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BLD: misc housekeeping

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This commit is contained in:
fredfortier
2017-11-16 16:55:40 -05:00
parent e087e48088
commit 3fa88a3e56
7 changed files with 129 additions and 66 deletions
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catalyst/examples/buy_and_hodl.py
+21 -3
View File
@@ -14,7 +14,9 @@
# 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.
import pandas as pd
from catalyst import run_algorithm
from catalyst.api import (
order_target_value,
symbol,
@@ -23,6 +25,7 @@ from catalyst.api import (
get_open_orders,
)
def initialize(context):
context.ASSET_NAME = 'BTC_USDT'
context.TARGET_HODL_RATIO = 0.8
@@ -38,6 +41,7 @@ def initialize(context):
context.i = 0
def handle_data(context, data):
context.i += 1
@@ -64,8 +68,8 @@ def handle_data(context, data):
order_target_value(
context.asset,
target_hodl_value,
limit_price=price*1.1,
stop_price=price*0.9,
limit_price=price * 1.1,
stop_price=price * 0.9,
)
record(
@@ -76,6 +80,7 @@ def handle_data(context, data):
leverage=context.account.leverage,
)
def analyze(context=None, results=None):
import matplotlib.pyplot as plt
@@ -134,4 +139,17 @@ def analyze(context=None, results=None):
# Show the plot.
plt.gcf().set_size_inches(18, 8)
plt.show()
plt.show()
run_algorithm(
capital_base=10000,
data_frequency='minute',
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='poloniex',
base_currency='usd',
start=pd.to_datetime('2017-10-1', utc=True),
end=pd.to_datetime('2017-11-10', utc=True),
)
catalyst/examples/mean_reversion_simple.py
+17 -19
View File
@@ -1,14 +1,12 @@
# For this example, we're going to write a simple momentum script. When the
# stock goes up quickly, we're going to buy; when it goes down quickly, we're
# going to sell. Hopefully we'll ride the waves.
from datetime import timedelta
import pandas as pd
import talib
# To run an algorithm in Catalyst, you need two functions: initialize and
# handle_data.
from logbook import Logger
from talib.common import MA_Type
from catalyst import run_algorithm
from catalyst.api import symbol, record, order_target_percent, \
@@ -17,10 +15,10 @@ from catalyst.api import symbol, record, order_target_percent, \
# In this example, Catalyst will create the `.catalyst/data/live_algos`
# directory. If we stop and start the algorithm, Catalyst will resume its
# state using the files included in the folder.
from catalyst.exchange.stats_utils import extract_transactions, trend_direction
from catalyst.exchange.stats_utils import extract_transactions
algo_namespace = 'mean_reversion_simple'
log = Logger(algo_namespace)
NAMESPACE = 'mean_reversion_simple'
log = Logger(NAMESPACE)
def initialize(context):
@@ -30,7 +28,7 @@ def initialize(context):
# parameters or values you're going to use.
# In our example, we're looking at Ether in USD Tether.
context.eth_btc = symbol('neo_usd')
context.neo_usd = symbol('neo_usd')
context.base_price = None
context.current_day = None
@@ -50,14 +48,14 @@ def handle_data(context, data):
context.current_day = today
# We're computing the volume-weighted-average-price of the security
# defined above, in the context.eth_btc variable. For this example, we're
# defined above, in the context.neo_usd variable. For this example, we're
# using three bars on the 15 min bars.
# The frequency attribute determine the bar size. We use this convention
# for the frequency alias:
# http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
prices = data.history(
context.eth_btc,
context.neo_usd,
fields='close',
bar_count=50,
frequency='15T'
@@ -72,7 +70,7 @@ def handle_data(context, data):
# We need a variable for the current price of the security to compare to
# the average. Since we are requesting two fields, data.current()
# returns a DataFrame with
current = data.current(context.eth_btc, fields=['close', 'volume'])
current = data.current(context.neo_usd, fields=['close', 'volume'])
price = current['close']
# If base_price is not set, we use the current value. This is the
@@ -101,19 +99,19 @@ def handle_data(context, data):
