Author: jpolec

Date: 27-02-2024 and 18-03-2024

Class: Equities()

Method: get_us_securities

def get_us_securities() -> pd.DataFrame

Get a list of all US securities from EODHistoricalData.

Examples:

sec = dc.self.connectors['eod'].get_us_securities()

US Securities:              Code  ...          Isin
0      0P0000A412  ...          None
1      0P0000RX5G  ...          None
2      0P0001GXZ7  ...          None
3      0P0001NGF5  ...          None
4               A  ...  US00846U1016
...           ...  ...           ...
47987        ZYME  ...  CA98985W1023
47988        ZYXI  ...  US98986M1036
47989       ZZHGF  ...          None
47990       ZZHGY  ...          None
47991       ZZZOF  ...          None

Returns:

Type	Description
`pd.DataFrame`	Code, Name, Country, Exchange, Currency, Type, Isin

Method: async_get_ticker_historical_mcap

def async_get_ticker_historical_mcap(
            ticker: str,
            exchange: str ="US"
        ) -> pd.DataFrame

Get historical market capitalization for a ticker

Examples:

mcap = await dc.equities.async_get_ticker_historical_mcap("AAPL")

Parameters:

Name	Type	Description
`ticker`	`str`	the stock ticker
`exchange`	`str`	the stock exchange

Returns:

Type	Description
`pd.DataFrame`	the historical market capitalization data

Method: async_get_ticker_nearby_earnings

def async_get_ticker_nearby_earnings(
            ticker: str,
            exchange: str ="US"
        ) -> pd.DataFrame

Get nearby earnings for a ticker

Examples:

earnings = await dc.equities.async_get_ticker_nearby_earnings("AAPL")

Nearby Earnings:       code report_date        date  ... estimate difference  percent
0  AAPL.US  2023-05-04  2023-03-31  ...     1.43       0.09   6.2937
1  AAPL.US  2023-08-03  2023-06-30  ...     1.19       0.07   5.8824
2  AAPL.US  2023-11-02  2023-09-30  ...     1.39       0.07   5.0360
3  AAPL.US  2024-02-01  2023-12-31  ...     2.10       0.08   3.8095
4  AAPL.US  2024-05-02  2024-03-31  ...     1.50        NaN      NaN
5  AAPL.US  2024-08-01  2024-06-30  ...      NaN        NaN      NaN
6  AAPL.US  2024-10-31  2024-09-30  ...      NaN        NaN      NaN
7  AAPL.US  2025-02-27  2024-12-31  ...      NaN        NaN      NaN

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange

Returns:

Type	Description
`pd.DataFrame`	the nearby earnings data

Method: async_get_nearby_ipos

def async_get_nearby_ipos() -> pd.DataFrame

Get nearby IPOs, i.e., Initial Public Offerings

Examples:

ipos = await dc.equities.async_get_nearby_ipos()

Returns:

Type	Description
`pd.DataFrame`	the nearby IPOs data

Method: async_get_nearby_splits

def async_get_nearby_splits() -> pd.DataFrame

Get nearby stock splits

Examples:

splits = await dc.equities.async_get_nearby_splits()

Nearby Splits:               code  split_date optionable  old_shares  new_shares
0     CANTABIL.BSE  2023-11-02          N           1           5
1          MOTS.US  2023-11-02          N          15           1
2            VR.CN  2023-11-02          N           3           1
3     CANTABIL.NSE  2023-11-02          N           1           5
4         VRCFD.US  2023-11-02          N           3           1
...            ...         ...        ...         ...         ...
1965       3AG1.BE  2024-09-27          N           1          10
1966      9434.TSE  2024-09-27          N           1          10
1967      3AG1.STU  2024-09-27          N           1          10
1968        3AG1.F  2024-09-27          N           1          10
1969      9534.TSE  2024-09-27          N           1           5

Returns:

Type	Description
`pd.DataFrame`	the nearby stock splits data

Method: async_get_ticker_earnings_trend

def async_get_ticker_earnings_trend(
            ticker: str,
            exchange: str ="US"
        ) -> pd.DataFrame

