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* add yahoofinance undervalued & most shorted screeners * . * add chaikin osc to ta menu * follow up * .
103 lines
2.4 KiB
Python
103 lines
2.4 KiB
Python
"""Volume Technical Analysis"""
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__docformat__ = "numpy"
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import pandas as pd
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import pandas_ta as ta
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def ad(df_stock: pd.DataFrame, use_open: bool) -> pd.DataFrame:
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"""Calculate AD technical indicator
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Parameters
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----------
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df_stock : pd.DataFrame
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Dataframe of prices
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use_open : bool
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Whether to use open prices
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Returns
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-------
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pd.DataFrame
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Dataframe with techinical indicator
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"""
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if use_open:
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df_ta = ta.ad(
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high=df_stock["High"],
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low=df_stock["Low"],
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close=df_stock["Close"],
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volume=df_stock["Volume"],
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open_=df_stock["Open"],
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).dropna()
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# Do not use open stock values
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else:
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df_ta = ta.ad(
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high=df_stock["High"],
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low=df_stock["Low"],
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close=df_stock["Close"],
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volume=df_stock["Volume"],
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).dropna()
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return pd.DataFrame(df_ta)
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def adosc(df_stock: pd.DataFrame, use_open: bool, fast: int, slow: int) -> pd.DataFrame:
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"""Calculate AD oscillator technical indicator
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Parameters
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----------
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df_stock : pd.DataFrame
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Dataframe of prices
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use_open : bool
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Whether to use open prices
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Returns
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-------
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pd.DataFrame
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Dataframe with technical indicator
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"""
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if use_open:
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df_ta = ta.adosc(
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high=df_stock["High"],
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low=df_stock["Low"],
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close=df_stock["Close"],
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volume=df_stock["Volume"],
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open_=df_stock["Open"],
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fast=fast,
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slow=slow,
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).dropna()
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else:
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df_ta = ta.adosc(
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high=df_stock["High"],
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low=df_stock["Low"],
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close=df_stock["Close"],
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volume=df_stock["Volume"],
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fast=fast,
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slow=slow,
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).dropna()
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return pd.DataFrame(df_ta)
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def obv(s_interval: str, df_stock: pd.DataFrame) -> pd.DataFrame:
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"""On Balance Volume
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Parameters
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----------
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s_interval: str
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Stock data interval
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df_stock: pd.DataFrame
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Dataframe of stock prices
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Returns
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-------
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pd.DataFrame
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Dataframe with techinical indicator
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"""
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# Daily
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if s_interval == "1440min":
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df_ta = ta.obv(close=df_stock["Adj Close"], volume=df_stock["Volume"]).dropna()
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# Intraday
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else:
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df_ta = ta.obv(close=df_stock["Close"], volume=df_stock["Volume"]).dropna()
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return df_ta
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