scubamut

 pandas as pd
import numpy as np

# Assuming returns is your dataset with returns data
def calculate_correlations(returns, symbols, window=50):
    """
    Calculate rolling correlations between ETFs
    
    Parameters:
    returns: numpy array or pandas DataFrame of returns

scubamut

import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf

data = yf.download('QQQ', '2020-01-01', '2023-12-31')
daily_df   = data['Adj Close']

weekly_df  = daily_df.resample('W').mean()
monthly_df = daily_df.resample('BME').last()

scubamut

import pandas as pd
import yfinance as yf

etf = 'SPY'
# etf = 'QQQ
trend = "downtrend"
# trend = "uptrend"
window = 30
year = 2024

scubamut

#########################################################################
# US_stock_bundle
###############

# ~.zipline/extensions.py

#from zipline.data.bundles import register, US_stock_data
#
#register('US_stock_bundle', US_stock_data.US_stock_data, calendar_name='NYSE')

scubamut

# to ingest the etfs

import zipline
from zipline.data.bundles.core import register, ingest
import yfinance as yf
import pandas as pd
from datetime import datetime
import pytz

# FOR ALL ASSETS

scubamut

import sys

if 'ziptrader36' in sys.path[1]:
    active_kernel = 'ziptrader36'

elif 'zipline-reloaded' in sys.path[1]:
        active_kernel = 'zipline-reloaded'
else:
    active_kernel = 'not ziptrader36 or zipline-reloaded'
        

scubamut

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scubamut

import talib

# routine to get args required for talib function

def find_talib_args(func):
    s = eval('talib.' + func + '.__doc__')
    try:
        s = s.splitlines()[0].split('(')[1].split(')')[0].replace('[','').replace(']','').replace('?','')
        return s.split(',')
    except:

scubamut

from fintools import endpoints

# end_points prices (in this case, monthly)
end_points = endpoints(period='M', trading_days=prices_d.index)
prices_m = prices_d.loc[end_points]
prices_m[:2]

scubamut

etfs = [
    # ----------------------------------------- #
    # SPDRS/State Street Global Advisors (SSGA)
    'XLY',  # Select SPDR U.S. Consumer Discretionary
    'XLP',  # Select SPDR U.S. Consumer Staples
    'XLE',  # Select SPDR U.S. Energy
    'XLF',  # Select SPDR U.S. Financials
    'XLV',  # Select SPDR U.S. Healthcare
    'XLI',  # Select SPDR U.S. Industrials
    'XLB',  # Select SPDR U.S. Materials