def execute_sell(trade: Trade, limit: float) -> None:
"""
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param limit: limit rate for the sell order
:return: None
"""
# Execute sell and update trade record
order_id = exchange.sell(str(trade.pair), limit, trade.amount)
trade.open_order_id = order_id
fmt_exp_profit = round(trade.calc_profit_percent(rate=limit) * 100, 2)
profit_trade = trade.calc_profit(rate=limit)
message = '*{exchange}:* Selling [{pair}]({pair_url}) with limit `{limit:.8f}`'.format(
exchange=trade.exchange,
pair=trade.pair.replace('_', '/'),
pair_url=exchange.get_pair_detail_url(trade.pair),
limit=limit
)
# For regular case, when the configuration exists
if 'stake_currency' in _CONF and 'fiat_display_currency' in _CONF:
fiat_converter = CryptoToFiatConverter()
profit_fiat = fiat_converter.convert_amount(
profit_trade,
_CONF['stake_currency'],
_CONF['fiat_display_currency']
)
message += '` ({gain}: {profit_percent:.2f}%, {profit_coin:.8f} {coin}`' \
'` / {profit_fiat:.3f} {fiat})`'.format(
gain="profit" if fmt_exp_profit > 0 else "loss",
profit_percent=fmt_exp_profit,
profit_coin=profit_trade,
coin=_CONF['stake_currency'],
profit_fiat=profit_fiat,
fiat=_CONF['fiat_display_currency'],
)
# Because telegram._forcesell does not have the configuration
# Ignore the FIAT value and does not show the stake_currency as well
else:
message += '` ({gain}: {profit_percent:.2f}%, {profit_coin:.8f})`'.format(
gain="profit" if fmt_exp_profit > 0 else "loss",
profit_percent=fmt_exp_profit,
profit_coin=profit_trade
)
# Send the message
rpc.send_msg(message)
Trade.session.flush()
def handle_trade(trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold, False otherwise
"""
if not trade.is_open:
raise ValueError('attempt to handle closed trade: {}'.format(trade))
logger.debug('Handling %s ...', trade)
current_rate = exchange.get_ticker(trade.pair)['bid']
# Check if minimal roi has been reached
if min_roi_reached(trade, current_rate, datetime.utcnow()):
logger.debug('Executing sell due to ROI ...')
execute_sell(trade, current_rate)
return True
# Experimental: Check if sell signal has been enabled and triggered
if _CONF.get('experimental', {}).get('use_sell_signal'):
# Experimental: Check if the trade is profitable before selling it (avoid selling at loss)
if _CONF.get('experimental', {}).get('sell_profit_only'):
logger.debug('Checking if trade is profitable ...')
if trade.calc_profit(rate=current_rate) <= 0:
return False
logger.debug('Checking sell_signal ...')
if get_signal(trade.pair, SignalType.SELL):
logger.debug('Executing sell due to sell signal ...')
execute_sell(trade, current_rate)
return True
return False
def _exec_forcesell(trade: Trade) -> None:
# Check if there is there is an open order
if trade.open_order_id:
order = exchange.get_order(trade.open_order_id)
# Cancel open LIMIT_BUY orders and close trade
if order and not order['closed'] and order['type'] == 'LIMIT_BUY':
exchange.cancel_order(trade.open_order_id)
trade.close(order.get('rate') or trade.open_rate)
# TODO: sell amount which has been bought already
return
# Ignore trades with an attached LIMIT_SELL order
if order and not order['closed'] and order['type'] == 'LIMIT_SELL':
return
# Get current rate and execute sell
current_rate = exchange.get_ticker(trade.pair, False)['bid']
from freqtrade.main import execute_sell
execute_sell(trade, current_rate)
def min_roi_reached(trade: Trade, current_rate: float, current_time: datetime) -> bool:
"""
Based an earlier trade and current price and ROI configuration, decides whether bot should sell
:return True if bot should sell at current rate
"""
current_profit = trade.calc_profit_percent(current_rate)
if 'stoploss' in _CONF and current_profit < float(_CONF['stoploss']):
logger.debug('Stop loss hit.')
return True
# Check if time matches and current rate is above threshold
time_diff = (current_time - trade.open_date).total_seconds() / 60
for duration, threshold in sorted(_CONF['minimal_roi'].items()):
if time_diff > float(duration) and current_profit > threshold:
return True
logger.debug('Threshold not reached. (cur_profit: %1.2f%%)', float(current_profit) * 100.0)
return False
def execute_sell(self, trade: Trade, limit: float,
sell_reason: SellType) -> None:
"""
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param limit: limit rate for the sell order
:param sellreason: Reason the sell was triggered
:return: None
"""
sell_type = 'sell'
if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
sell_type = 'stoploss'
# if stoploss is on exchange and we are on dry_run mode,
# we consider the sell price stop price
if self.config.get('dry_run', False) and sell_type == 'stoploss' \
and self.strategy.order_types['stoploss_on_exchange']:
limit = trade.stop_loss
# First cancelling stoploss on exchange ...
if self.strategy.order_types.get(
'stoploss_on_exchange') and trade.stoploss_order_id:
self.exchange.cancel_order(trade.stoploss_order_id, trade.pair)
# Execute sell and update trade record
order_id = self.exchange.sell(
pair=str(trade.pair),
ordertype=self.strategy.order_types[sell_type],
amount=trade.amount,
rate=limit,
time_in_force=self.strategy.order_time_in_force['sell'])['id']
trade.open_order_id = order_id
trade.close_rate_requested = limit
trade.sell_reason = sell_reason.value
profit_trade = trade.calc_profit(rate=limit)
current_rate = self.exchange.get_ticker(trade.pair)['bid']
profit_percent = trade.calc_profit_percent(limit)
pair_url = self.exchange.get_pair_detail_url(trade.pair)
gain = "profit" if profit_percent > 0 else "loss"
msg = {
'type': RPCMessageType.SELL_NOTIFICATION,
'exchange': trade.exchange.capitalize(),
'pair': trade.pair,
'gain': gain,
'market_url': pair_url,
'limit': limit,
'amount': trade.amount,
'open_rate': trade.open_rate,
'current_rate': current_rate,
'profit_amount': profit_trade,
'profit_percent': profit_percent,
'sell_reason': sell_reason.value
}
# For regular case, when the configuration exists
if 'stake_currency' in self.config and 'fiat_display_currency' in self.config:
stake_currency = self.config['stake_currency']
fiat_currency = self.config['fiat_display_currency']
msg.update({
'stake_currency': stake_currency,
'fiat_currency': fiat_currency,
})
# Send the message
self.rpc.send_msg(msg)
Trade.session.flush()
def min_roi_reached_dynamic(
self, trade: Trade, current_profit: float, current_time: datetime,
trade_dur: int) -> Tuple[Optional[int], Optional[float]]:
dynamic_roi = self.get_pair_params(trade.pair, 'dynamic_roi')
minimal_roi = self.get_pair_params(trade.pair, 'minimal_roi')
if not dynamic_roi or not minimal_roi:
return None, None
_, table_roi = self.min_roi_reached_entry(trade_dur, trade.pair)
# see if we have the data we need to do this, otherwise fall back to the standard table
if self.custom_trade_info and trade and trade.pair in self.custom_trade_info:
if self.config['runmode'].value in ('live', 'dry_run'):
dataframe, last_updated = self.dp.get_analyzed_dataframe(
pair=trade.pair, timeframe=self.timeframe)
roc = dataframe['roc'].iat[-1]
atr = dataframe['atr'].iat[-1]
rmi_slow = dataframe['rmi-slow'].iat[-1]
rmi_trend = dataframe['rmi-up-trend'].iat[-1]
# If in backtest or hyperopt, get the indicator values out of the trades dict (Thanks @JoeSchr!)
else:
roc = self.custom_trade_info[
trade.pair]['roc'].loc[current_time]['roc']
atr = self.custom_trade_info[
trade.pair]['atr'].loc[current_time]['atr']
rmi_slow = self.custom_trade_info[
trade.pair]['rmi-slow'].loc[current_time]['rmi-slow']
rmi_trend = self.custom_trade_info[trade.pair][
'rmi-up-trend'].loc[current_time]['rmi-up-trend']
d = dynamic_roi
profit_factor = (1 - (rmi_slow / d['profit-factor']))
rmi_grow = cta.linear_growth(d['rmi-start'], d['rmi-end'],
d['grow-delay'], d['grow-time'],
trade_dur)
max_profit = trade.calc_profit_ratio(trade.max_rate)
open_rate = trade.open_rate
atr_roi = max(d['min-roc-atr'],
((open_rate + atr) / open_rate) - 1)
roc_roi = max(d['min-roc-atr'], (roc / 100))
# atr as the fallback (if > min-roc-atr)
if d['fallback'] == 'atr':
min_roi = atr_roi
# roc as the fallback (if > min-roc-atr)
elif d['fallback'] == 'roc':
min_roi = roc_roi
# atr or table as the fallback (whichever is larger)
elif d['fallback'] == 'atr-table':
min_roi = max(table_roi, atr_roi)
# roc or table as the fallback (whichever is larger)
elif d['fallback'] == 'roc-table':
min_roi = max(table_roi, roc_roi)
# default to table
else:
min_roi = table_roi
# If we observe a strong upward trend and our current profit has not retreated from the peak by much, hold
if (rmi_trend == 1) and (rmi_slow > rmi_grow):
if current_profit > min_roi and (current_profit <
(max_profit * profit_factor)):
min_roi = min_roi
else:
min_roi = 100
"""
# If we observe a strong upward trend and our current profit has not retreated from the peak by much, hold
if (current_profit > (max_profit * profit_factor)) and (rmi_trend == 1) and (rmi_slow > rmi_grow):
min_roi = 100
"""
else:
