| Overall Statistics |
|
Total Trades 10 Average Win 0.24% Average Loss -0.01% Compounding Annual Return -4.078% Drawdown 2.000% Expectancy 24.087 Net Profit -0.667% Sharpe Ratio -1.42 Probabilistic Sharpe Ratio 15.563% Loss Rate 20% Win Rate 80% Profit-Loss Ratio 30.36 Alpha -0.033 Beta 0.077 Annual Standard Deviation 0.027 Annual Variance 0.001 Information Ratio 0.125 Tracking Error 0.269 Treynor Ratio -0.504 Total Fees $7.00 |
# 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 datetime import timedelta
class CoveredCallAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 1, 1)
self.SetEndDate(2020, 3, 1)
self.SetCash(100000)
equity = self.AddEquity("IBM", Resolution.Minute)
option = self.AddOption("IBM", Resolution.Minute)
self.symbol = option.Symbol
# set strike/expiry filter for this option chain
option.SetFilter(-3, +3, timedelta(0), timedelta(30))
# use the underlying equity as the benchmark
self.SetBenchmark(equity.Symbol)
def OnData(self,slice):
if not self.Portfolio["IBM"].Invested:
self.MarketOrder("IBM",100) # buy 100 shares of underlying stocks
self.Log(str(self.Time) + " bought IBM " + "@" + str(self.Securities["IBM"].Price)
+ " Cash balance: " + str(self.Portfolio.Cash)
+ " Equity: " + str(self.Portfolio.HoldStock))
option_invested = [x.Key for x in self.Portfolio if x.Value.Invested and x.Value.Type==SecurityType.Option]
if len(option_invested) < 1:
self.TradeOptions(slice)
def TradeOptions(self,slice):
for i in slice.OptionChains:
if i.Key != self.symbol: continue
chain = i.Value
# filter the call options contracts
call = [x for x in chain if x.Right == OptionRight.Call]
# sorted the contracts according to their expiration dates and choose the ATM options
contracts = sorted(sorted(call, key = lambda x: abs(chain.Underlying.Price - x.Strike)),
key = lambda x: x.Expiry, reverse=True)
if len(contracts) == 0: return
self.call = contracts[0].Symbol
# short the call options
self.MarketOrder(self.call, -1)
def OnOrderEvent(self, orderEvent):
self.Log(str(orderEvent))
self.Log("Cash balance: " + str(self.Portfolio.Cash))