# 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 *

### <summary>

### The demonstration algorithm shows some of the most common order methods when working with Crypto assets.

### </summary>

### <meta name="tag" content="using data" />

### <meta name="tag" content="using quantconnect" />

### <meta name="tag" content="trading and orders" />

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))