Get earnings trend for a ticker, i.e., the earnings trend for the last 90 days

Examples:

trend = await dc.equities.async_get_ticker_earnings_trend("AAPL")

Earnings Trend: code                                            AAPL.US
date                                2025-09-30 00:00:00
period                                              +1y
growth                                           0.0920
earningsEstimateAvg                              7.1300
earningsEstimateLow                              6.5100
earningsEstimateHigh                             7.7000
earningsEstimateYearAgoEps                       6.5300
earningsEstimateNumberOfAnalysts                39.0000
earningsEstimateGrowth                           0.0920
revenueEstimateAvg                      410879000000.00
revenueEstimateLow                      386715000000.00
revenueEstimateHigh                     436241000000.00
revenueEstimateYearAgoEps                          None
revenueEstimateNumberOfAnalysts                   37.00
revenueEstimateGrowth                            0.0650
epsTrendCurrent                                  7.1300
epsTrend7daysAgo                                 7.1300
epsTrend30daysAgo                                7.1600
epsTrend60daysAgo                                7.1700
epsTrend90daysAgo                                7.1700
epsRevisionsUpLast7days                          0.0000
epsRevisionsUpLast30days                         1.0000
epsRevisionsDownLast30days                       2.0000

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange

Returns:

Type	Description
`pd.DataFrame`	the earnings trend data

Method: async_get_historical_splits

def async_get_historical_splits(
            ticker: str,
            exchange: str ="US"
        ) -> pd.DataFrame

Get historical stock splits for a ticker, i.e., the historical stock splits data

Examples:

splits = await dc.equities.async_get_historical_splits("AAPL")

Historical Splits:
date        split
1987-06-16  2.000000/1.000000
2000-06-21  2.000000/1.000000
2005-02-28  2.000000/1.000000
2014-06-09  7.000000/1.000000
2020-08-31  4.000000/1.000000

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange

Returns:

Type	Description
`pd.DataFrame`	the historical stock splits data

Method: async_get_historical_dividends

def async_get_historical_dividends(
            ticker: str,
            exchange: str ="US"
        ) -> pd.DataFrame

Get historical dividends for a ticker

Examples:

dividends = await dc.equities.async_get_historical_dividends("AAPL")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange

Returns:

Type	Description
`pd.DataFrame`	the historical dividends data

Method: async_get_equity_news

def async_get_equity_news(
            ticker: str ="",
            exchange: str ="US",
            tag: str ="",
            period_end=datetime.now(pytz.utc
        ) -> pd.DataFrame

Get news for a ticker

Examples:

news = await dc.equities.async_get_equity_news("AAPL")

Equity News:
date                                                                          ...
2024-04-29T09:06:00+00:00  4 Artificial Intelligence (AI) Stocks Members ...  ...  0.112
2024-04-29T09:50:00+00:00  Prediction: This Will Be Warren Buffett's Seco...  ...  0.105
2024-04-29T13:00:00+00:00  Here's How Much Stock Apple Repurchased in the...  ...  0.156
2024-04-29T13:48:00+00:00  These Stocks Are Moving the Most Today: Tesla,...  ...  0.113
2024-04-29T14:26:52+00:00  12 Under-the-Radar Stocks With Massive Upside ...  ...  0.135
2024-04-29T15:58:39+00:00  US STOCKS-Wall St edges up as Tesla and Apple ...  ...  0.094
2024-04-29T16:16:57+00:00  US Benchmark Equity Indexes Extend Gains in Mi...  ...  0.369
2024-04-29T16:47:00+00:00  Should You Buy Apple (AAPL) Stock Ahead of Q2 ...  ...  0.112
2024-04-29T17:28:23+00:00  What Would Happen If Warren Buffett Bailed On ...  ...  0.144
2024-04-29T17:49:01+00:00   Tesla, Apple Help US Equity Indexes Extend Gains  ...  0.576
2024-04-29T19:10:54+00:00  US STOCKS-Wall Street stocks gain as investors...  ...  0.093
2024-04-29T19:13:12+00:00  Apple shares gain ground after Bernstein analy...  ...  0.098

