#!/usr/bin/env python
#
# Copyright 2014 Quantopian, Inc.
#
# 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 zipline.api import order, record, symbol
from zipline.finance import commission, slippage
from zipline import run_algorithm
import pandas as pd
import pandas_datareader.data as web
import matplotlib.pyplot as plt


def initialize(context):
    context.asset = symbol("AAPL")

    # Explicitly set the commission/slippage to the "old" value until we can
    # rebuild example data.
    # github.com/quantopian/zipline/blob/master/tests/resources/
    # rebuild_example_data#L105
    context.set_commission(commission.PerShare(cost=0.0075, min_trade_cost=1.0))
    context.set_slippage(slippage.VolumeShareSlippage())


def handle_data(context, data):
    order(context.asset, 10)
    record(AAPL=data.current(context.asset, "price"))


# Note: this function can be removed if running
# this algorithm on quantopian.com
def analyze(context=None, results=None):
    import matplotlib.pyplot as plt

    # Plot the portfolio and asset data.
    ax1 = plt.subplot(211)
    results.portfolio_value.plot(ax=ax1)
    ax1.set_ylabel("Portfolio value (USD)")
    ax2 = plt.subplot(212, sharex=ax1)
    results.AAPL.plot(ax=ax2)
    ax2.set_ylabel("AAPL price (USD)")

    # Show the plot.
    plt.gcf().set_size_inches(18, 8)
    plt.show()


start = pd.Timestamp("2014")
end = pd.Timestamp("2018")

sp500 = web.DataReader("SP500", "fred", start, end).SP500
benchmark_returns = sp500.pct_change()
print(benchmark_returns.head())

result = run_algorithm(
    start=start.tz_localize("UTC"),
    end=end.tz_localize("UTC"),
    initialize=initialize,
    handle_data=handle_data,
    capital_base=100000,
    benchmark_returns=benchmark_returns,
    bundle="quandl",
    data_frequency="daily",
)

print(result.info())

result.portfolio_value.plot()
plt.show()

#!/usr/bin/env python
#
# Copyright 2014 Quantopian, Inc.
#
# 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 zipline.api import order, record, symbol
from zipline.finance import commission, slippage
from zipline import run_algorithm
import pandas as pd
import pandas_datareader.data as web
import matplotlib.pyplot as plt


def initialize(context):
    context.asset = symbol("AAPL")

    # Explicitly set the commission/slippage to the "old" value until we can
    # rebuild example data.
    # github.com/quantopian/zipline/blob/master/tests/resources/
    # rebuild_example_data#L105
    context.set_commission(commission.PerShare(cost=0.0075, min_trade_cost=1.0))
    context.set_slippage(slippage.VolumeShareSlippage())


def handle_data(context, data):
    order(context.asset, 10)
    record(AAPL=data.current(context.asset, "price"))


# Note: this function can be removed if running
# this algorithm on quantopian.com
def analyze(context=None, results=None):
    import matplotlib.pyplot as plt

    # Plot the portfolio and asset data.
    ax1 = plt.subplot(211)
    results.portfolio_value.plot(ax=ax1)
    ax1.set_ylabel("Portfolio value (USD)")
    ax2 = plt.subplot(212, sharex=ax1)
    results.AAPL.plot(ax=ax2)
    ax2.set_ylabel("AAPL price (USD)")

    # Show the plot.
    plt.gcf().set_size_inches(18, 8)
    plt.show()


start = pd.Timestamp("2014")
end = pd.Timestamp("2018")

sp500 = web.DataReader("SP500", "fred", start, end).SP500
benchmark_returns = sp500.pct_change()
print(benchmark_returns.head())

result = run_algorithm(
    start=start.tz_localize("UTC"),
    end=end.tz_localize("UTC"),
    initialize=initialize,
    handle_data=handle_data,
    capital_base=100000,
    benchmark_returns=benchmark_returns,
    bundle="quandl",
    data_frequency="daily",
)

print(result.info())

result.portfolio_value.plot()
plt.show()

#!/usr/bin/env python # # Copyright 2014 Quantopian, Inc. # # 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. # Explicitly set the commission/slippage to the "old" value until we can # rebuild example data. # github.com/quantopian/zipline/blob/master/tests/resources/ # rebuild_example_data#L105 # Note: this function can be removed if running # this algorithm on quantopian.com # Plot the portfolio and asset data. # Show the plot.