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BLD: adjusting sample algorithmns for validation

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This commit is contained in:
Frederic Fortier
2018-01-03 22:59:07 -05:00
parent d64fe12751
commit 9bb12eb781
4 changed files with 48 additions and 204 deletions
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catalyst/constants.py
+1 -1
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@@ -7,7 +7,7 @@ import logbook
For example, if you want to see the DEBUG messages, run:
$ export CATALYST_LOG_LEVEL=10
'''
LOG_LEVEL = int(os.environ.get('CATALYST_LOG_LEVEL', logbook.INFO))
LOG_LEVEL = int(os.environ.get('CATALYST_LOG_LEVEL', logbook.DEBUG))
SYMBOLS_URL = 'https://s3.amazonaws.com/enigmaco/catalyst-exchanges/' \
'{exchange}/symbols.json'
catalyst/examples/buy_low_sell_high.py
+46 -47
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@@ -1,20 +1,7 @@
'''
This algorithm requires an additional library (ta-lib) beyond those
required by catalyst. Install it first by running:
$ pip install TA-Lib
If you get build errors like:
"fatal error: ta-lib/ta_libc.h: No such file or directory"
it typically means that it can't find the underlying TA-Lib library and it
needs to be installed. See https://mrjbq7.github.io/ta-lib/install.html for
instructions on how to install the required dependencies.
'''
import pandas as pd
import talib
import pandas as pd
from logbook import Logger
from catalyst import run_algorithm
from catalyst.api import (
order,
order_target_percent,
@@ -23,53 +10,51 @@ from catalyst.api import (
get_open_orders,
)
from catalyst.exchange.utils.stats_utils import get_pretty_stats
from catalyst.utils.run_algo import run_algorithm
algo_namespace = 'buy_low_sell_high_xrp'
log = Logger(algo_namespace)
algo_namespace = 'buy_the_dip_live'
log = Logger('buy low sell high')
def initialize(context):
log.info('initializing algo')
context.ASSET_NAME = 'XRP_USDT'
context.ASSET_NAME = 'btc_usdt'
context.asset = symbol(context.ASSET_NAME)
context.TARGET_POSITIONS = 5000
context.TARGET_POSITIONS = 30
context.PROFIT_TARGET = 0.1
context.SLIPPAGE_ALLOWED = 0.05
context.swallow_errors = True
context.SLIPPAGE_ALLOWED = 0.02
context.errors = []
pass
def _handle_data(context, data):
price = data.current(context.asset, 'price')
log.info('got price {price}'.format(price=price))
prices = data.history(
context.asset,
fields='price',
bar_count=20,
frequency='15m'
frequency='1D'
)
rsi = talib.RSI(prices.values, timeperiod=14)[-1]
log.info('got rsi: {}'.format(rsi))
# Buying more when RSI is low, this should lower our cost basis
if rsi <= 30:
buy_increment = 50
buy_increment = 1
elif rsi <= 40:
buy_increment = 20
buy_increment = 0.5
elif rsi <= 70:
buy_increment = 5
buy_increment = 0.2
else:
buy_increment = None
buy_increment = 0.1
cash = context.portfolio.cash
log.info('base currency available: {cash}'.format(cash=cash))
price = data.current(context.asset, 'price')
log.info('got price {price}'.format(price=price))
record(
price=price,
rsi=rsi,
@@ -137,11 +122,11 @@ def _handle_data(context, data):
def handle_data(context, data):
log.info('handling bar {}'.format(data.current_dt))
try:
_handle_data(context, data)
except Exception as e:
log.warn('aborting the bar on error {}'.format(e))
context.errors.append(e)
# try:
_handle_data(context, data)
# except Exception as e:
# log.warn('aborting the bar on error {}'.format(e))
# context.errors.append(e)
log.info('completed bar {}, total execution errors {}'.format(
data.current_dt,
@@ -158,15 +143,29 @@ def analyze(context, stats):
if __name__ == '__main__':
run_algorithm(
capital_base=10000,
data_frequency='daily',
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='poloniex',
algo_namespace='buy_and_hodl',
base_currency='usd',
start=pd.to_datetime('2015-03-01', utc=True),
end=pd.to_datetime('2017-10-31', utc=True),
)
live = False
if live:
run_algorithm(
capital_base=0.001,
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='binance',
live=True,