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`tag`	`str`	The news tag
`period_end`	`datetime`	The end date for the period
`period_days`	`int`	The number of days for the period
`limit`	`int`	The number of news items to fetch

Returns:

Type	Description
`pd.DataFrame`	the news data

Method: async_get_ohlcv

def async_get_ohlcv(
            tickers: List[str],
            exchanges: List[str],
            source : str,
            granularity: str = "1d",
            period_starts: List[str] = None,
            period_ends: List[str] = None,
            db_name: Optional[str] = None,
            read_from_db: bool = False,
            write_to_db: bool = False
        ) -> List[pd.DataFrame]

Async get historical OHLCV data for stock tickers. All tickers, exchanges, and period_starts, period_ends are expected to be lists of the same length. Please note read_db and write_db are require running DB; otherwise, it will raise an error, unless set as False. You can specify different source: eod, yf, oanda, etc.

Examples:

ohlcv_data = await dc.equities.async_get_ohlcv(
tickers=["AAPL", "MSFT"],
exchanges=["US", "US"],
source="eod",
granularity="1d",
period_starts=["2023-01-01", "2023-01-01"],
period_ends=["2023-12-31", "2023-12-31"],
read_from_db=False,
write_to_db=False
)

OHLCV data: [                     datetime    open    high  ...   close  adj_close     volume
0   2023-01-03 00:00:00+00:00  130.28  130.90  ...  125.07   124.2163  112117500
1   2023-01-04 00:00:00+00:00  126.89  128.66  ...  126.36   125.4975   89113600
2   2023-01-05 00:00:00+00:00  127.13  127.77  ...  125.02   124.1666   80962700
3   2023-01-06 00:00:00+00:00  126.01  130.29  ...  129.62   128.7352   87754700
4   2023-01-09 00:00:00+00:00  130.47  133.41  ...  130.15   129.2616   70790800
..                        ...     ...     ...  ...     ...        ...        ...
245 2023-12-22 00:00:00+00:00  195.18  195.41  ...  193.60   193.3533   37122800
246 2023-12-26 00:00:00+00:00  193.61  193.89  ...  193.05   192.8040   28919300
247 2023-12-27 00:00:00+00:00  192.49  193.50  ...  193.15   192.9038   48087700
248 2023-12-28 00:00:00+00:00  194.14  194.66  ...  193.58   193.3333   34049900
249 2023-12-29 00:00:00+00:00  193.90  194.40  ...  192.53   192.2846   42628800

Parameters:

Name	Type	Description
`tickers`	`list of str`	List of stock tickers
`exchanges`	`list of str`	List of stock exchanges corresponding to tickers
`source`	`str`	Data source for connectors (e.g., "yf", "eod", "oanda", etc.)
`granularity`	`str`	Granularity for the OHLCV data ('1d', '1h', '15m', '5m', '1m')
`period_starts`	`list of str`	List of start dates for the OHLCV data
`period_ends`	`list of str`	List of end dates for the OHLCV data
`db_name`	`str`	Database name to read from/write to (e.g. Mongo)
`read_from_db`	`bool`	Read from database
`write_to_db`	`bool`	Write to database

Returns:

Type	Description
`List[pd.DataFrame]`	List of OHLCV DataFrames for each ticker

Method: async_get_live_lagged_prices

def async_get_live_lagged_prices(
            tickers: List[str],
            exchanges: List[str],
            source: str
        ) -> dict

Asynchronously fetches live and lagged prices for the given tickers and exchanges. You can specify different source: eod, yf, oanda, etc.

Examples:

prices = await dc.equities.async_get_live_lagged_prices(
tickers=["AAPL", "MSFT"],
exchanges=["US", "US"],
source="eod"
)

Parameters:

Name	Type	Description
`tickers`	`list of str`	List of stock tickers.
`exchanges`	`list of str`	List of stock exchanges corresponding to tickers.
`source`	`str`	Data source for connectors (e.g., "yf", "eod", "oanda", etc.).