min_roi = table_roi
# Attempting to wedge the dynamic roi value into a thing so we can trick backtesting...
if self.config['runmode'].value not in ('live', 'dry_run'):
# Theoretically, if backtesting uses this value, ROI was triggered so we need to trick it with a sell
# rate other than what is on the standard ROI table...
self.custom_trade_info['backtest']['roi'] = max(
min_roi, current_profit)
return trade_dur, min_roi
def backtest(stake_amount: float, processed: Dict[str, DataFrame],
max_open_trades: int = 0, realistic: bool = True, sell_profit_only: bool = False,
stoploss: int = -1.00, use_sell_signal: bool = False) -> DataFrame:
"""
Implements backtesting functionality
:param stake_amount: btc amount to use for each trade
:param processed: a processed dictionary with format {pair, data}
:param max_open_trades: maximum number of concurrent trades (default: 0, disabled)
:param realistic: do we try to simulate realistic trades? (default: True)
:return: DataFrame
"""
trades = []
trade_count_lock: dict = {}
exchange._API = Bittrex({'key': '', 'secret': ''})
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0
ticker = populate_sell_trend(populate_buy_trend(pair_data))
# for each buy point
lock_pair_until = None
buy_subset = ticker[ticker.buy == 1][['buy', 'open', 'close', 'date', 'sell']]
for row in buy_subset.itertuples(index=True):
if realistic:
if lock_pair_until is not None and row.Index <= lock_pair_until:
continue
if max_open_trades > 0:
# Check if max_open_trades has already been reached for the given date
if not trade_count_lock.get(row.date, 0) < max_open_trades:
continue
if max_open_trades > 0:
# Increase lock
trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
trade = Trade(
open_rate=row.close,
open_date=row.date,
stake_amount=stake_amount,
amount=stake_amount / row.open,
fee=exchange.get_fee()
)
# calculate win/lose forwards from buy point
sell_subset = ticker[row.Index + 1:][['close', 'date', 'sell']]
for row2 in sell_subset.itertuples(index=True):
if max_open_trades > 0:
# Increase trade_count_lock for every iteration
trade_count_lock[row2.date] = trade_count_lock.get(row2.date, 0) + 1
current_profit_percent = trade.calc_profit_percent(rate=row2.close)
if (sell_profit_only and current_profit_percent < 0):
continue
if min_roi_reached(trade, row2.close, row2.date) or \
(row2.sell == 1 and use_sell_signal) or \
current_profit_percent <= stoploss:
current_profit_btc = trade.calc_profit(rate=row2.close)
lock_pair_until = row2.Index
trades.append(
(
pair,
current_profit_percent,
current_profit_btc,
row2.Index - row.Index,
current_profit_btc > 0,
current_profit_btc < 0
)
)
break
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration', 'profit', 'loss']
return DataFrame.from_records(trades, columns=labels)
def _rpc_forcesell(self, trade_id: str) -> Dict[str, str]:
"""
Handler for forcesell <id>.
Sells the given trade at current price
"""
def _exec_forcesell(trade: Trade) -> None:
# Check if there is there is an open order
if trade.open_order_id:
order = self._freqtrade.exchange.get_order(
trade.open_order_id, trade.pair)
# Cancel open LIMIT_BUY orders and close trade
if order and order['status'] == 'open' \
and order['type'] == 'limit' \
and order['side'] == 'buy':
self._freqtrade.exchange.cancel_order(
trade.open_order_id, trade.pair)
trade.close(order.get('price') or trade.open_rate)
# Do the best effort, if we don't know 'filled' amount, don't try selling
if order['filled'] is None:
return
trade.amount = order['filled']
# Ignore trades with an attached LIMIT_SELL order
if order and order['status'] == 'open' \
and order['type'] == 'limit' \
and order['side'] == 'sell':
return
# Get current rate and execute sell
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
self._freqtrade.execute_sell(trade, current_rate,
SellType.FORCE_SELL)
# ---- EOF def _exec_forcesell ----
if self._freqtrade.state != State.RUNNING:
raise RPCException('trader is not running')
with self._freqtrade._sell_lock:
if trade_id == 'all':
# Execute sell for all open orders
for trade in Trade.get_open_trades():
_exec_forcesell(trade)
Trade.session.flush()
self._freqtrade.wallets.update()
return {'result': 'Created sell orders for all open trades.'}
# Query for trade
trade = Trade.get_trades(trade_filter=[
Trade.id == trade_id,
Trade.is_open.is_(True),
]).first()
if not trade:
logger.warning('forcesell: Invalid argument received')
raise RPCException('invalid argument')
_exec_forcesell(trade)
Trade.session.flush()
self._freqtrade.wallets.update()
return {'result': f'Created sell order for trade {trade_id}.'}
def _rpc_trade_statistics(
self,
stake_currency: str,
fiat_display_currency: str,
start_date: datetime = datetime.fromtimestamp(0)
) -> Dict[str, Any]:
""" Returns cumulative profit statistics """
trade_filter = ((Trade.is_open.is_(False) &
(Trade.close_date >= start_date))
| Trade.is_open.is_(True))
trades = Trade.get_trades(trade_filter).order_by(Trade.id).all()
profit_all_coin = []
profit_all_ratio = []
profit_closed_coin = []
profit_closed_ratio = []
durations = []
winning_trades = 0
losing_trades = 0
for trade in trades:
current_rate: float = 0.0
if not trade.open_rate:
continue
if trade.close_date:
durations.append(
(trade.close_date - trade.open_date).total_seconds())
if not trade.is_open:
profit_ratio = trade.close_profit
profit_closed_coin.append(trade.close_profit_abs)
profit_closed_ratio.append(profit_ratio)
if trade.close_profit >= 0:
winning_trades += 1
else:
losing_trades += 1
else:
# Get current rate
try:
current_rate = self._freqtrade.exchange.get_sell_rate(
trade.pair, False)
except (PricingError, ExchangeError):
current_rate = NAN
profit_ratio = trade.calc_profit_ratio(rate=current_rate)
profit_all_coin.append(
trade.calc_profit(rate=trade.close_rate or current_rate))
profit_all_ratio.append(profit_ratio)
best_pair = Trade.get_best_pair(start_date)
# Prepare data to display
profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
profit_closed_ratio_mean = float(
mean(profit_closed_ratio) if profit_closed_ratio else 0.0)
profit_closed_ratio_sum = sum(
profit_closed_ratio) if profit_closed_ratio else 0.0
profit_closed_fiat = self._fiat_converter.convert_amount(
profit_closed_coin_sum, stake_currency,
fiat_display_currency) if self._fiat_converter else 0
profit_all_coin_sum = round(sum(profit_all_coin), 8)
profit_all_ratio_mean = float(
mean(profit_all_ratio) if profit_all_ratio else 0.0)
profit_all_ratio_sum = sum(
profit_all_ratio) if profit_all_ratio else 0.0
profit_all_fiat = self._fiat_converter.convert_amount(
profit_all_coin_sum, stake_currency,
fiat_display_currency) if self._fiat_converter else 0
first_date = trades[0].open_date if trades else None
last_date = trades[-1].open_date if trades else None
num = float(len(durations) or 1)
return {
'profit_closed_coin':
profit_closed_coin_sum,
'profit_closed_percent_mean':
round(profit_closed_ratio_mean * 100, 2),
'profit_closed_ratio_mean':
profit_closed_ratio_mean,
'profit_closed_percent_sum':
round(profit_closed_ratio_sum * 100, 2),
'profit_closed_ratio_sum':
profit_closed_ratio_sum,
'profit_closed_fiat':
profit_closed_fiat,
'profit_all_coin':
profit_all_coin_sum,
'profit_all_percent_mean':
round(profit_all_ratio_mean * 100, 2),
'profit_all_ratio_mean':
profit_all_ratio_mean,
'profit_all_percent_sum':
round(profit_all_ratio_sum * 100, 2),
'profit_all_ratio_sum':
profit_all_ratio_sum,
'profit_all_fiat':
profit_all_fiat,
'trade_count':
len(trades),
'closed_trade_count':
len([t for t in trades if not t.is_open]),
'first_trade_date':
arrow.get(first_date).humanize() if first_date else '',
'first_trade_timestamp':
int(first_date.timestamp() * 1000) if first_date else 0,
'latest_trade_date':
arrow.get(last_date).humanize() if last_date else '',
'latest_trade_timestamp':
int(last_date.timestamp() * 1000) if last_date else 0,
'avg_duration':
str(timedelta(seconds=sum(durations) / num)).split('.')[0],
'best_pair':
best_pair[0] if best_pair else '',
'best_rate':
round(best_pair[1] * 100, 2) if best_pair else 0,
'winning_trades':
winning_trades,
'losing_trades':
losing_trades,
}
def stop_loss_reached(self,
current_rate: float,
trade: Trade,
current_time: datetime,
current_profit: float,
force_stoploss: float,
high: float = None) -> SellCheckTuple:
"""
Based on current profit of the trade and configured (trailing) stoploss,
decides to sell or not
:param current_profit: current profit in percent
"""
trailing_stop = self.config.get('trailing_stop', False)
