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

VSCode Shortcuts

List of helpful shortcuts for faster coding

If you have any other helpful shortcuts, feel free to add in the comments of this gist :)

Official List of all commands

• Windows
• Mac

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

scubamut

import matplotlib.pylab as plt
plt.rc('figure', figsize=(8, 5))
plt.style.use('seaborn-dark')

scubamut

import pandas_datareader.data as pdr
import matplotlib.pyplot as plt
import pandas as pd
from datetime import datetime, timezone
import pytz
import talib
import itable
import ffn

from fintools import get_DataArray,compute_weights_RS_DM,compute_weights_PMA,\

scubamut

import pandas_datareader.data as pdr
import matplotlib.pyplot as plt
import pandas as pd
from datetime import datetime, timezone
import pytz
import talib
import itable
import ffn

from fintools import get_DataArray,compute_weights_RS_DM,compute_weights_PMA,\

scubamut

##################################################
# DUAL MOMENTUM
###############

strategy_prices = strategy_values.dropna().copy()
# need to add prices for cash_proxy and, if necessary, risk_free

d = get_DataArray(['FFXSX'],start,end).to_pandas().transpose(1,2,0)
strategy_prices['FFXSX'] = d[:,:,'adj close'].loc[s_prices.index]

scubamut

"""
MSMP v6.00 Major Upgrade

- single RS momentum portfolio with downside protection
- RAA - Robust Asset Allocation (4 portfolios)
- minimumn correlation strategy
- downside protection strategy based on Alpha Architect DPM Rule: 50% TMOM, 50% MA
- RS with downside protection, single portfolio, EtfReplay-like ranking formula
- RS with 2 portfolios based on EtfReplay ranking model
- EAA - Elastic Asset Allocation