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@vonpupp
Created February 8, 2018 13:52
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# -*- coding: utf-8 -*-
#!/usr/bin/env python2
import sys
import os
import pandas as pd
import signal
#import talib
from logbook import Logger
from catalyst import run_algorithm
from catalyst.api import (
symbol,
record,
order,
order_target,
order_target_percent,
get_open_orders
)
from catalyst.finance import commission
#from base.telegrambot import TelegramBot
class GracefulKiller:
# Source: https://stackoverflow.com/a/31464349
def __init__(self, context):
self.kill_now = False
self.signal = 0
self.context = context
signal.signal(signal.SIGINT, self.exit_gracefully)
def exit_gracefully(self, signum, frame):
self.kill_now = True
self.signal = signum
if hasattr(self.context, 'telegram_bot') and self.context.telegram_bot is not None:
self.context.telegram_bot.updater.stop()
sys.exit(0)
def exit(self):
return self.kill_now
class SimulationParameters:
MODE = 'paper'
CAPITAL_BASE=1000
"""
Capital base used on this simulation
"""
DATA_FREQUECY='minute'
EXCHANGE_NAME='bitfinex'
"""
Exchange used on this simulation
"""
DATA_DIR = '/home/av/Dropbox/simulations/data'
ALGO_NAMESPACE = os.path.basename(__file__).split('.')[0]
ALGO_NAMESPACE_IMAGE = '{}/{}/{}.png'.format(DATA_DIR, 'images', ALGO_NAMESPACE)
ALGO_NAMESPACE_RESULTS_TABLE = '{}/{}/{}.csv'.format(DATA_DIR, 'tables', ALGO_NAMESPACE+'_results')
ALGO_NAMESPACE_TRANSACTIONS_TABLE = '{}/{}/{}.csv'.format(DATA_DIR, 'tables', ALGO_NAMESPACE+'_transactions')
BASE_CURRENCY='usd'
# SHORT PERIOD
START_DATE='2017-09-07'
"""
Start date used on this simulation
"""
END_DATE='2017-12-12'
"""
End date used on this simulation
"""
SKIP_FIRST_CANDLES = 0
#CANDLES_SAMPLE_RATE = 60
#CANDLES_SAMPLE_RATE = 30
CANDLES_SAMPLE_RATE = 1
"""
Candle interval used on this simulation (in minutes)
"""
# http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
# 30 minute interval ohlcv data (the standard data required for candlestick or
# indicators/signals)
# 30T means 30 minutes re-sampling of one minute data.
#CANDLES_FREQUENCY = '60T'
#CANDLES_FREQUENCY = '30T'
CANDLES_FREQUENCY = '1T'
CANDLES_BUFFER_SIZE = 48
COIN_PAIR = 'btc_usd'
"""
Coin pair used on this simulation
"""
# TRANSACTIONS
COMMISSION_FEE = 0.0030
BUY_MIN_AMOUNT = 5 # i.e: USD
SELL_MIN_AMOUNT = 0.001 # i.e: USD
BUY_SELL_PERCENTAGE = 1 #0.50
BUY_PERCENTAGE = BUY_SELL_PERCENTAGE
SELL_PERCENTAGE = BUY_SELL_PERCENTAGE
BASE_PRICE = 'close'
"""
Base price used (close / Heiken Ashi)
"""
log = None
parameters = None
def print_facts(context):
context.log.info("""
Index: {}
Date: {}
Candle:
O: {}
H: {}
L: {}
C: {}
V: {}
Metrics:
...
Portfolio:
Base price: {}
Base coin (coin2/usd): {}
Amount (coin1/btc): {}
""".format(
# Facts
context.i,
context.curr_minute,
context.candles_open[-1],
context.candles_high[-1],
context.candles_low[-1],
context.candles_close[-1],
context.candles_volume[-1],
# Metrics
# ...
# Portfolio
context.curr_base_price,
context.portfolio.cash,
context.portfolio.positions[context.coin_pair].amount,
))
def print_facts_telegram(context):
price = context.curr_base_price
amount = context.portfolio.positions[context.coin_pair].amount
pnl = context.portfolio.pnl
capital_used = context.portfolio.capital_used
portfolio_value = context.portfolio.portfolio_value
portfolio_returns = context.portfolio.returns
starting_cash = context.portfolio.starting_cash
cash = context.portfolio.cash
msg = """
Status...
