Hi,

I found some differnces between running this simple code on Zipline on my MacBook and Quantopian.

The difference between the Benchmark and the strategie is quite significant on my Zipline installation.
I do not understand why this should not be exact matching lines. basically they are on Quantopian.

Do you get the same issue, or is it just my installation?

ThankX

import zipline  
from zipline.api import (set_max_leverage, set_slippage, set_commission, order_target_percent,  
symbol, schedule_function, date_rules, time_rules, set_benchmark)

from datetime import datetime  
from zipline.finance.commission import PerDollar, PerShare  
from zipline.finance.slippage import VolumeShareSlippage

intial_portfolio = 100000

def initialize(context):

    set_benchmark(symbol('AAPL'))  
    set_commission(PerDollar(cost=0.000))  
    set_slippage(VolumeShareSlippage(volume_limit=1, price_impact=0))  
    schedule_function(rebalance,  
                      date_rules.every_day(),  
                      time_rules.market_open())

def rebalance(context, data):  
    order_target_percent(symbol('AAPL'),1)

# Set start and end  
start = datetime(2014, 1, 1, 8, 15, 12, 0, pytz.UTC)  
end = datetime(2019, 12, 31, 8, 15, 12, 0, pytz.UTC)

# Fire off backtest  
perf = zipline.run_algorithm(  
    start=start, # Set start  
    end=end,  # Set end  
    initialize=initialize, # Define startup function  
    capital_base=intial_portfolio, # Set initial capital  
    data_frequency = 'daily',  # Set data frequency  
    bundle='sec_master_q' ) # Select bundle

print("Ready to analyze result.")  

returns, positions, transactions = pf.utils.extract_rets_pos_txn_from_zipline(perf)  
benchmark_period_return = perf['benchmark_period_return']

# Convert benchmark returns to daily returns  
daily_benchmark_returns = (1 + benchmark_period_return) / (1 + benchmark_period_return.shift()) - 1

pf.create_returns_tear_sheet(returns, benchmark_rets=daily_benchmark_returns)