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Strange! The return is higher if I consider the slippage and commission ...

Normally I will set the following code in my codes:
... set_commission(commission.PerShare(cost = 0.0050, min_trade_cost = 0.0))
set_slippage(slippage.FixedSlippage(spread=0))
...

I thought the total return should lower than not considerung the slippage and commissions. But in fact it is the opposite.

Strange!

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Backtest from to with initial capital
Total Returns
--
Alpha
--
Beta
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Sharpe
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Sortino
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Max Drawdown
--
Benchmark Returns
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Volatility
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Returns 1 Month 3 Month 6 Month 12 Month
Alpha 1 Month 3 Month 6 Month 12 Month
Beta 1 Month 3 Month 6 Month 12 Month
Sharpe 1 Month 3 Month 6 Month 12 Month
Sortino 1 Month 3 Month 6 Month 12 Month
Volatility 1 Month 3 Month 6 Month 12 Month
Max Drawdown 1 Month 3 Month 6 Month 12 Month
"""
This is a template algorithm on Quantopian for you to adapt and fill in.
"""
import quantopian.algorithm as algo
from quantopian.pipeline import Pipeline
from quantopian.pipeline.data.builtin import USEquityPricing
from quantopian.pipeline.filters import QTradableStocksUS


def initialize(context):
    """
    Called once at the start of the algorithm.
    """
#    set_commission(commission.PerShare(cost = 0.0050, min_trade_cost = 0.0))
#    set_slippage(slippage.FixedSlippage(spread=0))       
    
    context.stock = symbol('SDD')
    
    # Rebalance every day, 1 hour after market open.
    algo.schedule_function(
        rebalance,
        algo.date_rules.every_day(),
        algo.time_rules.market_open(hours=1),
    )

    algo.schedule_function(
        exit,
        algo.date_rules.every_day(),
        algo.time_rules.market_open(hours=2),
    )
    
    # Record tracking variables at the end of each day.
    algo.schedule_function(
        record_vars,
        algo.date_rules.every_day(),
        algo.time_rules.market_close(),
    )

    # Create our dynamic stock selector.
    algo.attach_pipeline(make_pipeline(), 'pipeline')


def make_pipeline():
    """
    A function to create our dynamic stock selector (pipeline). Documentation
    on pipeline can be found here:
    https://www.quantopian.com/help#pipeline-title
    """

    # Base universe set to the QTradableStocksUS
    base_universe = QTradableStocksUS()

    # Factor of yesterday's close price.
    yesterday_close = USEquityPricing.close.latest

    pipe = Pipeline(
        columns={
            'close': yesterday_close,
        },
        screen=base_universe
    )
    return pipe


def before_trading_start(context, data):
    """
    Called every day before market open.
    """
    context.output = algo.pipeline_output('pipeline')

    # These are the securities that we are interested in trading each day.
    context.security_list = context.output.index


def rebalance(context, data):
    """
    Execute orders according to our schedule_function() timing.
    """
    order_target_percent(context.stock, 0.99)

def exit(context, data):
    order_target_percent(context.stock, 0)
    
def record_vars(context, data):
    """
    Plot variables at the end of each day.
    """
    pass


def handle_data(context, data):
    """
    Called every minute.
    """
    pass
There was a runtime error.