Price: {}
Starting cash: {}
Cash: {}
Capital used: {}
Amount: {}
Portfolio value: {}
Returns: {}
PnL: {}
""".format(
price,
starting_cash,
cash,
capital_used,
amount,
portfolio_value,
portfolio_returns,
pnl,
)
if hasattr(context, 'telegram_bot') and context.telegram_bot is not None:
context.telegram_bot.msg(msg)
def default_initialize(context):
# FIXME: set_benchmark
#set_benchmark(symbol(context.parameters.COIN_PAIR))
context.coin_pair = symbol(context.parameters.COIN_PAIR)
context.base_price = None
context.current_day = None
context.counter = -1
context.i = 0
context.candles_sample_rate = context.parameters.CANDLES_SAMPLE_RATE
context.candles_frequency = context.parameters.CANDLES_FREQUENCY
context.candles_buffer_size = context.parameters.CANDLES_BUFFER_SIZE
context.set_commission(commission.PerShare(cost=context.parameters.COMMISSION_FEE))
def default_handle_data(context, data):
context.curr_minute = data.current_dt
context.counter += 1
if context.candles_sample_rate == 1:
context.i += 1
elif context.counter % context.candles_sample_rate != 0:
context.i += 1
return
if context.i < context.parameters.SKIP_FIRST_CANDLES:
return
context.candles_open = data.history(
context.coin_pair,
'open',
bar_count=context.candles_buffer_size,
frequency=context.candles_frequency)
context.candles_high = data.history(
context.coin_pair,
'high',
bar_count=context.candles_buffer_size,
frequency=context.candles_frequency)
context.candles_low = data.history(
context.coin_pair,
'low',
bar_count=context.candles_buffer_size,
frequency=context.candles_frequency)
context.candles_close = data.history(
context.coin_pair,
'price',
bar_count=context.candles_buffer_size,
frequency=context.candles_frequency)
context.candles_volume = data.history(
context.coin_pair,
'volume',
bar_count=context.candles_buffer_size,
frequency=context.candles_frequency)
# FIXME: Here is the error!
# The candles_close frame shows more or less always a value of 94, while
# bitcoin price is very different from that
print(context.candles_close)
context.base_prices = context.candles_close
cash = context.portfolio.cash
amount = context.portfolio.positions[context.coin_pair].amount
price = data.current(context.coin_pair, 'price')
order_id = None
context.last_base_price = context.base_prices[-2]
context.curr_base_price = context.base_prices[-1]
# TA calculations
# ...
# Sanity checks
#assert cash >= 0
if cash < 0:
import ipdb; ipdb.set_trace() # BREAKPOINT
print_facts(context)
print_facts_telegram(context)
# Order management
net_shares = 0
if context.counter == 2:
brute_shares = (cash / price) * context.parameters.BUY_PERCENTAGE
share_commission_fee = brute_shares * context.parameters.COMMISSION_FEE
net_shares = brute_shares - share_commission_fee
buy_order_id = order(context.coin_pair, net_shares)
if context.counter == 3:
brute_shares = amount * context.parameters.SELL_PERCENTAGE
share_commission_fee = brute_shares * context.parameters.COMMISSION_FEE
net_shares = -(brute_shares - share_commission_fee)
sell_order_id = order(context.coin_pair, net_shares)
# Record
record(
price=price,
#volume=current['volume'],
#price_change=price_change,
# Metrics
cash=cash,
#buy=context.buy,
#sell=context.sell
)
def default_analyze(context=None, perf=None):
pass
def initialize(context):
global log
context.parameters = parameters
context.log = Logger(context.parameters.ALGO_NAMESPACE)
log = context.log
default_initialize(context)
context.killer = GracefulKiller(context)
context.telegram_bot = None
#TELEGRAM_TOKEN='token'
#context.telegram_bot = TelegramBot()
#context.telegram_bot.initialize(TELEGRAM_TOKEN, context)
if __name__ == '__main__':
# Parameters:
parameters = SimulationParameters()
start_date=pd.to_datetime(parameters.START_DATE, utc=True)
end_date=pd.to_datetime(parameters.END_DATE, utc=True)
if parameters.MODE == 'backtest':
results = run_algorithm(
capital_base=parameters.CAPITAL_BASE,
data_frequency=parameters.DATA_FREQUECY,
initialize=initialize,
handle_data=default_handle_data,
analyze=default_analyze,
exchange_name=parameters.EXCHANGE_NAME,
algo_namespace=parameters.ALGO_NAMESPACE,
base_currency=parameters.BASE_CURRENCY,
start=start_date,
end=end_date,
live=False,
live_graph=False
)
returns_daily = results
results.to_csv('{}'.format(parameters.ALGO_NAMESPACE_RESULTS_TABLE))
# returns_daily = returns_minutely.add(1).groupby(pd.TimeGrouper('24H')).prod().add(-1)
# FIXME: pyfolio integration
#pf_data = pyfolio.utils.extract_rets_pos_txn_from_zipline(results)
#pf_data = pyfolio.utils.extract_rets_pos_txn_from_zipline(results[:'2017-01-01'])
# pyfolio.create_full_tear_sheet(*pf_data)
elif parameters.MODE == 'paper':
results = run_algorithm(
capital_base=parameters.CAPITAL_BASE,
data_frequency=parameters.DATA_FREQUECY,
initialize=initialize,
handle_data=default_handle_data,
analyze=default_analyze,
exchange_name=parameters.EXCHANGE_NAME,
algo_namespace=parameters.ALGO_NAMESPACE,
base_currency=parameters.BASE_CURRENCY,
live=True,
simulate_orders=True,
live_graph=False
)
elif parameters.MODE == 'live':
results = run_algorithm(
initialize=initialize,
handle_data=default_handle_data,
analyze=default_analyze,
exchange_name=parameters.EXCHANGE_NAME,
algo_namespace=parameters.ALGO_NAMESPACE,
base_currency=parameters.BASE_CURRENCY,
live=True,
live_graph=True
)
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