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Lean/Algorithm.Python/BasicTemplateOptionsAlgorithm.py at master · QuantConnect/Lean · GitHub
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BasicTemplateOptionsAlgorithm.py
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Algorithm.Python
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BasicTemplateOptionsAlgorithm.py
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# 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>
### This example demonstrates how to add options for a given underlying equity security.
### It also shows how you can prefilter contracts easily based on strikes and expirations, and how you
### can inspect the option chain to pick a specific option contract to trade.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="options" />
### <meta name="tag" content="filter selection" />
class
BasicTemplateOptionsAlgorithm
(
QCAlgorithm
):
underlying_ticker
=
"GOOG"
def
initialize
(
self
):
self
.
set_start_date
(
2015
,
12
,
24
)
self
.
set_end_date
(
2015
,
12
,
24
)
self
.
set_cash
(
100000
)
equity
=
self
.
add_equity
(
self
.
underlying_ticker
)
option
=
self
.
add_option
(
self
.
underlying_ticker
)
self
.
option_symbol
=
option
.
symbol
# set our strike/expiry filter for this option chain
option
.
set_filter
(
lambda
u
: (
u
.
standards_only
().
strikes
(
-
2
,
+
2
)
# Expiration method accepts TimeSpan objects or integer for days.
# The following statements yield the same filtering criteria
.
expiration
(
0
,
180
)))
#.expiration(TimeSpan.zero, TimeSpan.from_days(180))))
# use the underlying equity as the benchmark
self
.
set_benchmark
(
equity
.
symbol
)
def
on_data
(
self
,
slice
):
if
self
.
portfolio
.
invested
or
not
self
.
is_market_open
(
self
.
option_symbol
):
return
chain
=
slice
.
option_chains
.
get
(
self
.
option_symbol
)
if
not
chain
:
return
# we sort the contracts to find at the money (ATM) contract with farthest expiration
contracts
=
sorted
(
sorted
(
sorted
(
chain
, \
key
=
lambda
x
:
abs
(
chain
.
underlying
.
price
-
x
.
strike
)), \
key
=
lambda
x
:
x
.
expiry
,
reverse
=
True
), \
key
=
lambda
x
:
x
.
right
,
reverse
=
True
)
# if found, trade it
if
len
(
contracts
)
==
0
:
return
symbol
=
contracts
[
0
].
symbol
self
.
market_order
(
symbol
,
1
)
self
.
market_on_close_order
(
symbol
,
-
1
)
def
on_order_event
(
self
,
order_event
):
self
.
log
(
str
(
order_event
))
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