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159 lines
4.3 KiB
Python
159 lines
4.3 KiB
Python
'''
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This algorithm requires an additional library (ta-lib) beyond those required by catalyst.
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Install it first by running:
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$ pip install TA-Lib
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If you get build errors like "fatal error: ta-lib/ta_libc.h: No such file or directory"
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it typically means that it can't find the underlying TA-Lib library and needs to be installed.
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See https://mrjbq7.github.io/ta-lib/install.html for instructions on how to install
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the required dependencies.
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'''
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import talib
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from logbook import Logger
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from catalyst.api import (
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order,
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order_target_percent,
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symbol,
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record,
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get_open_orders,
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)
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from catalyst.exchange.stats_utils import get_pretty_stats
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algo_namespace = 'buy_low_sell_high_xrp'
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log = Logger(algo_namespace)
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def initialize(context):
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log.info('initializing algo')
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context.ASSET_NAME = 'XRP_USD'
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context.asset = symbol(context.ASSET_NAME)
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context.TARGET_POSITIONS = 5000
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context.PROFIT_TARGET = 0.1
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context.SLIPPAGE_ALLOWED = 0.05
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context.retry_check_open_orders = 10
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context.retry_update_portfolio = 10
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context.retry_order = 5
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context.swallow_errors = True
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context.errors = []
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pass
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def _handle_data(context, data):
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prices = data.history(
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context.asset,
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fields='price',
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bar_count=20,
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frequency='15m'
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)
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rsi = talib.RSI(prices.values, timeperiod=14)[-1]
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log.info('got rsi: {}'.format(rsi))
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# Buying more when RSI is low, this should lower our cost basis
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if rsi <= 30:
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buy_increment = 50
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elif rsi <= 40:
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buy_increment = 20
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elif rsi <= 70:
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buy_increment = 5
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else:
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buy_increment = None
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cash = context.portfolio.cash
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log.info('base currency available: {cash}'.format(cash=cash))
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price = data.current(context.asset, 'price')
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log.info('got price {price}'.format(price=price))
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record(
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price=price,
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rsi=rsi,
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)
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orders = get_open_orders(context.asset)
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if orders:
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log.info('skipping bar until all open orders execute')
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return
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is_buy = False
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cost_basis = None
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if context.asset in context.portfolio.positions:
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position = context.portfolio.positions[context.asset]
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cost_basis = position.cost_basis
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log.info(
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'found {amount} positions with cost basis {cost_basis}'.format(
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amount=position.amount,
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cost_basis=cost_basis
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)
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)
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if position.amount >= context.TARGET_POSITIONS:
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log.info('reached positions target: {}'.format(position.amount))
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return
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if price < cost_basis:
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is_buy = True
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elif position.amount > 0 and \
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price > cost_basis * (1 + context.PROFIT_TARGET):
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profit = (price * position.amount) - (cost_basis * position.amount)
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log.info('closing position, taking profit: {}'.format(profit))
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order_target_percent(
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asset=context.asset,
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target=0,
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limit_price=price * (1 - context.SLIPPAGE_ALLOWED),
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)
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else:
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log.info('no buy or sell opportunity found')
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else:
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is_buy = True
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if is_buy:
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if buy_increment is None:
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log.info('the rsi is too high to consider buying {}'.format(rsi))
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return
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if price * buy_increment > cash:
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log.info('not enough base currency to consider buying')
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return
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log.info(
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'buying position cheaper than cost basis {} < {}'.format(
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price,
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cost_basis
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)
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)
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order(
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asset=context.asset,
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amount=buy_increment,
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limit_price=price * (1 + context.SLIPPAGE_ALLOWED)
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)
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def handle_data(context, data):
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log.info('handling bar {}'.format(data.current_dt))
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try:
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_handle_data(context, data)
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except Exception as e:
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log.warn('aborting the bar on error {}'.format(e))
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context.errors.append(e)
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log.info('completed bar {}, total execution errors {}'.format(
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data.current_dt,
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len(context.errors)
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))
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if len(context.errors) > 0:
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log.info('the errors:\n{}'.format(context.errors))
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def analyze(context, stats):
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log.info('the daily stats:\n{}'.format(get_pretty_stats(stats)))
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pass
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