algo_namespace=algo_namespace,
base_currency='btc',
simulate_orders=True,
)
else:
run_algorithm(
capital_base=10000,
data_frequency='daily',
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='poloniex',
algo_namespace='buy_and_hodl',
base_currency='usdt',
start=pd.to_datetime('2015-03-01', utc=True),
end=pd.to_datetime('2017-10-31', utc=True),
)
catalyst/examples/buy_low_sell_high_live.py
-155
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@@ -1,155 +0,0 @@
import talib
from logbook import Logger
from catalyst.api import (
order,
order_target_percent,
symbol,
record,
get_open_orders,
)
from catalyst.exchange.utils.stats_utils import get_pretty_stats
from catalyst.utils.run_algo import run_algorithm
algo_namespace = 'buy_the_dip_live'
log = Logger('buy low sell high')
def initialize(context):
log.info('initializing algo')
context.ASSET_NAME = 'btc_usdt'
context.asset = symbol(context.ASSET_NAME)
context.TARGET_POSITIONS = 30
context.PROFIT_TARGET = 0.1
context.SLIPPAGE_ALLOWED = 0.02
context.errors = []
pass
def _handle_data(context, data):
price = data.current(context.asset, 'price')
log.info('got price {price}'.format(price=price))
prices = data.history(
context.asset,
fields='price',
bar_count=20,
frequency='1D'
)
rsi = talib.RSI(prices.values, timeperiod=14)[-1]
log.info('got rsi: {}'.format(rsi))
# Buying more when RSI is low, this should lower our cost basis
if rsi <= 30:
buy_increment = 1
elif rsi <= 40:
buy_increment = 0.5
elif rsi <= 70:
buy_increment = 0.2
else:
buy_increment = 0.1
cash = context.portfolio.cash
log.info('base currency available: {cash}'.format(cash=cash))
record(
price=price,
rsi=rsi,
)
orders = get_open_orders(context.asset)
if orders:
log.info('skipping bar until all open orders execute')
return
is_buy = False
cost_basis = None
if context.asset in context.portfolio.positions:
position = context.portfolio.positions[context.asset]
cost_basis = position.cost_basis
log.info(
'found {amount} positions with cost basis {cost_basis}'.format(
amount=position.amount,
cost_basis=cost_basis
)
)
if position.amount >= context.TARGET_POSITIONS:
log.info('reached positions target: {}'.format(position.amount))
return
if price < cost_basis:
is_buy = True
elif (position.amount > 0
and price > cost_basis * (1 + context.PROFIT_TARGET)):
profit = (price * position.amount) - (cost_basis * position.amount)
log.info('closing position, taking profit: {}'.format(profit))
order_target_percent(
asset=context.asset,
target=0,
limit_price=price * (1 - context.SLIPPAGE_ALLOWED),
)
else:
log.info('no buy or sell opportunity found')
else:
is_buy = True
if is_buy:
if buy_increment is None:
log.info('the rsi is too high to consider buying {}'.format(rsi))
return
if price * buy_increment > cash:
log.info('not enough base currency to consider buying')
return
log.info(
'buying position cheaper than cost basis {} < {}'.format(
price,
cost_basis
)
)
order(
asset=context.asset,
amount=buy_increment,
limit_price=price * (1 + context.SLIPPAGE_ALLOWED)
)
def handle_data(context, data):
log.info('handling bar {}'.format(data.current_dt))
# try:
_handle_data(context, data)
# except Exception as e:
# log.warn('aborting the bar on error {}'.format(e))
# context.errors.append(e)
log.info('completed bar {}, total execution errors {}'.format(
data.current_dt,
len(context.errors)
))
if len(context.errors) > 0:
log.info('the errors:\n{}'.format(context.errors))
def analyze(context, stats):
log.info('the daily stats:\n{}'.format(get_pretty_stats(stats)))
pass
if __name__ == '__main__':
run_algorithm(
capital_base=0.001,
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='binance',
live=True,
algo_namespace=algo_namespace,
base_currency='btc',
simulate_orders=True,
)
catalyst/examples/mean_reversion_simple.py
+1 -1
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@@ -244,7 +244,7 @@ def analyze(context=None, perf=None):
if __name__ == '__main__':
# The execution mode: backtest or live
MODE = 'live'
MODE = 'backtest'
if MODE == 'backtest':
folder = os.path.join(