stop_loss_value = force_stoploss if force_stoploss else self.stoploss
# Initiate stoploss with open_rate. Does nothing if stoploss is already set.
trade.adjust_stop_loss(trade.open_rate, stop_loss_value, initial=True)
if trailing_stop:
# trailing stoploss handling
sl_offset = self.config.get('trailing_stop_positive_offset') or 0.0
tsl_only_offset = self.config.get(
'trailing_only_offset_is_reached', False)
# Make sure current_profit is calculated using high for backtesting.
high_profit = current_profit if not high else trade.calc_profit_percent(
high)
# Don't update stoploss if trailing_only_offset_is_reached is true.
if not (tsl_only_offset and high_profit < sl_offset):
# Specific handling for trailing_stop_positive
if 'trailing_stop_positive' in self.config and high_profit > sl_offset:
# Ignore mypy error check in configuration that this is a float
stop_loss_value = self.config.get(
'trailing_stop_positive') # type: ignore
logger.debug(
f"{trade.pair} - Using positive stoploss: {stop_loss_value} "
f"offset: {sl_offset:.4g} profit: {current_profit:.4f}%"
)
trade.adjust_stop_loss(high or current_rate, stop_loss_value)
# evaluate if the stoploss was hit if stoploss is not on exchange
if ((self.stoploss is not None) and (trade.stop_loss >= current_rate)
and (not self.order_types.get('stoploss_on_exchange'))):
sell_type = SellType.STOP_LOSS
# If initial stoploss is not the same as current one then it is trailing.
if trade.initial_stop_loss != trade.stop_loss:
sell_type = SellType.TRAILING_STOP_LOSS
logger.debug(
f"{trade.pair} - HIT STOP: current price at {current_rate:.6f}, "
f"stoploss is {trade.stop_loss:.6f}, "
f"initial stoploss was at {trade.initial_stop_loss:.6f}, "
f"trade opened at {trade.open_rate:.6f}")
logger.debug(
f"{trade.pair} - Trailing stop saved "
f"{trade.stop_loss - trade.initial_stop_loss:.6f}")
return SellCheckTuple(sell_flag=True, sell_type=sell_type)
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
def test_calc_profit_ratio(limit_buy_order, limit_sell_order, fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
amount=5,
open_rate=0.00001099,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='bittrex',
)
trade.open_order_id = 'something'
trade.update(limit_buy_order) # Buy @ 0.00001099
# Get percent of profit with a custom rate (Higher than open rate)
assert trade.calc_profit_ratio(rate=0.00001234) == 0.11723875
# Get percent of profit with a custom rate (Lower than open rate)
assert trade.calc_profit_ratio(rate=0.00000123) == -0.88863828
# Test when we apply a Sell order. Sell higher than open rate @ 0.00001173
trade.update(limit_sell_order)
assert trade.calc_profit_ratio() == 0.06201058
# Test with a custom fee rate on the close trade
assert trade.calc_profit_ratio(fee=0.003) == 0.06147824
def test_update_with_bittrex(limit_buy_order, limit_sell_order, fee, caplog):
"""
On this test we will buy and sell a crypto currency.
Buy
- Buy: 90.99181073 Crypto at 0.00001099 BTC
(90.99181073*0.00001099 = 0.0009999 BTC)
- Buying fee: 0.25%
- Total cost of buy trade: 0.001002500 BTC
((90.99181073*0.00001099) + ((90.99181073*0.00001099)*0.0025))
Sell
- Sell: 90.99181073 Crypto at 0.00001173 BTC
(90.99181073*0.00001173 = 0,00106733394 BTC)
- Selling fee: 0.25%
- Total cost of sell trade: 0.001064666 BTC
((90.99181073*0.00001173) - ((90.99181073*0.00001173)*0.0025))
Profit/Loss: +0.000062166 BTC
(Sell:0.001064666 - Buy:0.001002500)
Profit/Loss percentage: 0.0620
((0.001064666/0.001002500)-1 = 6.20%)
:param limit_buy_order:
:param limit_sell_order:
:return:
"""
trade = Trade(
id=2,
pair='ETH/BTC',
stake_amount=0.001,
open_rate=0.01,
amount=5,
is_open=True,
open_date=arrow.utcnow().datetime,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='bittrex',
)
assert trade.open_order_id is None
assert trade.close_profit is None
assert trade.close_date is None
trade.open_order_id = 'something'
trade.update(limit_buy_order)
assert trade.open_order_id is None
assert trade.open_rate == 0.00001099
assert trade.close_profit is None
assert trade.close_date is None
assert log_has_re(
r"LIMIT_BUY has been fulfilled for Trade\(id=2, "
r"pair=ETH/BTC, amount=90.99181073, open_rate=0.00001099, open_since=.*\).",
caplog)
caplog.clear()
trade.open_order_id = 'something'
trade.update(limit_sell_order)
assert trade.open_order_id is None
assert trade.close_rate == 0.00001173
assert trade.close_profit == 0.06201058
assert trade.close_date is not None
assert log_has_re(
r"LIMIT_SELL has been fulfilled for Trade\(id=2, "
r"pair=ETH/BTC, amount=90.99181073, open_rate=0.00001099, open_since=.*\).",
caplog)
def test_calc_open_close_trade_price(limit_buy_order, limit_sell_order, fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
open_rate=0.01,
amount=5,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='bittrex',
)
trade.open_order_id = 'something'
trade.update(limit_buy_order)
assert trade._calc_open_trade_value() == 0.0010024999999225068
trade.update(limit_sell_order)
assert trade.calc_close_trade_value() == 0.0010646656050132426
# Profit in BTC
assert trade.calc_profit() == 0.00006217
# Profit in percent
assert trade.calc_profit_ratio() == 0.06201058
def test_calc_profit(limit_buy_order, limit_sell_order, fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
amount=5,
open_rate=0.00001099,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='bittrex',
)
trade.open_order_id = 'something'
trade.update(limit_buy_order) # Buy @ 0.00001099
# Custom closing rate and regular fee rate
# Higher than open rate
assert trade.calc_profit(rate=0.00001234) == 0.00011753
# Lower than open rate
assert trade.calc_profit(rate=0.00000123) == -0.00089086
# Custom closing rate and custom fee rate
# Higher than open rate
assert trade.calc_profit(rate=0.00001234, fee=0.003) == 0.00011697
# Lower than open rate
assert trade.calc_profit(rate=0.00000123, fee=0.003) == -0.00089092
# Test when we apply a Sell order. Sell higher than open rate @ 0.00001173
trade.update(limit_sell_order)
assert trade.calc_profit() == 0.00006217
# Test with a custom fee rate on the close trade
assert trade.calc_profit(fee=0.003) == 0.00006163
def test_fee_updated(fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
fee_open=fee.return_value,
open_date=arrow.utcnow().shift(hours=-2).datetime,
amount=10,
fee_close=fee.return_value,
exchange='bittrex',
open_rate=1,
max_rate=1,
)
assert trade.fee_open_currency is None
assert not trade.fee_updated('buy')
assert not trade.fee_updated('sell')
assert not trade.fee_updated('asdf')
trade.update_fee(0.15, 'BTC', 0.0075, 'buy')
assert trade.fee_updated('buy')
assert not trade.fee_updated('sell')
assert trade.fee_open_currency is not None
assert trade.fee_close_currency is None
trade.update_fee(0.15, 'ABC', 0.0075, 'sell')
assert trade.fee_updated('buy')
assert trade.fee_updated('sell')
assert not trade.fee_updated('asfd')
def stop_loss_reached(self, current_rate: float, trade: Trade,
current_time: datetime, current_profit: float,
force_stoploss: float, low: float = None,
high: float = None) -> SellCheckTuple:
"""
Based on current profit of the trade and configured (trailing) stoploss,
decides to sell or not
:param current_profit: current profit as ratio
:param low: Low value of this candle, only set in backtesting
:param high: High value of this candle, only set in backtesting
"""
