In [2]:

    

import pandas as pd
import itable
import ffn
import talib

%matplotlib inline

def side_by_side(*objs, **kwds):
    from pandas.formats.printing import adjoin
    space = kwds.get('space', 4)
    reprs = [repr(obj).split('\n') for obj in objs]
    print (adjoin(space, *reprs))
    
import os
os.chdir('C:\\users\\scuba\\pycharmprojects\\simplebacktester')
os.getcwd()


    

    
Out[2]:





'C:\\users\\scuba\\pycharmprojects\\simplebacktester'

In [ ]:

    

import pandas as pd
import ffn

%matplotlib inline

from backtest_helpers.compute_weights_RS_DM import compute_weights_RS_DM
from backtest_helpers.compute_weights_PMA import compute_weights_PMA
from backtest_helpers.monthly_return_table import monthly_return_table
from backtest_helpers.endpoints import endpoints
from backtest_helpers.backtest import backtest

strategies = {
    'RS0001': { 'symbols': ['CWB','HYG','MBB','IEF','HYD'], 'prices': 'yahoo',  
               'rs_lookback': 1, 'risk_lookback': 1, 'n_top': 2, 'frequency': 'm',
              'cash_proxy': 'CASHX', 'risk_free': 0},
    'RS0002': {'symbols': ['HYD','QLTB','MBB'],  'prices': 'yahoo', 
               'rs_lookback': 3, 'risk_lookback': 2, 'n_top': 1, 'frequency': 'm',
              'cash_proxy': 'CASHX', 'risk_free': 0},
    'RS0003': {'symbols': ['HYD','MBB','SHY'], 'prices': 'yahoo', 
               'rs_lookback': 1, 'risk_lookback': 1, 'n_top': 1, 'frequency': 'q',
              'cash_proxy': 'CASHX', 'risk_free': 0},    
    'DM0001': {'symbols': ['CWB','VYM','HYG','VHT','TLT','MBB','HYD','IEF'],
                'prices': 'yahoo', 
               'rs_lookback': 1, 'risk_lookback': 1, 'n_top': 3, 'frequency': 'm',
              'cash_proxy': 'CASHX', 'risk_free': 'SHY'},
    'DM0002': {'symbols': ['CWB','TLT','HYG','VHT','VNQ'], 'prices': 'yahoo', 
               'rs_lookback': 1, 'risk_lookback': 1, 'n_top': 5, 'frequency': 'm',
              'cash_proxy': 'MBB', 'risk_free': 'SHY'},
    'PMA001': {'symbols': ['CWB','MBB'],  'prices': 'yahoo', 
               'risk_lookback': 3, 'frequency': 'm', 'allocations': [0.6, 0.4],
              'cash_proxy': 'TLT'},
    'PMA002': {'symbols': ['CWB','VYM','HYG'], 'prices': 'yahoo', 
               'risk_lookback': 3, 'frequency': 'm', 'allocations': [0.6, 0.2, 0.2],
              'cash_proxy': 'TLT'},
    'PMA003': {'symbols': ['VCVSX', 'FAGIX', 'VGHCX'], 'prices': 'yahoo',  
               'risk_lookback': 2, 'frequency': 'm', 'allocations': [1./3., 1./3., 1./3.],
              'cash_proxy': 'VUSTX'},    
}

strategy_values = pd.DataFrame(columns=strategies.keys())
security_weights = {}
security_holdings = {}
prices = {}

for name in strategies :
    if 'PMA' in name :
        s_value, s_holdings, s_weights, s_prices =  compute_weights_PMA (name, strategies[name])
    else :
        s_value, s_holdings, s_weights, s_prices =  compute_weights_RS_DM (name, strategies[name])
    
    strategy_values[name] = s_value
    security_weights[name] = s_weights
    security_holdings[name] = s_holdings
    prices[name] = s_prices