Returns:

Type	Description
`dict`	dictionary containing live and lagged prices DataFrames for each ticker.

Method: async_get_intraday_data

def async_get_intraday_data(
            tickers: List[str],
            exchanges: List[str],
            source: str,
            interval: str = "5m",
            to_utc: Optional[datetime] = None,
            period_days: int = 120
        ) -> dict

Asynchronously fetches intraday data for the given tickers and exchanges. You can specify different source: eod, yf, oanda, etc. Interval options: '1m', '5m', '15m', '30m', '1h'.

Examples:

intraday_data = await dc.equities.async_get_intraday_data(
tickers=["AAPL", "MSFT"],
exchanges=["US", "US"],
source="eod",
interval="5m",
to_utc=datetime.utcnow(),
period_days=120
)

Parameters:

Name	Type	Description
`tickers`	`list of str`	List of stock tickers
`exchanges`	`list of str`	List of stock exchanges corresponding to tickers
`source`	`str`	Data source for connectors (e.g., "yf", "eod", "oanda", etc.)
`interval`	`str`	Interval for the intraday data ('1m', '5m', '15m', '30m', '1h')
`to_utc`	`datetime`	End date and time in UTC. Defaults to current UTC time
`period_days`	`int`	Number of days for the data period

Returns:

Type	Description
`dict`	dictionary containing intraday data DataFrames for each ticker.

Method: async_get_fundamental_data

def async_get_fundamental_data(
            ticker: str,
            exchange: str = "US",
            source: str = "eod",
            statement_type: Optional[str] = None,
            period: Union[str,
            int,
            None] = None,
            specific_date: Optional[str] = None,
            db_name: Optional[str] = None,
            read_from_db: bool = False,
            write_to_db: bool = False
        ) -> Union[Dict, pd.DataFrame]

Async get fundamental data (income statement, cash flow, balance sheet) for a stock ticker. Reads from the database if read_from_db is True, otherwise fetches from the data source. Writes to the database if write_to_db is True.

Examples:

fundamental_data = await dc.equities.async_get_fundamental_data("AAPL", "US", "eod", "income_statement", "y")
async_get_funamental_data("AAPL", "US", "eod", "income_statement", "y")
async_get_funamental_data("AAPL", "US", "eod", "cash_flow", "q")
async_get_funamental_data("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)
`statement_type`	`str`	The type of fundamental data (income_statement, cash_flow, balance_sheet)
`period`	`str, int`	The period for the fundamental data (e.g., 'y', 'q', 1, 4)
`specific_date`	`str`	The specific date for the fundamental data
`db_name`	`str`	Database name to read from/write to (e.g. Mongo)
`read_from_db`	`bool`	Read from database
`write_to_db`	`bool`	Write to database

Returns:

Type	Description
`Union[Dict, pd.DataFrame]`	the fundamental data

Method: async_get_income_statement

def async_get_income_statement(
            ticker: str,
            exchange: str,
            option: str = "q",
            source: str = "eod"
        ) -> pd.DataFrame

Get income statement for a ticker.

Examples:

income_statement = await dc.equities.async_get_income_statement("AAPL", "US", "q", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`option`	`str`	The period option (q - quarterly, y - yearly)
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the income statement data

Method: async_get_balance_sheet

def async_get_balance_sheet(
            ticker: str,
            exchange: str,
            option: str = "q",
            source: str = "eod"
        ) -> pd.DataFrame

Get balance sheet for a ticker.

Examples:

balance_sheet = await dc.equities.async_get_balance_sheet("AAPL", "US", "q", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`option`	`str`	The period option (q - quarterly, y - yearly)
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	pd.DataFrame, The balance sheet data

Method: async_get_cash_flow

def async_get_cash_flow(
            ticker: str,
            exchange: str,
            option: str = "q",
            source: str = "eod"
        ) -> pd.DataFrame

Get cash flow for a ticker.