stop_loss_value = force_stoploss if force_stoploss else self.stoploss
# Initiate stoploss with open_rate. Does nothing if stoploss is already set.
trade.adjust_stop_loss(trade.open_rate, stop_loss_value, initial=True)
if self.use_custom_stoploss and trade.stop_loss < (low or current_rate):
stop_loss_value = strategy_safe_wrapper(self.custom_stoploss, default_retval=None
)(pair=trade.pair, trade=trade,
current_time=current_time,
current_rate=current_rate,
current_profit=current_profit)
# Sanity check - error cases will return None
if stop_loss_value:
# logger.info(f"{trade.pair} {stop_loss_value=} {current_profit=}")
trade.adjust_stop_loss(current_rate, stop_loss_value)
else:
logger.warning("CustomStoploss function did not return valid stoploss")
if self.trailing_stop and trade.stop_loss < (low or current_rate):
# trailing stoploss handling
sl_offset = self.trailing_stop_positive_offset
# Make sure current_profit is calculated using high for backtesting.
high_profit = current_profit if not high else trade.calc_profit_ratio(high)
# Don't update stoploss if trailing_only_offset_is_reached is true.
if not (self.trailing_only_offset_is_reached and high_profit < sl_offset):
# Specific handling for trailing_stop_positive
if self.trailing_stop_positive is not None and high_profit > sl_offset:
stop_loss_value = self.trailing_stop_positive
logger.debug(f"{trade.pair} - Using positive stoploss: {stop_loss_value} "
f"offset: {sl_offset:.4g} profit: {current_profit:.2%}")
trade.adjust_stop_loss(high or current_rate, stop_loss_value)
# evaluate if the stoploss was hit if stoploss is not on exchange
# in Dry-Run, this handles stoploss logic as well, as the logic will not be different to
# regular stoploss handling.
if ((trade.stop_loss >= (low or current_rate)) and
(not self.order_types.get('stoploss_on_exchange') or self.config['dry_run'])):
sell_type = SellType.STOP_LOSS
# If initial stoploss is not the same as current one then it is trailing.
if trade.initial_stop_loss != trade.stop_loss:
sell_type = SellType.TRAILING_STOP_LOSS
logger.debug(
f"{trade.pair} - HIT STOP: current price at {(low or current_rate):.6f}, "
f"stoploss is {trade.stop_loss:.6f}, "
f"initial stoploss was at {trade.initial_stop_loss:.6f}, "
f"trade opened at {trade.open_rate:.6f}")
logger.debug(f"{trade.pair} - Trailing stop saved "
f"{trade.stop_loss - trade.initial_stop_loss:.6f}")
return SellCheckTuple(sell_type=sell_type)
return SellCheckTuple(sell_type=SellType.NONE)
def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool,
sell: bool, low: float = None, high: float = None,
force_stoploss: float = 0) -> SellCheckTuple:
"""
This function evaluates if one of the conditions required to trigger a sell
has been reached, which can either be a stop-loss, ROI or sell-signal.
:param low: Only used during backtesting to simulate stoploss
:param high: Only used during backtesting, to simulate ROI
:param force_stoploss: Externally provided stoploss
:return: True if trade should be sold, False otherwise
"""
current_rate = rate
current_profit = trade.calc_profit_ratio(current_rate)
trade.adjust_min_max_rates(high or current_rate, low or current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=date, current_profit=current_profit,
force_stoploss=force_stoploss, low=low, high=high)
# Set current rate to high for backtesting sell
current_rate = high or rate
current_profit = trade.calc_profit_ratio(current_rate)
# if buy signal and ignore_roi is set, we don't need to evaluate min_roi.
roi_reached = (not (buy and self.ignore_roi_if_buy_signal)
and self.min_roi_reached(trade=trade, current_profit=current_profit,
current_time=date))
sell_signal = SellType.NONE
custom_reason = ''
# use provided rate in backtesting, not high/low.
current_rate = rate
current_profit = trade.calc_profit_ratio(current_rate)
if (self.sell_profit_only and current_profit <= self.sell_profit_offset):
# sell_profit_only and profit doesn't reach the offset - ignore sell signal
pass
elif self.use_sell_signal and not buy:
if sell:
sell_signal = SellType.SELL_SIGNAL
else:
custom_reason = strategy_safe_wrapper(self.custom_sell, default_retval=False)(
pair=trade.pair, trade=trade, current_time=date, current_rate=current_rate,
current_profit=current_profit)
if custom_reason:
sell_signal = SellType.CUSTOM_SELL
if isinstance(custom_reason, str):
if len(custom_reason) > CUSTOM_SELL_MAX_LENGTH:
logger.warning(f'Custom sell reason returned from custom_sell is too '
f'long and was trimmed to {CUSTOM_SELL_MAX_LENGTH} '
f'characters.')
custom_reason = custom_reason[:CUSTOM_SELL_MAX_LENGTH]
else:
custom_reason = None
# TODO: return here if sell-signal should be favored over ROI
# Start evaluations
# Sequence:
# ROI (if not stoploss)
# Sell-signal
# Stoploss
if roi_reached and stoplossflag.sell_type != SellType.STOP_LOSS:
logger.debug(f"{trade.pair} - Required profit reached. sell_type=SellType.ROI")
return SellCheckTuple(sell_type=SellType.ROI)
if sell_signal != SellType.NONE:
logger.debug(f"{trade.pair} - Sell signal received. "
f"sell_type=SellType.{sell_signal.name}" +
(f", custom_reason={custom_reason}" if custom_reason else ""))
return SellCheckTuple(sell_type=sell_signal, sell_reason=custom_reason)
if stoplossflag.sell_flag:
logger.debug(f"{trade.pair} - Stoploss hit. sell_type={stoplossflag.sell_type}")
return stoplossflag
# This one is noisy, commented out...
# logger.debug(f"{trade.pair} - No sell signal.")
return SellCheckTuple(sell_type=SellType.NONE)
def __init__(self, config: Dict[str, Any]) -> None:
LoggingMixin.show_output = False
self.config = config
# Reset keys for backtesting
remove_credentials(self.config)
self.strategylist: List[IStrategy] = []
self.all_results: Dict[str, Dict] = {}
self.exchange = ExchangeResolver.load_exchange(
self.config['exchange']['name'], self.config)
self.dataprovider = DataProvider(self.config, None)
if self.config.get('strategy_list', None):
for strat in list(self.config['strategy_list']):
stratconf = deepcopy(self.config)
stratconf['strategy'] = strat
self.strategylist.append(
StrategyResolver.load_strategy(stratconf))
validate_config_consistency(stratconf)
else:
# No strategy list specified, only one strategy
self.strategylist.append(
StrategyResolver.load_strategy(self.config))
validate_config_consistency(self.config)
if "timeframe" not in self.config:
raise OperationalException(
"Timeframe (ticker interval) needs to be set in either "
"configuration or as cli argument `--timeframe 5m`")
self.timeframe = str(self.config.get('timeframe'))
self.timeframe_min = timeframe_to_minutes(self.timeframe)
self.pairlists = PairListManager(self.exchange, self.config)
if 'VolumePairList' in self.pairlists.name_list:
raise OperationalException(
"VolumePairList not allowed for backtesting.")
if 'PerformanceFilter' in self.pairlists.name_list:
raise OperationalException(
"PerformanceFilter not allowed for backtesting.")
if len(self.strategylist
) > 1 and 'PrecisionFilter' in self.pairlists.name_list:
raise OperationalException(
"PrecisionFilter not allowed for backtesting multiple strategies."
)
self.dataprovider.add_pairlisthandler(self.pairlists)
self.pairlists.refresh_pairlist()
if len(self.pairlists.whitelist) == 0:
raise OperationalException("No pair in whitelist.")
