diff --git a/strategies/two_period_rsi.py b/strategies/two_period_rsi.py index b589f40..34ff725 100644 --- a/strategies/two_period_rsi.py +++ b/strategies/two_period_rsi.py @@ -1,35 +1,15 @@ -import numpy as np - +from numpy import where from pandas import DataFrame, Series -def calculate_moving_average(data: DataFrame, window: int = 200) -> Series: - """ - Calculate the 200-period moving average and return it as a Series without modifying the original DataFrame. - """ - return data['Close'].rolling(window = window).mean() - -def calculate_rsi(data: DataFrame, period: int = 2) -> Series: - """ - Calculate the 2-period RSI and return it as a Series without modifying the original DataFrame. - """ - delta = data['Close'].diff() - gain = np.where(delta > 0, delta, 0) - loss = np.where(delta < 0, -delta, 0) - - alpha = 1 / period - avg_gain = Series(gain).ewm(alpha = alpha, adjust = False).mean() - avg_loss = Series(loss).ewm(alpha = alpha, adjust = False).mean() - - rs = avg_gain / avg_loss - return 100 - (100 / (1 + rs)) +from indicators import rsi, sma def two_period_rsi(data: DataFrame) -> Series: """ Calculate signals based on the 200-period MA and 2-period RSI. Returns a Series with 'Long' for signals and 'None' otherwise, without modifying the original DataFrame. """ - ma_200 = calculate_moving_average(data) - rsi_2 = calculate_rsi(data) + ma_200 = sma(data, period = 200) + rsi_2 = rsi(data, period = 2) conditions = (data['Close'] > ma_200) & (rsi_2 < 15) - return Series(np.where(conditions, 'L', 'N'), index = data.index) \ No newline at end of file + return Series(where(conditions, 'L', 'N'), index = data.index) \ No newline at end of file