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A Basic Markowitz portfolio of Stocks and Bonds.
Change it from 50/50 to 60/40 or 70/30.
from __future__ import division
import datetime
import pytz
import pandas as pd
from zipline.api import order_target_percent
def initialize(context):
context.secs = symbols( 'VTI', 'AGG') # Securities
context.pcts = [ 0.7, 0.3 ] # Percentages
context.ETFs = zip(context.secs, context.pcts)
# Check to rebalance every month, but only do it in December
date_rules.month_end(days_offset=5), # trade before EOY settlment dates
time_rules.market_open(minutes=45)) # trade after 10:15am
def rebalance(context, data):
threshold = 0.05 # trigger a rebalance if we are off by this threshold (5%)
# Get the current exchange time, in the exchange timezone
exchange_time = pd.Timestamp(get_datetime()).tz_convert('US/Eastern')
if exchange_time.month < 12:
return # bail if it's not December
need_full_rebalance = False
portfolio_value = context.portfolio.portfolio_value
# rebalance if we have too much cash
if / portfolio_value > threshold:
need_full_rebalance = True
# or rebalance if an ETF is off by the given threshold
for sid, target in context.ETFs:
pos = context.portfolio.positions[sid]
position_pct = (pos.amount * pos.last_sale_price) / portfolio_value
# if any position is out of range then rebalance the whole portfolio
if abs(position_pct - target) > threshold:
need_full_rebalance = True
break # don't bother checking the rest
# perform the full rebalance if we flagged the need to do so
if need_full_rebalance:
for sid, target in context.ETFs:
order_target_percent(sid, target)"Rebalanced at %s" % str(exchange_time))
context.rebalance_date = exchange_time
def handle_data(context, data):