Examples:

cash_flow = await dc.equities.async_get_cash_flow("AAPL", "US", "q", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`option`	`str`	The period option (q - quarterly, y - yearly)
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the cash flow data

Method: async_get_ticker_highlights

def async_get_ticker_highlights(
            ticker: str,
            exchange: str,
            source: str = "eod"
        ) -> pd.DataFrame

Get ticker highlights.

Examples:

highlights = await dc.equities.async_get_ticker_highlights("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	pd.DataFrame, The ticker highlights data

Method: async_get_ticker_mcap

def async_get_ticker_mcap(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker market capitalization.

Examples:

mcap = await dc.equities.async_get_ticker_mcap("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker market capitalization data

Method: async_get_ticker_ebitda

def async_get_ticker_ebitda(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker EBITDA.

Examples:

ebitda = await dc.equities.async_get_ticker_ebitda("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker EBITDA data

Method: async_get_ticker_pe

def async_get_ticker_pe(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker PE.

Examples:

pe = await dc.equities.async_get_ticker_pe("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	pd.DataFrame, The ticker PE data

Method: async_get_ticker_peg

def async_get_ticker_peg(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker PEG.

Examples:

peg = await dc.equities.async_get_ticker_peg("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker PEG data

Method: async_get_ticker_book

def async_get_ticker_book(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker book.

Examples:

book = await dc.equities.async_get_ticker_book("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	pd.DataFrame, The ticker book data

Method: async_get_ticker_div_ps

def async_get_ticker_div_ps(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker div ps.

Examples:

div_ps = await dc.equities.async_get_ticker_div_ps("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker div ps data

Method: async_get_ticker_div_yield

def async_get_ticker_div_yield(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker div yield.

Examples:

div_yield = await dc.equities.async_get_ticker_div_yield("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker div yield data

Method: async_get_ticker_eps

def async_get_ticker_eps(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker EPS.

Examples:

eps = await dc.equities.async_get_ticker_eps("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker EPS data

Method: async_get_ticker_last_quarter_date

def async_get_ticker_last_quarter_date(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker last quarter date.

Examples:

last_quarter_date = await dc.equities.async_get_ticker_last_quarter_date("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	pd.DataFrame, The ticker last quarter date data

Method: async_get_ticker_profit_margin

def async_get_ticker_profit_margin(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker profit margin.

Examples:

profit_margin = await dc.equities.async_get_ticker_profit_margin("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker profit margin data

Method: async_get_ticker_op_marginTTM

def async_get_ticker_op_marginTTM(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker op margin TTM (Operating Margin TTM)

Examples:

op_marginTTM = await dc.equities.async_get_ticker_op_marginTTM("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker op margin TTM data

Method: async_get_ticker_roaTTM

def async_get_ticker_roaTTM(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker ROA TTM (Return on Assets TTM)

Examples:

roaTTM = await dc.equities.async_get_ticker_roaTTM("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker ROA TTM data

Method: async_get_ticker_roeTTM

def async_get_ticker_roeTTM(
            ticker: str,
            exchange: str,
            source: str = "eod",fundamental_data=None
        ) -> pd.DataFrame

Get ticker ROE TTM (Return on Equity TTM)

Examples:

roeTTM = await dc.equities.async_get_ticker_roeTTM("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker ROE TTM data

Method: async_get_ticker_revenueTTM

def async_get_ticker_revenueTTM(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker revenue TTM

Examples:

revenueTTM = await dc.equities.async_get_ticker_revenueTTM("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker revenue TTM data

Method: async_get_ticker_revenue_psTTM

def async_get_ticker_revenue_psTTM(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker revenue ps TTM.

Examples:

revenue_psTTM = await dc.equities.async_get_ticker_revenue_psTTM("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker revenue ps TTM data

Method: async_get_ticker_qoq_rev_growth

def async_get_ticker_qoq_rev_growth(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker QoQ revenue growth.

Examples:

qoq_rev_growth = await dc.equities.async_get_ticker_qoq_rev_growth("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker QoQ revenue growth data

Method: async_get_ticker_qoq_earnings_growth

def async_get_ticker_qoq_earnings_growth(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker QoQ earnings growth.