if config.get('fee', None) is not None:
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee(
symbol=self.pairlists.whitelist[0])
Trade.use_db = False
Trade.reset_trades()
PairLocks.timeframe = self.config['timeframe']
PairLocks.use_db = False
PairLocks.reset_locks()
self.wallets = Wallets(self.config, self.exchange, log=False)
# Get maximum required startup period
self.required_startup = max(
[strat.startup_candle_count for strat in self.strategylist])
def test_adjust_stop_loss(fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
amount=5,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='bittrex',
open_rate=1,
max_rate=1,
)
trade.adjust_stop_loss(trade.open_rate, 0.05, True)
assert trade.stop_loss == 0.95
assert trade.stop_loss_pct == -0.05
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# Get percent of profit with a lower rate
trade.adjust_stop_loss(0.96, 0.05)
assert trade.stop_loss == 0.95
assert trade.stop_loss_pct == -0.05
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# Get percent of profit with a custom rate (Higher than open rate)
trade.adjust_stop_loss(1.3, -0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.stop_loss_pct == -0.1
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# current rate lower again ... should not change
trade.adjust_stop_loss(1.2, 0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# current rate higher... should raise stoploss
trade.adjust_stop_loss(1.4, 0.1)
assert round(trade.stop_loss, 8) == 1.26
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# Initial is true but stop_loss set - so doesn't do anything
trade.adjust_stop_loss(1.7, 0.1, True)
assert round(trade.stop_loss, 8) == 1.26
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
assert trade.stop_loss_pct == -0.1
def _rpc_trade_status(self,
trade_ids: List[int] = []) -> List[Dict[str, Any]]:
"""
Below follows the RPC backend it is prefixed with rpc_ to raise awareness that it is
a remotely exposed function
"""
# Fetch open trades
if trade_ids:
trades = Trade.get_trades(
trade_filter=Trade.id.in_(trade_ids)).all()
else:
trades = Trade.get_open_trades()
if not trades:
raise RPCException('no active trade')
else:
results = []
for trade in trades:
order = None
if trade.open_order_id:
order = self._freqtrade.exchange.fetch_order(
trade.open_order_id, trade.pair)
# calculate profit and send message to user
if trade.is_open:
try:
current_rate = self._freqtrade.exchange.get_sell_rate(
trade.pair, False)
except (ExchangeError, PricingError):
current_rate = NAN
else:
current_rate = trade.close_rate
current_profit = trade.calc_profit_ratio(current_rate)
current_profit_abs = trade.calc_profit(current_rate)
current_profit_fiat: Optional[float] = None
# Calculate fiat profit
if self._fiat_converter:
current_profit_fiat = self._fiat_converter.convert_amount(
current_profit_abs,
self._freqtrade.config['stake_currency'],
self._freqtrade.config['fiat_display_currency'])
# Calculate guaranteed profit (in case of trailing stop)
stoploss_entry_dist = trade.calc_profit(trade.stop_loss)
stoploss_entry_dist_ratio = trade.calc_profit_ratio(
trade.stop_loss)
# calculate distance to stoploss
stoploss_current_dist = trade.stop_loss - current_rate
stoploss_current_dist_ratio = stoploss_current_dist / current_rate
trade_dict = trade.to_json()
trade_dict.update(
dict(
base_currency=self._freqtrade.config['stake_currency'],
close_profit=trade.close_profit
if trade.close_profit is not None else None,
current_rate=current_rate,
current_profit=current_profit, # Deprecated
current_profit_pct=round(current_profit * 100,
2), # Deprecated
current_profit_abs=current_profit_abs, # Deprecated
profit_ratio=current_profit,
profit_pct=round(current_profit * 100, 2),
profit_abs=current_profit_abs,
profit_fiat=current_profit_fiat,
stoploss_current_dist=stoploss_current_dist,
stoploss_current_dist_ratio=round(
stoploss_current_dist_ratio, 8),
stoploss_current_dist_pct=round(
stoploss_current_dist_ratio * 100, 2),
stoploss_entry_dist=stoploss_entry_dist,
stoploss_entry_dist_ratio=round(
stoploss_entry_dist_ratio, 8),
open_order='({} {} rem={:.8f})'.format(
order['type'], order['side'], order['remaining'])
if order else None,
))
results.append(trade_dict)
return results
def test_api_performance(botclient, fee):
ftbot, client = botclient
patch_get_signal(ftbot, (True, False, None))
trade = Trade(
pair='LTC/ETH',
amount=1,
exchange='binance',
stake_amount=1,
open_rate=0.245441,
open_order_id="123456",
is_open=False,
fee_close=fee.return_value,
fee_open=fee.return_value,
close_rate=0.265441,
)
trade.close_profit = trade.calc_profit_ratio()
trade.close_profit_abs = trade.calc_profit()
Trade.query.session.add(trade)
trade = Trade(
pair='XRP/ETH',
amount=5,
stake_amount=1,
exchange='binance',
open_rate=0.412,
open_order_id="123456",
is_open=False,
fee_close=fee.return_value,
fee_open=fee.return_value,
close_rate=0.391
)
trade.close_profit = trade.calc_profit_ratio()
trade.close_profit_abs = trade.calc_profit()
Trade.query.session.add(trade)
Trade.query.session.flush()
rc = client_get(client, f"{BASE_URI}/performance")
assert_response(rc)
assert len(rc.json()) == 2
assert rc.json() == [{'count': 1, 'pair': 'LTC/ETH', 'profit': 7.61, 'profit_abs': 0.01872279},
{'count': 1, 'pair': 'XRP/ETH', 'profit': -5.57, 'profit_abs': -0.1150375}]
def should_sell(self,
trade: Trade,
rate: float,
date: datetime,
buy: bool,
sell: bool,
low: float = None,
high: float = None,
force_stoploss: float = 0) -> SellCheckTuple:
"""
This function evaluates if one of the conditions required to trigger a sell
has been reached, which can either be a stop-loss, ROI or sell-signal.
:param low: Only used during backtesting to simulate stoploss
:param high: Only used during backtesting, to simulate ROI
:param force_stoploss: Externally provided stoploss
:return: True if trade should be sold, False otherwise
"""
# Set current rate to low for backtesting sell
current_rate = low or rate
current_profit = trade.calc_profit_percent(current_rate)
trade.adjust_min_max_rates(high or current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate,
trade=trade,
current_time=date,
current_profit=current_profit,
force_stoploss=force_stoploss,
high=high)
if stoplossflag.sell_flag:
logger.debug(f"{trade.pair} - Stoploss hit. sell_flag=True, "
f"sell_type={stoplossflag.sell_type}")
return stoplossflag
# Set current rate to high for backtesting sell
current_rate = high or rate
current_profit = trade.calc_profit_percent(current_rate)
experimental = self.config.get('experimental', {})
if buy and experimental.get('ignore_roi_if_buy_signal', False):
# This one is noisy, commented out
# logger.debug(f"{trade.pair} - Buy signal still active. sell_flag=False")
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
# Check if minimal roi has been reached and no longer in buy conditions (avoiding a fee)
if self.min_roi_reached(trade=trade,
current_profit=current_profit,
current_time=date):
logger.debug(
f"{trade.pair} - Required profit reached. sell_flag=True, "
f"sell_type=SellType.ROI")
return SellCheckTuple(sell_flag=True, sell_type=SellType.ROI)
if experimental.get('sell_profit_only', False):
# This one is noisy, commented out
# logger.debug(f"{trade.pair} - Checking if trade is profitable...")
if trade.calc_profit(rate=rate) <= 0:
# This one is noisy, commented out
# logger.debug(f"{trade.pair} - Trade is not profitable. sell_flag=False")
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
if sell and not buy and experimental.get('use_sell_signal', False):
logger.debug(
f"{trade.pair} - Sell signal received. sell_flag=True, "
f"sell_type=SellType.SELL_SIGNAL")
return SellCheckTuple(sell_flag=True,
sell_type=SellType.SELL_SIGNAL)
# This one is noisy, commented out...
# logger.debug(f"{trade.pair} - No sell signal. sell_flag=False")
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
def test_api_forcebuy(botclient, mocker, fee):
ftbot, client = botclient
rc = client_post(client, f"{BASE_URI}/forcebuy",
data='{"pair": "ETH/BTC"}')
assert_response(rc, 502)
assert rc.json == {"error": "Error querying _forcebuy: Forcebuy not enabled."}
# enable forcebuy
ftbot.config["forcebuy_enable"] = True
fbuy_mock = MagicMock(return_value=None)
mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
rc = client_post(client, f"{BASE_URI}/forcebuy",
data='{"pair": "ETH/BTC"}')
assert_response(rc)
assert rc.json == {"status": "Error buying pair ETH/BTC."}
# Test creating trae
fbuy_mock = MagicMock(return_value=Trade(
pair='ETH/ETH',
amount=1,
exchange='bittrex',
stake_amount=1,
open_rate=0.245441,
open_order_id="123456",
open_date=datetime.utcnow(),
is_open=False,
fee_close=fee.return_value,
fee_open=fee.return_value,
close_rate=0.265441,
))
mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
rc = client_post(client, f"{BASE_URI}/forcebuy",
data='{"pair": "ETH/BTC"}')
assert_response(rc)
assert rc.json == {'amount': 1,
'trade_id': None,
'close_date': None,
'close_date_hum': None,
'close_timestamp': None,
'close_rate': 0.265441,
'open_date': ANY,
'open_date_hum': 'just now',
'open_timestamp': ANY,
'open_rate': 0.245441,
'pair': 'ETH/ETH',
'stake_amount': 1,
'stop_loss': None,
'stop_loss_abs': None,
'stop_loss_pct': None,
'stop_loss_ratio': None,
'stoploss_order_id': None,
'stoploss_last_update': None,
'stoploss_last_update_timestamp': None,
'initial_stop_loss': None,
'initial_stop_loss_abs': None,
'initial_stop_loss_pct': None,
'initial_stop_loss_ratio': None,
'close_profit': None,
'close_profit_abs': None,
'close_rate_requested': None,
'fee_close': 0.0025,
'fee_close_cost': None,
'fee_close_currency': None,
'fee_open': 0.0025,
'fee_open_cost': None,
'fee_open_currency': None,
'is_open': False,
'max_rate': None,
'min_rate': None,
'open_order_id': '123456',
'open_rate_requested': None,
'open_trade_price': 0.2460546025,
'sell_reason': None,
'sell_order_status': None,
'strategy': None,
'ticker_interval': None,
'timeframe': None,
'exchange': 'bittrex',
}
def handle_stoploss_on_exchange(self, trade: Trade) -> bool:
"""
Check if trade is fulfilled in which case the stoploss
on exchange should be added immediately if stoploss on exchange
is enabled.
