I made a simple algorithm that buys when the security is below the second standard deviation for the 20 day moving average then sells when it is above the 20 day moving average but it took more than two hours to backtest so it failed the backtest. What are some common errors to keep the code fast?

from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline.data.builtin import USEquityPricing  
from quantopian.pipeline.factors import AverageDollarVolume  
from quantopian.pipeline.filters.morningstar import Q500US  
import pandas

sma_day = 20  
trade_cushion = .02  
sd = 2

trade = list()

def initialize(context):  
    schedule_function(my_rebalance, date_rules.every_day(), time_rules.market_open())  
    schedule_function(my_record_vars, date_rules.every_day(), time_rules.market_close())  
    attach_pipeline(make_pipeline(), 'my_pipeline')  
def make_pipeline():  
    base_universe = Q500US()  
    pipe = Pipeline(  
        screen = base_universe,  
    )  
    return pipe  
def before_trading_start(context, data):  
    del trade[:]  
    context.output = pipeline_output('my_pipeline')  
    context.security_list = context.output.index  
    for security in context.security_list:  
        close = data.history(security, "price", 1, "1d")  
        sma = data.history(security, "price", sma_day, "1d")  
        mean = sma.mean()  
        stddev = sma.std()  
        lower_bb = mean - (sd*stddev)  
        if close[0] < lower_bb:  
            trade.append(security)  
        record(avalible_positions = len(trade))  
def my_assign_weights(context, data):  
    pass  
def my_rebalance(context,data):  
    cpp = context.portfolio.positions  
    record(open_positions = len(cpp))  
    for security in cpp:  
        if data.history(security, "price", sma_day, "1d").mean() <= data.current(security, "price"):  
            if len(get_open_orders(security)) == 0:  
                order(security, -cpp[security]["amount"])  
    day_cash = context.portfolio.cash  
    if day_cash > 0:  
        if len(trade) > 0:  
            if len(cpp) >= 25:  
                if len(trade)+len(cpp) >= 50:  
                    cash_position = day_cash/len(trade)  
                if len(trade)+len(cpp) < 50:  
                    cash_position = day_cash/50  
            if len(cpp) < 25:  
                cash_position = day_cash/50  
            for security in trade:  
                close = data.history(security, "price", 1, "1d")  
                quan = cash_position//close[0]  
                if security not in cpp:  
                    order(security, quan, style=LimitOrder(close[0]*(1+trade_cushion)))  
    pass  
def my_record_vars(context, data):  
    pass  
def handle_data(context,data):  
    cpp = context.portfolio.positions  
    for security in cpp:  
        if data.history(security, "price", sma_day, "1d").mean() <= data.current(security, "price"):  
            if len(get_open_orders(security)) == 0:  
                roi = (data.current(security, "price") - cpp[security]["cost_basis"])*100/cpp[security]["cost_basis"]  
                log.info(roi)  
                order(security, -cpp[security]["amount"])  
        if (data.current(security, "price") - cpp[security]["cost_basis"])*100/cpp[security]["cost_basis"] <= -3:  
            if len(get_open_orders(security)) == 0:  
                roi = (data.current(security, "price") - cpp[security]["cost_basis"])*100/cpp[security]["cost_basis"]  
                log.info(roi)  
                order(security, -cpp[security]["amount"])  
    pass