# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
# 
# Licensed under the Apache License, Version 2.0 (the "License"); 
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import clr
clr.AddReference("System")
clr.AddReference("QuantConnect.Algorithm")
clr.AddReference("QuantConnect.Indicators")
clr.AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *


class DailyAlgorithm(QCAlgorithm):
    '''Uses daily data and a simple moving average cross to place trades and an ema for stop placement'''

    def Initialize(self):
        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
        
        self.SetStartDate(2013,01,01)  #Set Start Date
        self.SetEndDate(2014,01,01)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        spy_security = self.AddSecurity(SecurityType.Equity, "SPY", Resolution.Daily)
        ibm_security = self.AddSecurity(SecurityType.Equity, "IBM", Resolution.Hour)
        ibm_security.SetLeverage(1.0)
        self.ibm = ibm_security.Symbol
        self.spy = spy_security.Symbol
        self.macd = self.MACD(self.spy, 12, 26, 9, MovingAverageType.Wilders, Resolution.Daily, Field.Close)
        self.ema = self.EMA(self.ibm, 15*6, Resolution.Hour, Field.SevenBar)
        self.lastAction = None
        

    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
        
        Arguments:
            data: Slice object keyed by symbol containing the stock data
        '''
        if not self.macd.IsReady: return
        if not data.ContainsKey(self.ibm): return
        if data[self.ibm] is None:
            self.Log("Price Missing Time: %s"%str(self.Time))
            return
        if self.lastAction is not None and self.lastAction.date() == self.Time.date(): return
        
        self.lastAction = self.Time
        holding = self.Portfolio[self.spy]

        if holding.Quantity <= 0 and self.macd.Current.Value > self.macd.Signal.Current.Value and data[self.ibm].Price > self.ema.Current.Value:
            self.SetHoldings(self.ibm, 0.25)
        elif holding.Quantity >= 0 and self.macd.Current.Value < self.macd.Signal.Current.Value and data[self.ibm].Price < self.ema.Current.Value:
            self.SetHoldings(self.ibm, -0.25)