"""
logger.debug('Handling stoploss on exchange %s ...', trade)
stoploss_order = None
try:
# First we check if there is already a stoploss on exchange
stoploss_order = self.exchange.get_order(trade.stoploss_order_id, trade.pair) \
if trade.stoploss_order_id else None
except InvalidOrderException as exception:
logger.warning('Unable to fetch stoploss order: %s', exception)
# If trade open order id does not exist: buy order is fulfilled
buy_order_fulfilled = not trade.open_order_id
# Limit price threshold: As limit price should always be below price
limit_price_pct = 0.99
# If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
if (buy_order_fulfilled and not stoploss_order):
if self.edge:
stoploss = self.edge.stoploss(pair=trade.pair)
else:
stoploss = self.strategy.stoploss
stop_price = trade.open_rate * (1 + stoploss)
# limit price should be less than stop price.
limit_price = stop_price * limit_price_pct
try:
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair,
amount=trade.amount,
stop_price=stop_price,
rate=limit_price)['id']
trade.stoploss_order_id = str(stoploss_order_id)
trade.stoploss_last_update = datetime.now()
return False
except DependencyException as exception:
logger.warning(
'Unable to place a stoploss order on exchange: %s',
exception)
# If stoploss order is canceled for some reason we add it
if stoploss_order and stoploss_order['status'] == 'canceled':
try:
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair,
amount=trade.amount,
stop_price=trade.stop_loss,
rate=trade.stop_loss * limit_price_pct)['id']
trade.stoploss_order_id = str(stoploss_order_id)
return False
except DependencyException as exception:
logger.warning(
'Stoploss order was cancelled, '
'but unable to recreate one: %s', exception)
# We check if stoploss order is fulfilled
if stoploss_order and stoploss_order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(stoploss_order)
self._notify_sell(trade)
return True
# Finally we check if stoploss on exchange should be moved up because of trailing.
if stoploss_order and self.config.get('trailing_stop', False):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
self.handle_trailing_stoploss_on_exchange(trade, stoploss_order)
return False
def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
get_fee=fee,
)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
patch_get_signal(freqtradebot)
rpc = RPC(freqtradebot)
freqtradebot.state = State.RUNNING
with pytest.raises(RPCException, match=r'.*no active trade*'):
rpc._rpc_trade_status()
freqtradebot.enter_positions()
trades = Trade.get_open_trades()
trades[0].open_order_id = None
freqtradebot.exit_positions(trades)
results = rpc._rpc_trade_status()
assert results[0] == {
'trade_id': 1,
'pair': 'ETH/BTC',
'base_currency': 'BTC',
'open_date': ANY,
'open_timestamp': ANY,
'is_open': ANY,
'fee_open': ANY,
'fee_open_cost': ANY,
'fee_open_currency': ANY,
'fee_close': fee.return_value,
'fee_close_cost': ANY,
'fee_close_currency': ANY,
'open_rate_requested': ANY,
'open_trade_value': 0.0010025,
'close_rate_requested': ANY,
'sell_reason': ANY,
'sell_order_status': ANY,
'min_rate': ANY,
'max_rate': ANY,
'strategy': ANY,
'buy_tag': ANY,
'timeframe': 5,
'open_order_id': ANY,
'close_date': None,
'close_timestamp': None,
'open_rate': 1.098e-05,
'close_rate': None,
'current_rate': 1.099e-05,
'amount': 91.07468123,
'amount_requested': 91.07468123,
'stake_amount': 0.001,
'trade_duration': None,
'trade_duration_s': None,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'current_profit': -0.00408133,
'current_profit_pct': -0.41,
'current_profit_abs': -4.09e-06,
'profit_ratio': -0.00408133,
'profit_pct': -0.41,
'profit_abs': -4.09e-06,
'profit_fiat': ANY,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
'stoploss_current_dist': -1.1080000000000002e-06,
'stoploss_current_dist_ratio': -0.10081893,
'stoploss_current_dist_pct': -10.08,
'stoploss_entry_dist': -0.00010475,
'stoploss_entry_dist_ratio': -0.10448878,
'open_order': None,
'exchange': 'binance',
}
mocker.patch(
'freqtrade.exchange.Exchange.get_rate',
MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
results = rpc._rpc_trade_status()
assert isnan(results[0]['current_profit'])
assert isnan(results[0]['current_rate'])
assert results[0] == {
'trade_id': 1,
'pair': 'ETH/BTC',
'base_currency': 'BTC',
'open_date': ANY,
'open_timestamp': ANY,
'is_open': ANY,
'fee_open': ANY,
'fee_open_cost': ANY,
'fee_open_currency': ANY,
'fee_close': fee.return_value,
'fee_close_cost': ANY,
'fee_close_currency': ANY,
'open_rate_requested': ANY,
'open_trade_value': ANY,
'close_rate_requested': ANY,
'sell_reason': ANY,
'sell_order_status': ANY,
'min_rate': ANY,
'max_rate': ANY,
'strategy': ANY,
'buy_tag': ANY,
'timeframe': ANY,
'open_order_id': ANY,
'close_date': None,
'close_timestamp': None,
'open_rate': 1.098e-05,
'close_rate': None,
'current_rate': ANY,
'amount': 91.07468123,
'amount_requested': 91.07468123,
'trade_duration': ANY,
'trade_duration_s': ANY,
'stake_amount': 0.001,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'current_profit': ANY,
'current_profit_pct': ANY,
'current_profit_abs': ANY,
'profit_ratio': ANY,
'profit_pct': ANY,
'profit_abs': ANY,
'profit_fiat': ANY,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
'stoploss_current_dist': ANY,
'stoploss_current_dist_ratio': ANY,
'stoploss_current_dist_pct': ANY,
'stoploss_entry_dist': -0.00010475,
'stoploss_entry_dist_ratio': -0.10448878,
'open_order': None,
'exchange': 'binance',
}
def test_get_open(fee):
create_mock_trades(fee)
assert len(Trade.get_open_trades()) == 4
def _rpc_trade_statistics(self, stake_currency: str,
fiat_display_currency: str) -> Dict[str, Any]:
""" Returns cumulative profit statistics """
trades = Trade.get_trades().order_by(Trade.id).all()
profit_all_coin = []
profit_all_ratio = []
profit_closed_coin = []
profit_closed_ratio = []
durations = []
for trade in trades:
current_rate: float = 0.0
if not trade.open_rate:
continue
if trade.close_date:
durations.append(
(trade.close_date - trade.open_date).total_seconds())
if not trade.is_open:
profit_ratio = trade.close_profit
profit_closed_coin.append(trade.close_profit_abs)
profit_closed_ratio.append(profit_ratio)
else:
# Get current rate
try:
current_rate = self._freqtrade.get_sell_rate(
trade.pair, False)
except DependencyException:
current_rate = NAN
profit_ratio = trade.calc_profit_ratio(rate=current_rate)
profit_all_coin.append(
trade.calc_profit(rate=trade.close_rate or current_rate))
profit_all_ratio.append(profit_ratio)
best_pair = Trade.get_best_pair()
if not best_pair:
raise RPCException('no closed trade')
bp_pair, bp_rate = best_pair
# Prepare data to display
profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
profit_closed_percent = (round(mean(profit_closed_ratio) *
100, 2) if profit_closed_ratio else 0.0)
profit_closed_fiat = self._fiat_converter.convert_amount(
profit_closed_coin_sum, stake_currency,
fiat_display_currency) if self._fiat_converter else 0
profit_all_coin_sum = round(sum(profit_all_coin), 8)
profit_all_percent = round(mean(profit_all_ratio) *
100, 2) if profit_all_ratio else 0.0
profit_all_fiat = self._fiat_converter.convert_amount(
profit_all_coin_sum, stake_currency,
fiat_display_currency) if self._fiat_converter else 0
num = float(len(durations) or 1)
return {
'profit_closed_coin':
profit_closed_coin_sum,
'profit_closed_percent':
profit_closed_percent,
'profit_closed_fiat':
profit_closed_fiat,
'profit_all_coin':
profit_all_coin_sum,
'profit_all_percent':
profit_all_percent,
'profit_all_fiat':
profit_all_fiat,
'trade_count':
len(trades),
'first_trade_date':
arrow.get(trades[0].open_date).humanize(),
'latest_trade_date':
arrow.get(trades[-1].open_date).humanize(),
'avg_duration':
str(timedelta(seconds=sum(durations) / num)).split('.')[0],
'best_pair':
bp_pair,
'best_rate':
round(bp_rate * 100, 2),
}
def test_api_status(botclient, mocker, ticker, fee, markets):
ftbot, client = botclient
patch_get_signal(ftbot, (True, False))
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_balances=MagicMock(return_value=ticker),
fetch_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
rc = client_get(client, f"{BASE_URI}/status")
assert_response(rc, 200)
assert rc.json == []
ftbot.enter_positions()
trades = Trade.get_open_trades()
trades[0].open_order_id = None
ftbot.exit_positions(trades)
rc = client_get(client, f"{BASE_URI}/status")
