EMA30_50.py

import pandas
Current_stock = 0
# Put any initialization logic here.  The context object will be passed to
# the other methods in your algorithm.
def initialize(context):
    context.sids = [sid(8655), sid(5923), sid(7797), sid(8229), sid(5484), sid(7488), sid(3136), sid(438), sid(3806), sid(3499)]
    context.long = {}
    context.short = {}
    context.stop_loss = 1
    context.take_profit = 3
    context.max_notional = 10000.1
    context.min_notional = -10000.0
    set_commission(commission.PerTrade(cost=7))

# Will be called on every trade event for the securities you specify.
def handle_data(context, data):
    acc_fast=0
    acc_slow=0

    for stock in context.sids:
        global Current_stock
        Current_stock = int(str(stock)[9:-1])

        mavg_fast=get_EMA_fast(data)
        if mavg_fast == None:
            return
        mavg_slow=get_EMA_slow(data)
        if mavg_slow == None:
            return
        acc_fast += mavg_fast
        acc_slow += mavg_slow

        notional = context.portfolio.positions[stock].amount * data[stock].price

        if stock not in context.long and stock not in context.short and notional < context.max_notional and notional > context.min_notional:
            if mavg_fast > mavg_slow:
                order(stock, 100)
                log.info("Long %f, %s" %(data[stock].price, stock))
                context.long[stock] = data[stock].price
            else:
                order(stock, -100)
                log.info("Short %f, %s" %(data[stock].price, stock))
                context.short[stock] = data[stock].price

        if stock in context.long:
            if context.long[stock] - data[stock].price > context.stop_loss:
                order(stock, -100)
                log.info("LONG Stop loss at %f, %s" %(data[stock].price, stock))
                context.long.pop(stock)
            elif data[stock].price - context.long[stock] > context.take_profit:
                order(stock, -100)
                log.info("LONG Take profit at %f, %s" %(data[stock].price, stock))
                context.long.pop(stock)
        elif stock in context.short:
             if data[stock].price - context.short[stock] > context.stop_loss:
                order(stock, 100)
                log.info("SHORT Stop loss at %f, %s" %(data[stock].price, stock))
                context.short.pop(stock)
             elif context.short[stock] - data[stock].price > context.take_profit:
                order(stock, 100)
                log.info("SHORT Take profit at %f, %s" %(data[stock].price, stock))
                context.short.pop(stock)

    record(EMA30=acc_fast/10, EMA50=acc_slow/10)

@batch_transform(window_length=30)
def get_EMA_fast(datapanel):
    global Current_stock
    prices=datapanel['price']
    EMA = pandas.stats.moments.ewma(prices, span=20)
    return EMA[Current_stock][29]

@batch_transform(window_length=50)
def get_EMA_slow(datapanel):
    global Current_stock
    prices=datapanel['price']
    EMA = pandas.stats.moments.ewma(prices, span=50)
    return EMA[Current_stock][49]