# 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.
from AlgorithmImports import *
###
### The demonstration algorithm shows some of the most common order methods when working with Crypto assets.
###
###
###
###
class BasicTemplateCryptoAlgorithm(QCAlgorithm):
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.set_start_date(2018, 4, 4) #Set Start Date
self.set_end_date(2018, 4, 4) #Set End Date
# Although typically real brokerages as GDAX only support a single account currency,
# here we add both USD and EUR to demonstrate how to handle non-USD account currencies.
# Set Strategy Cash (USD)
self.set_cash(10000)
# Set Strategy Cash (EUR)
# EUR/USD conversion rate will be updated dynamically
self.set_cash("EUR", 10000)
# Add some coins as initial holdings
# When connected to a real brokerage, the amount specified in SetCash
# will be replaced with the amount in your actual account.
self.set_cash("BTC", 1)
self.set_cash("ETH", 5)
self.set_brokerage_model(BrokerageName.GDAX, AccountType.CASH)
# You can uncomment the following lines when live trading with GDAX,
# to ensure limit orders will only be posted to the order book and never executed as a taker (incurring fees).
# Please note this statement has no effect in backtesting or paper trading.
# self.default_order_properties = GDAXOrderProperties()
# self.default_order_properties.post_only = True
# Find more symbols here: http://quantconnect.com/data
self.add_crypto("BTCUSD", Resolution.MINUTE)
self.add_crypto("ETHUSD", Resolution.MINUTE)
self.add_crypto("BTCEUR", Resolution.MINUTE)
symbol = self.add_crypto("LTCUSD", Resolution.MINUTE).symbol
# create two moving averages
self.fast = self.ema(symbol, 30, Resolution.MINUTE)
self.slow = self.ema(symbol, 60, Resolution.MINUTE)
def on_data(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
'''
# Note: all limit orders in this algorithm will be paying taker fees,
# they shouldn't, but they do (for now) because of this issue:
# https://github.com/QuantConnect/Lean/issues/1852
if self.time.hour == 1 and self.time.minute == 0:
# Sell all ETH holdings with a limit order at 1% above the current price
limit_price = round(self.securities["ETHUSD"].price * 1.01, 2)
quantity = self.portfolio.cash_book["ETH"].amount
self.limit_order("ETHUSD", -quantity, limit_price)
elif self.time.hour == 2 and self.time.minute == 0:
# Submit a buy limit order for BTC at 5% below the current price
usd_total = self.portfolio.cash_book["USD"].amount
limit_price = round(self.securities["BTCUSD"].price * 0.95, 2)
# use only half of our total USD
quantity = usd_total * 0.5 / limit_price
self.limit_order("BTCUSD", quantity, limit_price)
elif self.time.hour == 2 and self.time.minute == 1:
# Get current USD available, subtracting amount reserved for buy open orders
usd_total = self.portfolio.cash_book["USD"].amount
usd_reserved = sum(x.quantity * x.limit_price for x
in [x for x in self.transactions.get_open_orders()
if x.direction == OrderDirection.BUY
and x.type == OrderType.LIMIT
and (x.symbol.value == "BTCUSD" or x.symbol.value == "ETHUSD")])
usd_available = usd_total - usd_reserved
self.debug("usd_available: {}".format(usd_available))
# Submit a marketable buy limit order for ETH at 1% above the current price
limit_price = round(self.securities["ETHUSD"].price * 1.01, 2)
# use all of our available USD
quantity = usd_available / limit_price
# this order will be rejected (for now) because of this issue:
# https://github.com/QuantConnect/Lean/issues/1852
self.limit_order("ETHUSD", quantity, limit_price)
# use only half of our available USD
quantity = usd_available * 0.5 / limit_price
self.limit_order("ETHUSD", quantity, limit_price)
elif self.time.hour == 11 and self.time.minute == 0:
# Liquidate our BTC holdings (including the initial holding)
self.set_holdings("BTCUSD", 0)
elif self.time.hour == 12 and self.time.minute == 0:
# Submit a market buy order for 1 BTC using EUR
self.buy("BTCEUR", 1)
# Submit a sell limit order at 10% above market price
limit_price = round(self.securities["BTCEUR"].price * 1.1, 2)
self.limit_order("BTCEUR", -1, limit_price)
elif self.time.hour == 13 and self.time.minute == 0:
# Cancel the limit order if not filled
self.transactions.cancel_open_orders("BTCEUR")
elif self.time.hour > 13:
# To include any initial holdings, we read the LTC amount from the cashbook
# instead of using Portfolio["LTCUSD"].quantity
if self.fast > self.slow:
if self.portfolio.cash_book["LTC"].amount == 0:
self.buy("LTCUSD", 10)
else:
if self.portfolio.cash_book["LTC"].amount > 0:
self.liquidate("LTCUSD")
def on_order_event(self, order_event):
self.debug("{} {}".format(self.time, order_event.to_string()))
def on_end_of_algorithm(self):
self.log("{} - TotalPortfolioValue: {}".format(self.time, self.portfolio.total_portfolio_value))
self.log("{} - CashBook: {}".format(self.time, self.portfolio.cash_book))