assert_response(rc)
assert len(rc.json) == 1
assert rc.json == [{'amount': 91.07468124,
'base_currency': 'BTC',
'close_date': None,
'close_date_hum': None,
'close_timestamp': None,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'close_rate': None,
'current_profit': -0.00408133,
'current_profit_pct': -0.41,
'current_profit_abs': -4.09e-06,
'current_rate': 1.099e-05,
'open_date': ANY,
'open_date_hum': 'just now',
'open_timestamp': ANY,
'open_order': None,
'open_rate': 1.098e-05,
'pair': 'ETH/BTC',
'stake_amount': 0.001,
'stop_loss': 9.882e-06,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss': 9.882e-06,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
'stoploss_current_dist': -1.1080000000000002e-06,
'stoploss_current_dist_ratio': -0.10081893,
'stoploss_entry_dist': -0.00010475,
'stoploss_entry_dist_ratio': -0.10448878,
'trade_id': 1,
'close_rate_requested': None,
'current_rate': 1.099e-05,
'fee_close': 0.0025,
'fee_close_cost': None,
'fee_close_currency': None,
'fee_open': 0.0025,
'fee_open_cost': None,
'fee_open_currency': None,
'open_date': ANY,
'is_open': True,
'max_rate': 1.099e-05,
'min_rate': 1.098e-05,
'open_order_id': None,
'open_rate_requested': 1.098e-05,
'open_trade_price': 0.0010025,
'sell_reason': None,
'sell_order_status': None,
'strategy': 'DefaultStrategy',
'ticker_interval': 5,
'timeframe': 5,
'exchange': 'bittrex',
}]
def test_to_json(default_conf, fee):
# Simulate dry_run entries
trade = Trade(pair='ETH/BTC',
stake_amount=0.001,
amount=123.0,
amount_requested=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_date=arrow.utcnow().shift(hours=-2).datetime,
open_rate=0.123,
exchange='bittrex',
open_order_id='dry_run_buy_12345')
result = trade.to_json()
assert isinstance(result, dict)
assert result == {
'trade_id': None,
'pair': 'ETH/BTC',
'is_open': None,
'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
'open_timestamp': int(trade.open_date.timestamp() * 1000),
'open_order_id': 'dry_run_buy_12345',
'close_date': None,
'close_timestamp': None,
'open_rate': 0.123,
'open_rate_requested': None,
'open_trade_value': 15.1668225,
'fee_close': 0.0025,
'fee_close_cost': None,
'fee_close_currency': None,
'fee_open': 0.0025,
'fee_open_cost': None,
'fee_open_currency': None,
'close_rate': None,
'close_rate_requested': None,
'amount': 123.0,
'amount_requested': 123.0,
'stake_amount': 0.001,
'trade_duration': None,
'trade_duration_s': None,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'profit_ratio': None,
'profit_pct': None,
'profit_abs': None,
'sell_reason': None,
'sell_order_status': None,
'stop_loss_abs': None,
'stop_loss_ratio': None,
'stop_loss_pct': None,
'stoploss_order_id': None,
'stoploss_last_update': None,
'stoploss_last_update_timestamp': None,
'initial_stop_loss_abs': None,
'initial_stop_loss_pct': None,
'initial_stop_loss_ratio': None,
'min_rate': None,
'max_rate': None,
'strategy': None,
'timeframe': None,
'exchange': 'bittrex',
}
# Simulate dry_run entries
trade = Trade(
pair='XRP/BTC',
stake_amount=0.001,
amount=100.0,
amount_requested=101.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_date=arrow.utcnow().shift(hours=-2).datetime,
close_date=arrow.utcnow().shift(hours=-1).datetime,
open_rate=0.123,
close_rate=0.125,
exchange='bittrex',
)
result = trade.to_json()
assert isinstance(result, dict)
assert result == {
'trade_id': None,
'pair': 'XRP/BTC',
'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
'open_timestamp': int(trade.open_date.timestamp() * 1000),
'close_date': trade.close_date.strftime("%Y-%m-%d %H:%M:%S"),
'close_timestamp': int(trade.close_date.timestamp() * 1000),
'open_rate': 0.123,
'close_rate': 0.125,
'amount': 100.0,
'amount_requested': 101.0,
'stake_amount': 0.001,
'trade_duration': 60,
'trade_duration_s': 3600,
'stop_loss_abs': None,
'stop_loss_pct': None,
'stop_loss_ratio': None,
'stoploss_order_id': None,
'stoploss_last_update': None,
'stoploss_last_update_timestamp': None,
'initial_stop_loss_abs': None,
'initial_stop_loss_pct': None,
'initial_stop_loss_ratio': None,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'profit_ratio': None,
'profit_pct': None,
'profit_abs': None,
'close_rate_requested': None,
'fee_close': 0.0025,
'fee_close_cost': None,
'fee_close_currency': None,
'fee_open': 0.0025,
'fee_open_cost': None,
'fee_open_currency': None,
'is_open': None,
'max_rate': None,
'min_rate': None,
'open_order_id': None,
'open_rate_requested': None,
'open_trade_value': 12.33075,
'sell_reason': None,
'sell_order_status': None,
'strategy': None,
'timeframe': None,
'exchange': 'bittrex',
}
def populate_trades(self, pair: str) -> dict:
# Initialize the trades dict if it doesn't exist, persist it otherwise
if not pair in self.custom_trade_info:
self.custom_trade_info[pair] = {}
# init the temp dicts and set the trade stuff to false
trade_data = {}
trade_data['active_trade'] = trade_data['other_trades'] = trade_data[
'biggest_loser'] = False
self.custom_trade_info['meta'] = {}
# active trade stuff only works in live and dry, not backtest
if self.config['runmode'].value in ('live', 'dry_run'):
# find out if we have an open trade for this pair
active_trade = Trade.get_trades([
Trade.pair == pair,
Trade.is_open.is_(True),
]).all()
# if so, get some information
if active_trade:
# get current price and update the min/max rate
current_rate = self.get_current_price(pair, True)
active_trade[0].adjust_min_max_rates(current_rate)
# get how long the trade has been open in minutes and candles
present = arrow.utcnow()
trade_start = arrow.get(active_trade[0].open_date)
open_minutes = (present -
trade_start).total_seconds() // 60 # floor
# set up the things we use in the strategy
trade_data['active_trade'] = True
trade_data['current_profit'] = active_trade[
0].calc_profit_ratio(current_rate)
trade_data['peak_profit'] = max(
0, active_trade[0].calc_profit_ratio(
active_trade[0].max_rate))
trade_data['open_minutes']: int = open_minutes
trade_data['open_candles']: int = (
open_minutes // active_trade[0].timeframe) # floor
else:
trade_data['current_profit'] = trade_data['peak_profit'] = 0.0
trade_data['open_minutes'] = trade_data['open_candles'] = 0
# if there are open trades not including the current pair, get some information
# future reference, for *all* open trades: open_trades = Trade.get_open_trades()
other_trades = Trade.get_trades([
Trade.pair != pair,
Trade.is_open.is_(True),
]).all()
if other_trades:
trade_data['other_trades'] = True
other_profit = tuple(
trade.calc_profit_ratio(
self.get_current_price(trade.pair, False))
for trade in other_trades)
trade_data['avg_other_profit'] = mean(other_profit)
# find which of our trades is the biggest loser
if trade_data['current_profit'] < min(other_profit):
trade_data['biggest_loser'] = True
else:
trade_data['avg_other_profit'] = 0
# get the number of free trade slots, storing in every pairs dict due to laziness
open_trades = len(Trade.get_open_trades())
trade_data['free_slots'] = max(
0, self.config['max_open_trades'] - open_trades)
return trade_data
def test_stoploss_reinitialization(default_conf, fee):
init_db(default_conf['db_url'])
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
fee_open=fee.return_value,
open_date=arrow.utcnow().shift(hours=-2).datetime,
amount=10,
fee_close=fee.return_value,
exchange='bittrex',
open_rate=1,
max_rate=1,
)
trade.adjust_stop_loss(trade.open_rate, 0.05, True)
assert trade.stop_loss == 0.95
assert trade.stop_loss_pct == -0.05
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
Trade.query.session.add(trade)
# Lower stoploss
Trade.stoploss_reinitialization(0.06)
trades = Trade.get_open_trades()
assert len(trades) == 1
trade_adj = trades[0]
assert trade_adj.stop_loss == 0.94
assert trade_adj.stop_loss_pct == -0.06
assert trade_adj.initial_stop_loss == 0.94
assert trade_adj.initial_stop_loss_pct == -0.06
# Raise stoploss
Trade.stoploss_reinitialization(0.04)
trades = Trade.get_open_trades()
assert len(trades) == 1
trade_adj = trades[0]
assert trade_adj.stop_loss == 0.96
assert trade_adj.stop_loss_pct == -0.04
assert trade_adj.initial_stop_loss == 0.96
assert trade_adj.initial_stop_loss_pct == -0.04
# Trailing stoploss (move stoplos up a bit)
trade.adjust_stop_loss(1.02, 0.04)
assert trade_adj.stop_loss == 0.9792
assert trade_adj.initial_stop_loss == 0.96
Trade.stoploss_reinitialization(0.04)
trades = Trade.get_open_trades()
assert len(trades) == 1
trade_adj = trades[0]
