from System import *
from QuantConnect import *
from QuantConnect.Data.Consolidators import *
from QuantConnect.Data.Market import *
from QuantConnect.Orders import OrderStatus
from QuantConnect.Algorithm import QCAlgorithm
from QuantConnect.Indicators import *
import numpy as np
from datetime import timedelta, datetime
### <summary>
### Example structure for structuring an algorithm with indicator and consolidator data for many tickers.
### </summary>
### <meta name="tag" content="consolidating data" />
### <meta name="tag" content="indicators" />
### <meta name="tag" content="using data" />
### <meta name="tag" content="strategy example" />
class MultipleSymbolConsolidationAlgorithm(QCAlgorithm):
# Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
def Initialize(self):
#self.SetStartDate(2014, 8, 1)
self.SetStartDate(2020, 8, 3)
# self.SetEndDate(2015, 2, 1)
self.SetEndDate(datetime.now().date())
self.SetCash(100000) # Set Strategy Cash
# This is the period of bars we'll be creating
# Holds all of our data keyed by each symbol
self.Data = {}
self.daily = {}
self.window = {}
self.securities = []
# consolidation_size = 24
consolidation_size = 1440
EquitySymbols = ["AAPL", "SPY", "IBM"]
# Contains all of our forex symbols
ForexSymbols = ["EURUSD", "USDJPY", "EURGBP", "EURCHF", "USDCAD", "USDCHF", "AUDUSD", "NZDUSD"]
# Crypto symbols
# CryptoSymbols = ["BTCUSD","ETHUSD","LTCUSD","BCHUSD"]
CryptoSymbols = ["BTCUSD", "ETHUSD", "LTCUSD", "BCHUSD", "XRPUSD", "BCHUSD", "XLMUSD", "EOSUSD", "REPUSD",
"XTZUSD", "ETCUSD", "ZRXUSD"]
# testcase
# CryptoSymbols = ["BTCUSD"]
self.cryptosymbols = []
for symbol in CryptoSymbols:
crypto = self.AddCrypto(symbol, Resolution.Minute, Market.GDAX).Symbol
self.securities.append(crypto)
HourlyConsolidator = TradeBarConsolidator(consolidation_size)
HourlyConsolidator.DataConsolidated += self.HourlyConsolidator
self.SubscriptionManager.AddConsolidator(crypto, HourlyConsolidator)
self.daily[crypto] = RollingWindow[TradeBar](3 * consolidation_size)
self.window[crypto] = RollingWindow[TradeBar](3 * consolidation_size)
self.cryptosymbols.append(crypto)
self.equitysymbols = []
for symbol in EquitySymbols:
equity = self.AddEquity(symbol, Resolution.Minute, Market.USA).Symbol
self.equitysymbols.append(equity)
HourlyConsolidator = TradeBarConsolidator(consolidation_size)
HourlyConsolidator.DataConsolidated += self.HourlyConsolidator
self.SubscriptionManager.AddConsolidator(crypto, HourlyConsolidator)
self.daily[crypto] = RollingWindow[TradeBar](3 * consolidation_size)
self.window[crypto] = RollingWindow[TradeBar](3 * consolidation_size)
self.equitysymbols.append(equity)
#consolidates daily data for crypto so far
def HourlyConsolidator(self, sender, bar):
self.daily[bar.Symbol].Add(bar)
def OnData(self, data):
# for symbol in self.securities:
sell_len = 120
buy_len = 180
buy_ticks = list(range(0, buy_len))
sell_ticks = list(range(0, sell_len))
# solves issue of wasn't found in the TradeBars object, likely because there was no-data at this moment in time and it wasn't possible to fillforward historical data
if not all([data.Bars.ContainsKey(symbol) for symbol in self.cryptosymbols]):
return
for symbol in self.cryptosymbols:
# self.Debug(symbol)
if not data.ContainsKey(symbol):
return
# if not slice.Bars.ContainsKey(symbol):
# return
self.window[symbol].Add(data.Bars[symbol])
# Access bar properties from the `window`
if not self.window[symbol].IsReady:
continue
latest_bar = self.window[symbol][0]
close_of_latest_bar = latest_bar.Close
close_lst = [self.window[symbol][0].Close, self.window[symbol][1].Close, self.window[symbol][120].Close]
# Acessing previous bar properties from the daily bar
previous_daily_bar = self.daily[symbol][1]
close_of_previous_daily_bar = previous_daily_bar.Close
high_of_previous_daily_bar = previous_daily_bar.High
low_of_previous_daily_bar = previous_daily_bar.Low
sell_dic = {}
buy_dic = {}
sell_len = []
buy_len = []
for num in buy_ticks:
minute_bar = self.window[symbol][num]
close_bar = minute_bar.Close
buy_len.append(close_bar)
# orders prices in chronological order left to right in the lst
buy_dic[symbol] = buy_len[::-1]
for num in sell_ticks:
minute_bar = self.window[symbol][num]
close_bar = minute_bar.Close
sell_len.append(close_bar)
# orders prices in chronological order left to right in the lst
sell_dic[symbol] = sell_len[::-1]
if not all([data.Bars.ContainsKey(symbol) for symbol in self.equitysymbols]):
return
for symbol in self.equitysymbols:
# self.Debug(symbol)
if not data.ContainsKey(symbol):
return
self.window[symbol].Add(data.Bars[symbol])
# Access bar properties from the `window`
if not self.window[symbol].IsReady:
continue
latest_bar = self.window[symbol][0]
close_of_latest_bar = latest_bar.Close
# 120 minutes--> sell signals
# 180 minutes--> buy signals
close_lst = [self.window[symbol][0].Close, self.window[symbol][1].Close, self.window[symbol][120].Close]
# self.Debug(close_lst)
# Acessing previous bar properties from the daily bar
previous_daily_bar = self.daily[symbol][1]
close_of_previous_daily_bar = previous_daily_bar.Close
high_of_previous_daily_bar = previous_daily_bar.High
low_of_previous_daily_bar = previous_daily_bar.Low
sell_dic = {}
buy_dic = {}
sell_len = []
buy_len = []
for num in buy_ticks:
minute_bar = self.window[symbol][num]
close_bar = minute_bar.Close
buy_len.append(close_bar)
# orders prices in chronological order left to right in the lst
buy_dic[symbol] = buy_len[::-1]
for num in sell_ticks:
minute_bar = self.window[symbol][num]
close_bar = minute_bar.Close
sell_len.append(close_bar)
# orders prices in chronological order left to right in the lst
sell_dic[symbol] = sell_len[::-1]