35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
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import numpy as np
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import pandas as pd
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def calculate_rsi(data: pd.DataFrame, period: int = 21) -> pd.Series:
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"""
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Calculate the RSI for a given period and return it as a Series.
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"""
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delta = data['Close'].diff()
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gain = np.where(delta > 0, delta, 0)
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loss = np.where(delta < 0, -delta, 0)
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alpha = 1 / period
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avg_gain = pd.Series(gain).ewm(alpha = alpha, adjust = False).mean()
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avg_loss = pd.Series(loss).ewm(alpha = alpha, adjust = False).mean()
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rs = avg_gain / avg_loss
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return 100 - (100 / (1 + rs))
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def calculate_ibs(data: pd.DataFrame) -> pd.Series:
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"""
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Calculate the IBS and return it as a Series.
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"""
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return (data['Close'] - data['Low']) / (data['High'] - data['Low'])
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def signals(data: pd.DataFrame) -> pd.Series:
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"""
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Generate swing trading signals based on the IBS + RSI strategy.
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Returns a Series with 'L' for long signals and 'N' otherwise.
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"""
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ibs = calculate_ibs(data)
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rsi_21 = calculate_rsi(data, period = 21)
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conditions = (ibs < 0.25) & (rsi_21 < 45)
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return pd.Series(np.where(conditions, 'L', 'N'), index = data.index)
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