# Stoploss should not change in this case.
assert trade_adj.stop_loss == 0.9792
assert trade_adj.stop_loss_pct == -0.04
assert trade_adj.initial_stop_loss == 0.96
assert trade_adj.initial_stop_loss_pct == -0.04
def backtest(stake_amount: float,
processed: Dict[str, DataFrame],
max_open_trades: int = 0,
realistic: bool = True,
sell_profit_only: bool = False,
stoploss: int = -1.00,
use_sell_signal: bool = False) -> DataFrame:
"""
Implements backtesting functionality
:param stake_amount: btc amount to use for each trade
:param processed: a processed dictionary with format {pair, data}
:param max_open_trades: maximum number of concurrent trades (default: 0, disabled)
:param realistic: do we try to simulate realistic trades? (default: True)
:return: DataFrame
"""
trades = []
trade_count_lock: dict = {}
exchange._API = Bittrex({'key': '', 'secret': ''})
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0
ticker = populate_sell_trend(populate_buy_trend(pair_data))
# for each buy point
lock_pair_until = None
buy_subset = ticker[ticker.buy == 1][[
'buy', 'open', 'close', 'date', 'sell'
]]
for row in buy_subset.itertuples(index=True):
if realistic:
if lock_pair_until is not None and row.Index <= lock_pair_until:
continue
if max_open_trades > 0:
# Check if max_open_trades has already been reached for the given date
if not trade_count_lock.get(row.date, 0) < max_open_trades:
continue
if max_open_trades > 0:
# Increase lock
trade_count_lock[row.date] = trade_count_lock.get(row.date,
0) + 1
trade = Trade(open_rate=row.close,
open_date=row.date,
stake_amount=stake_amount,
amount=stake_amount / row.open,
fee=exchange.get_fee())
# calculate win/lose forwards from buy point
sell_subset = ticker[row.Index + 1:][['close', 'date', 'sell']]
for row2 in sell_subset.itertuples(index=True):
if max_open_trades > 0:
# Increase trade_count_lock for every iteration
trade_count_lock[row2.date] = trade_count_lock.get(
row2.date, 0) + 1
current_profit_percent = trade.calc_profit_percent(
rate=row2.close)
if (sell_profit_only and current_profit_percent < 0):
continue
if min_roi_reached(trade, row2.close, row2.date) or \
(row2.sell == 1 and use_sell_signal) or \
current_profit_percent <= stoploss:
current_profit_btc = trade.calc_profit(rate=row2.close)
lock_pair_until = row2.Index
trades.append(
(pair, current_profit_percent, current_profit_btc,
row2.Index - row.Index, current_profit_btc > 0,
current_profit_btc < 0))
break
labels = [
'currency', 'profit_percent', 'profit_BTC', 'duration', 'profit',
'loss'
]
return DataFrame.from_records(trades, columns=labels)
def test_update_fee(fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
fee_open=fee.return_value,
open_date=arrow.utcnow().shift(hours=-2).datetime,
amount=10,
fee_close=fee.return_value,
exchange='bittrex',
open_rate=1,
max_rate=1,
)
fee_cost = 0.15
fee_currency = 'BTC'
fee_rate = 0.0075
assert trade.fee_open_currency is None
assert not trade.fee_updated('buy')
assert not trade.fee_updated('sell')
trade.update_fee(fee_cost, fee_currency, fee_rate, 'buy')
assert trade.fee_updated('buy')
assert not trade.fee_updated('sell')
assert trade.fee_open_currency == fee_currency
assert trade.fee_open_cost == fee_cost
assert trade.fee_open == fee_rate
# Setting buy rate should "guess" close rate
assert trade.fee_close == fee_rate
assert trade.fee_close_currency is None
assert trade.fee_close_cost is None
fee_rate = 0.0076
trade.update_fee(fee_cost, fee_currency, fee_rate, 'sell')
assert trade.fee_updated('buy')
assert trade.fee_updated('sell')
assert trade.fee_close == 0.0076
assert trade.fee_close_cost == fee_cost
assert trade.fee_close == fee_rate
def execute_buy(self,
pair: str,
stake_amount: float,
price: Optional[float] = None) -> bool:
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
:return: None
"""
pair_s = pair.replace('_', '/')
pair_url = self.exchange.get_pair_detail_url(pair)
stake_currency = self.config['stake_currency']
fiat_currency = self.config.get('fiat_display_currency', None)
time_in_force = self.strategy.order_time_in_force['buy']
if price:
buy_limit_requested = price
else:
# Calculate amount
buy_limit_requested = self.get_target_bid(
pair, self.exchange.get_ticker(pair))
min_stake_amount = self._get_min_pair_stake_amount(
pair_s, buy_limit_requested)
if min_stake_amount is not None and min_stake_amount > stake_amount:
logger.warning(
f'Can\'t open a new trade for {pair_s}: stake amount'
f' is too small ({stake_amount} < {min_stake_amount})')
return False
amount = stake_amount / buy_limit_requested
order = self.exchange.buy(pair=pair,
ordertype=self.strategy.order_types['buy'],
amount=amount,
rate=buy_limit_requested,
time_in_force=time_in_force)
order_id = order['id']
order_status = order.get('status', None)
# we assume the order is executed at the price requested
buy_limit_filled_price = buy_limit_requested
if order_status == 'expired' or order_status == 'rejected':
order_type = self.strategy.order_types['buy']
order_tif = self.strategy.order_time_in_force['buy']
# return false if the order is not filled
if float(order['filled']) == 0:
logger.warning(
'Buy %s order with time in force %s for %s is %s by %s.'
' zero amount is fulfilled.', order_tif, order_type,
pair_s, order_status, self.exchange.name)
return False
else:
# the order is partially fulfilled
# in case of IOC orders we can check immediately
# if the order is fulfilled fully or partially
logger.warning(
'Buy %s order with time in force %s for %s is %s by %s.'
' %s amount fulfilled out of %s (%s remaining which is canceled).',
order_tif, order_type, pair_s, order_status,
self.exchange.name, order['filled'], order['amount'],
order['remaining'])
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
order_id = None
# in case of FOK the order may be filled immediately and fully
elif order_status == 'closed':
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
order_id = None
self.rpc.send_msg({
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': self.exchange.name.capitalize(),
'pair': pair_s,
'market_url': pair_url,
'limit': buy_limit_filled_price,
'stake_amount': stake_amount,
'stake_currency': stake_currency,
'fiat_currency': fiat_currency
})
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
trade = Trade(pair=pair,
stake_amount=stake_amount,
amount=amount,
fee_open=fee,
fee_close=fee,
open_rate=buy_limit_filled_price,
open_rate_requested=buy_limit_requested,
open_date=datetime.utcnow(),
exchange=self.exchange.id,
open_order_id=order_id,
strategy=self.strategy.get_strategy_name(),
ticker_interval=constants.TICKER_INTERVAL_MINUTES[
self.config['ticker_interval']])
Trade.session.add(trade)
Trade.session.flush()
# Updating wallets
self.wallets.update()
return True
def handle_stoploss_on_exchange(self, trade: Trade) -> bool:
"""
Check if trade is fulfilled in which case the stoploss
on exchange should be added immediately if stoploss on exchange
is enabled.
"""
logger.debug('Handling stoploss on exchange %s ...', trade)
stoploss_order = None
try:
# First we check if there is already a stoploss on exchange
stoploss_order = self.exchange.get_order(trade.stoploss_order_id, trade.pair) \
if trade.stoploss_order_id else None
except InvalidOrderException as exception:
logger.warning('Unable to fetch stoploss order: %s', exception)
# If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
if (not trade.open_order_id and not stoploss_order):
stoploss = self.edge.stoploss(
pair=trade.pair) if self.edge else self.strategy.stoploss
stop_price = trade.open_rate * (1 + stoploss)
if self.create_stoploss_order(trade=trade,
stop_price=stop_price,
rate=stop_price):
trade.stoploss_last_update = datetime.now()
return False
# If stoploss order is canceled for some reason we add it
if stoploss_order and stoploss_order['status'] == 'canceled':
if self.create_stoploss_order(trade=trade,
stop_price=trade.stop_loss,
rate=trade.stop_loss):
return False
else:
trade.stoploss_order_id = None
logger.warning(
'Stoploss order was cancelled, but unable to recreate one.'
)
# We check if stoploss order is fulfilled
if stoploss_order and stoploss_order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(stoploss_order)
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(
trade.pair,
timeframe_to_next_date(self.config['ticker_interval']))
self._notify_sell(trade, "stoploss")
return True
# Finally we check if stoploss on exchange should be moved up because of trailing.
if stoploss_order and self.config.get('trailing_stop', False):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
self.handle_trailing_stoploss_on_exchange(trade, stoploss_order)
return False
