Hi everyone,

I am trying to build a simple algo that would buy when the market make a gap up of more than 3% but I have some trouble to implement a stop loss.

Any idea ?

Thanks
Chris

import numpy as np  
import pandas as pd

def initialize(context):  
    set_universe(universe.DollarVolumeUniverse(floor_percentile=95.0, ceiling_percentile=100.0))  
    context.stop_price = 0  
    context.stop_pct = 0.99  
    schedule_function(  
        func=market_open,  
        date_rule=date_rules.every_day(),  
        time_rule=time_rules.market_open(hours=0, minutes=5),  
        half_days=True)  
    schedule_function(  
        func=close_all_positions,  
        date_rule=date_rules.every_day(),  
        time_rule=time_rules.market_close(hours=0, minutes=5),  
        half_days=True)  
    # Set execution cost assumptions. For live trading with Interactive Brokers  
    # we will assume a $1.00 minimum per trade fee, with a per share cost of $0.0075.  
    set_commission(commission.PerShare(cost=0.0075, min_trade_cost=1.00))  
    # Set market impact assumptions. We limit the simulation to  
    # trade up to 2.5% of the traded volume for any one minute,  
    # and  our price impact constant is 0.1.  
    set_slippage(slippage.VolumeShareSlippage(volume_limit=0.025, price_impact=0.10))

def market_open(context, data):  
    for stock in data:  
        price_history = history(bar_count=5, frequency='1d', field='price')  
        #close_2_day_ago = price_history[data.stock][-3] # close two days ago  
        close_yesterday = price_history[stock][-2] # close of yesterday  
        open_today = price_history[stock][-1]  
        cash = context.portfolio.cash  
        nb_of_shares = int(cash / open_today)  
        #target_shares = cash / stock.price  
        gap_percent = (open_today / close_yesterday - 1)  
        #log.info('Percent change {}'.format(gap_percent))  
### ENTRY ###  
        if gap_percent > 0.03 and len(get_open_orders()) == 0:  
            order(stock, nb_of_shares)  
            log.info('Bought {} shares of {}'.format(nb_of_shares, stock.symbol))


def handle_data(context, data):  
    set_stop_loss(context, data)  
    if data[context.stock].price < context.stop_price:  
        order_target(context.stock, 0)  


def set_stop_loss(context, data):  
    if context.portfolio.positions[context.stock].amount:  
        price = data[context.stock].price  
        context.stop_price = context.stop_pct * price  


def close_all_positions(context, data):  
    for stock in data:  
        current_positions = context.portfolio.positions  
        if current_positions != 0:  
            order_target_percent(stock, 0)  
            log.info('cover before the close of the day')