Forked from yongghongg/squeeze-momentum-indicator-general.py
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May 1, 2022 19:50
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# import required libraries | |
import pandas as pd | |
import yfinance as yf | |
import numpy as np | |
import math | |
# get stock prices | |
df = yf.download('AAPL', start='2020-01-01', threads= False) | |
# parameter setup | |
length = 20 | |
mult = 2 | |
length_KC = 20 | |
mult_KC = 1.5 | |
# calculate BB | |
m_avg = df['Close'].rolling(window=length).mean() | |
m_std = df['Close'].rolling(window=length).std(ddof=0) | |
df['upper_BB'] = m_avg + mult * m_std | |
df['lower_BB'] = m_avg - mult * m_std | |
# calculate true range | |
df['tr0'] = abs(df["High"] - df["Low"]) | |
df['tr1'] = abs(df["High"] - df["Close"].shift()) | |
df['tr2'] = abs(df["Low"] - df["Close"].shift()) | |
df['tr'] = df[['tr0', 'tr1', 'tr2']].max(axis=1) | |
# calculate KC | |
range_ma = df['tr'].rolling(window=length_KC).mean() | |
df['upper_KC'] = m_avg + range_ma * mult_KC | |
df['lower_KC'] = m_avg - range_ma * mult_KC | |
# calculate bar value | |
highest = df['High'].rolling(window = length_KC).max() | |
lowest = df['Low'].rolling(window = length_KC).min() | |
m1 = (highest + lowest)/2 | |
df['value'] = (df['Close'] - (m1 + m_avg)/2) | |
fit_y = np.array(range(0,length_KC)) | |
df['value'] = df['value'].rolling(window = length_KC).apply(lambda x: | |
np.polyfit(fit_y, x, 1)[0] * (length_KC-1) + | |
np.polyfit(fit_y, x, 1)[1], raw=True) | |
# check for 'squeeze' | |
df['squeeze_on'] = (df['lower_BB'] > df['lower_KC']) & (df['upper_BB'] < df['upper_KC']) | |
df['squeeze_off'] = (df['lower_BB'] < df['lower_KC']) & (df['upper_BB'] > df['upper_KC']) | |
# buying window for long position: | |
# 1. black cross becomes gray (the squeeze is released) | |
long_cond1 = (df['squeeze_off'][-2] == False) & (df['squeeze_off'][-1] == True) | |
# 2. bar value is positive => the bar is light green k | |
long_cond2 = df['value'][-1] > 0 | |
enter_long = long_cond1 and long_cond2 | |
# buying window for short position: | |
# 1. black cross becomes gray (the squeeze is released) | |
short_cond1 = (df['squeeze_off'][-2] == False) & (df['squeeze_off'][-1] == True) | |
# 2. bar value is negative => the bar is light red | |
short_cond2 = df['value'][-1] < 0 | |
enter_short = short_cond1 and short_cond2 |
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