Examples:

qoq_earnings_growth = await dc.equities.async_get_ticker_qoq_earnings_growth("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker QoQ earnings growth data

Method: async_get_ticker_gross_profitTTM

def async_get_ticker_gross_profitTTM(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker gross profit TTM.

Examples:

gross_profitTTM = await dc.equities.async_get_ticker_gross_profitTTM("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker gross profit TTM data

Method: async_get_ticker_diluted_epsTTM

def async_get_ticker_diluted_epsTTM(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker diluted EPS TTM (Earnings Per Share TTM).

Examples:

diluted_epsTTM = await dc.equities.async_get_ticker_diluted_epsTTM("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker diluted EPS TTM data

Method: async_get_ticker_analyst_target

def async_get_ticker_analyst_target(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker analyst target.

Examples:

analyst_target = await dc.equities.async_get_ticker_analyst_target("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker analyst target data

Method: async_get_ticker_sharestats

def async_get_ticker_sharestats(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker share stats.

Examples:

sharestats = await dc.equities.async_get_ticker_sharestats("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker share stats data

Method: async_get_ticker_shortratio

def async_get_ticker_shortratio(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker short ratio.

Examples:

shortratio = await dc.equities.async_get_ticker_shortratio("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker short ratio data

Method: async_get_ticker_percentinsiders

def async_get_ticker_percentinsiders(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker percent insiders.

Examples:

percentinsiders = await dc.equities.async_get_ticker_percentinsiders("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker percent insiders data

Method: async_get_ticker_valuation

def async_get_ticker_valuation(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker valuation.

Examples:

valuation = await dc.equities.async_get_ticker_valuation("AAPL", "US", "eod")

Ticker Valuation: {'TrailingPE': 26.3297, 'ForwardPE': 26.3158, 'PriceSalesTTM': 6.778,
'PriceBookMRQ': 35.4267, 'EnterpriseValue': 2649250332672, 'EnterpriseValueRevenue': 6.8966,
'EnterpriseValueEbitda': 19.929}

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker valuation data

Method: async_get_ticker_trailing_pe

def async_get_ticker_trailing_pe(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker trailing PE (Price to Earnings).

Examples:

trailing_pe = await dc.equities.async_get_ticker_trailing_pe("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker trailing PE data

Method: async_get_ticker_forward_pe

def async_get_ticker_forward_pe(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker forward PE (Price to Earnings).

Examples:

forward_pe = await dc.equities.async_get_ticker_forward_pe("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker forward PE data

Method: async_get_ticker_price_to_sales

def async_get_ticker_price_to_sales(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker price to sales.

Examples:

price_to_sales = await dc.equities.async_get_ticker_price_to_sales("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker price to sales data

Method: async_get_ticker_price_to_book

def async_get_ticker_price_to_book(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker price to book.

Examples:

price_to_book = await dc.equities.async_get_ticker_price_to_book("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker price to book data

Method: async_get_ticker_ev

def async_get_ticker_ev(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker enterprise value.

Examples:

ev = await dc.equities.async_get_ticker_ev("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker enterprise value data

Method: async_get_ticker_ev_revenue

def async_get_ticker_ev_revenue(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker enterprise value to revenue.

Examples:

ev_revenue = await dc.equities.async_get_ticker_ev_revenue("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker enterprise value to revenue data

Method: async_get_ticker_ev_ebitda

def async_get_ticker_ev_ebitda(
            ticker: str,
            exchange: str,
            source: str = "eod",
            fundamental_data=None
        ) -> pd.DataFrame

Get ticker enterprise value to EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization).

Examples:

ev_ebitda = await dc.equities.async_get_ticker_ev_ebitda("AAPL", "US", "eod")

Parameters:

Name	Type	Description
`ticker`	`str`	The stock ticker
`exchange`	`str`	The stock exchange
`source`	`str`	The data source (eod, yf, etc.)

Returns:

Type	Description
`pd.DataFrame`	the ticker enterprise value to EBITDA data