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82 lines
2.3 KiB
Python
82 lines
2.3 KiB
Python
"""Custom Indicator Models"""
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__docformat__ = "numpy"
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from typing import Any, Tuple
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import pandas as pd
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def calculate_fib_levels(
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df_stock: pd.DataFrame, period: int, open_date: Any, close_date: Any
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) -> Tuple[pd.DataFrame, pd.Timestamp, pd.Timestamp, float, float]:
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"""Calculate Fibonacci levels
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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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period : int
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Days to look back for retracement
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open_date : Any
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Custom start date for retracement
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close_date : Any
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Custom end date for retracement
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Returns
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-------
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df : pd.DataFrame
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Dataframe of fib levels
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min_date: pd.Timestamp
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Date of min point
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max_date: pd.Timestamp:
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Date of max point
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min_pr: float
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Price at min point
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max_pr: float
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Price at max point
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"""
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if open_date and close_date:
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if open_date not in df_stock.index:
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date0 = df_stock.index[df_stock.index.get_loc(open_date, method="nearest")]
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print(f"Start date not in df_stock. Using nearest: {date0}")
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else:
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date0 = open_date
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if close_date not in df_stock.index:
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date1 = df_stock.index[df_stock.index.get_loc(close_date, method="nearest")]
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print(f"End date not in df_stock. Using nearest: {date1}")
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else:
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date1 = close_date
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df_stock0 = df_stock.loc[date0, "Adj Close"]
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df_stock1 = df_stock.loc[date1, "Adj Close"]
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min_pr = min(df_stock0, df_stock1)
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max_pr = max(df_stock0, df_stock1)
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if min_pr == df_stock0:
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min_date = date0
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max_date = date1
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else:
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min_date = date1
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max_date = date0
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else:
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data_to_use = df_stock.iloc[period:]["Adj Close"]
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min_pr = data_to_use.min()
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min_date = data_to_use.idxmin()
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max_pr = data_to_use.max()
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max_date = data_to_use.idxmax()
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fib_levels = [0, 0.235, 0.382, 0.5, 0.618, 1]
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price_dif = max_pr - min_pr
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levels = [round(max_pr - price_dif * f_lev, 2) for f_lev in fib_levels]
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df = pd.DataFrame()
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df["Level"] = fib_levels
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df["Level"] = df["Level"].apply(lambda x: str(x * 100) + "%")
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df["Price"] = levels
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return df, min_date, max_date, min_pr, max_pr
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