# Since we are using limit orders, some orders may not execute immediately
# we wait until all orders are executed before considering more trades.
orders = get_open_orders(context.eth_btc)
orders = get_open_orders(context.neo_usd)
if len(orders) > 0:
return
# Exit if we cannot trade
if not data.can_trade(context.eth_btc):
if not data.can_trade(context.neo_usd):
return
# Another powerful built-in feature of the Catalyst backtester is the
# portfolio object. The portfolio object tracks your positions, cash,
# cost basis of specific holdings, and more. In this line, we calculate
# how long or short our position is at this minute.
pos_amount = context.portfolio.positions[context.eth_btc].amount
pos_amount = context.portfolio.positions[context.neo_usd].amount
if rsi[-1] <= 30 and pos_amount == 0:
log.info(
@@ -121,7 +119,7 @@ def handle_data(context, data):
data.current_dt, price, rsi[-1]
)
)
order_target_percent(context.eth_btc, 1)
order_target_percent(context.neo_usd, 1)
context.traded_today = True
elif rsi[-1] >= 80 and pos_amount > 0:
@@ -130,7 +128,7 @@ def handle_data(context, data):
data.current_dt, price, rsi[-1]
)
)
order_target_percent(context.eth_btc, 0)
order_target_percent(context.neo_usd, 0)
context.traded_today = True
@@ -150,7 +148,7 @@ def analyze(context=None, perf=None):
perf.loc[:, 'price'].plot(ax=ax2, label='Price')
ax2.set_ylabel('{asset} ({base})'.format(
asset=context.eth_btc.symbol, base=base_currency
asset=context.neo_usd.symbol, base=base_currency
))
transaction_df = extract_transactions(perf)
@@ -218,10 +216,10 @@ def analyze(context=None, perf=None):
if __name__ == '__main__':
# The execution mode: backtest or live
MODE = 'backtest'
MODE = 'live'
if MODE == 'backtest':
# catalyst run -f catalyst/examples/mean_reversion_simple.py -x poloniex -s 2017-7-1 -e 2017-7-31 -c usdt -n mean-reversion --data-frequency minute --capital-base 10000
# catalyst run -f catalyst/examples/mean_reversion_simple.py -x poloniex -s 2017-10-1 -e 2017-11-10 -c usdt -n mean-reversion --data-frequency minute --capital-base 10000
run_algorithm(
capital_base=10000,
data_frequency='minute',
@@ -229,7 +227,7 @@ if __name__ == '__main__':
handle_data=handle_data,
analyze=analyze,
exchange_name='bitfinex',
algo_namespace=algo_namespace,
algo_namespace=NAMESPACE,
base_currency='usd',
start=pd.to_datetime('2017-10-1', utc=True),
end=pd.to_datetime('2017-11-10', utc=True),
@@ -242,7 +240,7 @@ if __name__ == '__main__':
analyze=analyze,
exchange_name='bitfinex',
live=True,
algo_namespace=algo_namespace,
algo_namespace=NAMESPACE,
base_currency='usd',
live_graph=True
)
catalyst/examples/rsi_profit_target.py
+17 -17
View File
@@ -250,27 +250,27 @@ def analyze(context=None, results=None):
pass
run_algorithm(
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='bittrex',
live=True,
algo_namespace=algo_namespace,
base_currency='btc',
live_graph=False
)
# Backtest
# run_algorithm(
# capital_base=0.5,
# data_frequency='minute',
# initialize=initialize,
# handle_data=handle_data,
# analyze=analyze,
# exchange_name='poloniex',
# exchange_name='bittrex',
# live=True,
# algo_namespace=algo_namespace,
# base_currency='btc',
# start=pd.to_datetime('2017-9-1', utc=True),
# end=pd.to_datetime('2017-10-1', utc=True),
# live_graph=False
# )
# Backtest
run_algorithm(
capital_base=0.5,
data_frequency='minute',
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='poloniex',
algo_namespace=algo_namespace,
base_currency='btc',
start=pd.to_datetime('2017-9-1', utc=True),
end=pd.to_datetime('2017-10-1', utc=True),
)