66 lines
2.9 KiB
Python
66 lines
2.9 KiB
Python
# 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 *
|
|
|
|
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
|
|
from Execution.ImmediateExecutionModel import ImmediateExecutionModel
|
|
from Selection.ManualUniverseSelectionModel import ManualUniverseSelectionModel
|
|
|
|
### <summary>
|
|
### Basic template framework algorithm uses framework components to define the algorithm.
|
|
### Shows EqualWeightingPortfolioConstructionModel.long_only() application
|
|
### </summary>
|
|
### <meta name="tag" content="alpha streams" />
|
|
### <meta name="tag" content="using quantconnect" />
|
|
### <meta name="tag" content="algorithm framework" />
|
|
class LongOnlyAlphaStreamAlgorithm(QCAlgorithm):
|
|
|
|
def initialize(self):
|
|
# 1. Required:
|
|
self.set_start_date(2013, 10, 7)
|
|
self.set_end_date(2013, 10, 11)
|
|
|
|
# 2. Required: Alpha Streams Models:
|
|
self.set_brokerage_model(BrokerageName.ALPHA_STREAMS)
|
|
|
|
# 3. Required: Significant AUM Capacity
|
|
self.set_cash(1000000)
|
|
|
|
# Only SPY will be traded
|
|
self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel(Resolution.DAILY, PortfolioBias.LONG))
|
|
self.set_execution(ImmediateExecutionModel())
|
|
|
|
# Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
|
|
# Commented so regression algorithm is more sensitive
|
|
#self.settings.minimum_order_margin_portfolio_percentage = 0.005
|
|
|
|
# Set algorithm framework models
|
|
self.set_universe_selection(ManualUniverseSelectionModel(
|
|
[Symbol.create(x, SecurityType.EQUITY, Market.USA) for x in ["SPY", "IBM"]]))
|
|
|
|
def on_data(self, slice):
|
|
if self.portfolio.invested: return
|
|
|
|
self.emit_insights(
|
|
[
|
|
Insight.price("SPY", timedelta(1), InsightDirection.UP),
|
|
Insight.price("IBM", timedelta(1), InsightDirection.DOWN)
|
|
])
|
|
|
|
def on_order_event(self, order_event):
|
|
if order_event.status == OrderStatus.FILLED:
|
|
if self.securities[order_event.symbol].holdings.is_short:
|
|
raise ValueError("Invalid position, should not be short")
|
|
self.debug(order_event)
|