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Merge branch 'develop' of https://github.com/nicolaspapp/freqtrade into feat/relative-drawdown

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Nicolas Papp
2022-04-11 14:42:10 -03:00
parent 47a6ef4f00 baefda80d1
commit 178240aa6c
99 changed files with 1703 additions and 1148 deletions
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136
freqtrade/optimize/backtesting.py
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@@ -14,7 +14,7 @@ from pandas import DataFrame
from freqtrade import constants
from freqtrade.configuration import TimeRange, validate_config_consistency
from freqtrade.constants import DATETIME_PRINT_FORMAT
from freqtrade.constants import DATETIME_PRINT_FORMAT, LongShort
from freqtrade.data import history
from freqtrade.data.btanalysis import find_existing_backtest_stats, trade_list_to_dataframe
from freqtrade.data.converter import trim_dataframe, trim_dataframes
@@ -349,20 +349,20 @@ class Backtesting:
data[pair] = df_analyzed[headers].values.tolist() if not df_analyzed.empty else []
return data
def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
def _get_close_rate(self, row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
trade_dur: int) -> float:
"""
Get close rate for backtesting result
"""
# Special handling if high or low hit STOP_LOSS or ROI
if sell.exit_type in (ExitType.STOP_LOSS, ExitType.TRAILING_STOP_LOSS):
return self._get_close_rate_for_stoploss(sell_row, trade, sell, trade_dur)
return self._get_close_rate_for_stoploss(row, trade, sell, trade_dur)
elif sell.exit_type == (ExitType.ROI):
return self._get_close_rate_for_roi(sell_row, trade, sell, trade_dur)
return self._get_close_rate_for_roi(row, trade, sell, trade_dur)
else:
return sell_row[OPEN_IDX]
return row[OPEN_IDX]
def _get_close_rate_for_stoploss(self, sell_row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
def _get_close_rate_for_stoploss(self, row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
trade_dur: int) -> float:
# our stoploss was already lower than candle high,
# possibly due to a cancelled trade exit.
@@ -371,11 +371,11 @@ class Backtesting:
leverage = trade.leverage or 1.0
side_1 = -1 if is_short else 1
if is_short:
if trade.stop_loss < sell_row[LOW_IDX]:
return sell_row[OPEN_IDX]
if trade.stop_loss < row[LOW_IDX]:
return row[OPEN_IDX]
else:
if trade.stop_loss > sell_row[HIGH_IDX]:
return sell_row[OPEN_IDX]
if trade.stop_loss > row[HIGH_IDX]:
return row[OPEN_IDX]
# Special case: trailing triggers within same candle as trade opened. Assume most
# pessimistic price movement, which is moving just enough to arm stoploss and
@@ -388,29 +388,28 @@ class Backtesting:
and self.strategy.trailing_stop_positive
):
# Worst case: price reaches stop_positive_offset and dives down.
stop_rate = (sell_row[OPEN_IDX] *
stop_rate = (row[OPEN_IDX] *
(1 + side_1 * abs(self.strategy.trailing_stop_positive_offset) -
side_1 * abs(self.strategy.trailing_stop_positive / leverage)))
else:
# Worst case: price ticks tiny bit above open and dives down.
stop_rate = sell_row[OPEN_IDX] * (1 -
side_1 * abs(trade.stop_loss_pct / leverage))
stop_rate = row[OPEN_IDX] * (1 - side_1 * abs(trade.stop_loss_pct / leverage))
if is_short:
assert stop_rate > sell_row[LOW_IDX]
assert stop_rate > row[LOW_IDX]
else:
assert stop_rate < sell_row[HIGH_IDX]
assert stop_rate < row[HIGH_IDX]
# Limit lower-end to candle low to avoid sells below the low.
# This still remains "worst case" - but "worst realistic case".
if is_short:
return min(sell_row[HIGH_IDX], stop_rate)
return min(row[HIGH_IDX], stop_rate)
else:
return max(sell_row[LOW_IDX], stop_rate)
return max(row[LOW_IDX], stop_rate)
# Set close_rate to stoploss
return trade.stop_loss
def _get_close_rate_for_roi(self, sell_row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
def _get_close_rate_for_roi(self, row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
trade_dur: int) -> float:
is_short = trade.is_short or False
leverage = trade.leverage or 1.0
@@ -418,41 +417,41 @@ class Backtesting:
roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
if roi is not None and roi_entry is not None:
if roi == -1 and roi_entry % self.timeframe_min == 0:
# When forceselling with ROI=-1, the roi time will always be equal to trade_dur.
# When force_exiting with ROI=-1, the roi time will always be equal to trade_dur.
# If that entry is a multiple of the timeframe (so on candle open)
# - we'll use open instead of close
return sell_row[OPEN_IDX]
return row[OPEN_IDX]
# - (Expected abs profit - open_rate - open_fee) / (fee_close -1)
roi_rate = trade.open_rate * roi / leverage
open_fee_rate = side_1 * trade.open_rate * (1 + side_1 * trade.fee_open)
close_rate = -(roi_rate + open_fee_rate) / (trade.fee_close - side_1 * 1)
if is_short:
is_new_roi = sell_row[OPEN_IDX] < close_rate
is_new_roi = row[OPEN_IDX] < close_rate
else:
is_new_roi = sell_row[OPEN_IDX] > close_rate
is_new_roi = row[OPEN_IDX] > close_rate
if (trade_dur > 0 and trade_dur == roi_entry
and roi_entry % self.timeframe_min == 0
and is_new_roi):
# new ROI entry came into effect.
# use Open rate if open_rate > calculated sell rate
return sell_row[OPEN_IDX]
return row[OPEN_IDX]
if (trade_dur == 0 and (
(
is_short
# Red candle (for longs)
and sell_row[OPEN_IDX] < sell_row[CLOSE_IDX] # Red candle
and trade.open_rate > sell_row[OPEN_IDX] # trade-open above open_rate
and close_rate < sell_row[CLOSE_IDX] # closes below close
and row[OPEN_IDX] < row[CLOSE_IDX] # Red candle
and trade.open_rate > row[OPEN_IDX] # trade-open above open_rate
and close_rate < row[CLOSE_IDX] # closes below close
)
or
(
not is_short
# green candle (for shorts)
and sell_row[OPEN_IDX] > sell_row[CLOSE_IDX] # green candle
and trade.open_rate < sell_row[OPEN_IDX] # trade-open below open_rate
and close_rate > sell_row[CLOSE_IDX] # closes above close
and row[OPEN_IDX] > row[CLOSE_IDX] # green candle
and trade.open_rate < row[OPEN_IDX] # trade-open below open_rate
and close_rate > row[CLOSE_IDX] # closes above close
)
)):
# ROI on opening candles with custom pricing can only
@@ -464,11 +463,11 @@ class Backtesting:
# Use the maximum between close_rate and low as we
# cannot sell outside of a candle.
# Applies when a new ROI setting comes in place and the whole candle is above that.
return min(max(close_rate, sell_row[LOW_IDX]), sell_row[HIGH_IDX])
return min(max(close_rate, row[LOW_IDX]), row[HIGH_IDX])
else:
# This should not be reached...
return sell_row[OPEN_IDX]
return row[OPEN_IDX]
def _get_adjust_trade_entry_for_candle(self, trade: LocalTrade, row: Tuple
) -> LocalTrade:
@@ -498,7 +497,7 @@ class Backtesting:
return row[LOW_IDX] <= rate <= row[HIGH_IDX]
def _get_sell_trade_entry_for_candle(self, trade: LocalTrade,
sell_row: Tuple) -> Optional[LocalTrade]:
row: Tuple) -> Optional[LocalTrade]:
# Check if we need to adjust our current positions
if self.strategy.position_adjustment_enable:
@@ -507,15 +506,15 @@ class Backtesting:
entry_count = trade.nr_of_successful_entries
check_adjust_entry = (entry_count <= self.strategy.max_entry_position_adjustment)
if check_adjust_entry:
trade = self._get_adjust_trade_entry_for_candle(trade, sell_row)
trade = self._get_adjust_trade_entry_for_candle(trade, row)
sell_candle_time: datetime = sell_row[DATE_IDX].to_pydatetime()
enter = sell_row[SHORT_IDX] if trade.is_short else sell_row[LONG_IDX]
exit_ = sell_row[ESHORT_IDX] if trade.is_short else sell_row[ELONG_IDX]
sell_candle_time: datetime = row[DATE_IDX].to_pydatetime()
enter = row[SHORT_IDX] if trade.is_short else row[LONG_IDX]
exit_ = row[ESHORT_IDX] if trade.is_short else row[ELONG_IDX]
sell = self.strategy.should_exit(
trade, sell_row[OPEN_IDX], sell_candle_time, # type: ignore
trade, row[OPEN_IDX], sell_candle_time, # type: ignore
enter=enter, exit_=exit_,
low=sell_row[LOW_IDX], high=sell_row[HIGH_IDX]
low=row[LOW_IDX], high=row[HIGH_IDX]
)
if sell.exit_flag:
@@ -523,13 +522,13 @@ class Backtesting:
trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
try:
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
closerate = self._get_close_rate(row, trade, sell, trade_dur)
except ValueError:
return None
# call the custom exit price,with default value as previous closerate
current_profit = trade.calc_profit_ratio(closerate)
order_type = self.strategy.order_types['exit']
if sell.exit_type in (ExitType.SELL_SIGNAL, ExitType.CUSTOM_SELL):
if sell.exit_type in (ExitType.EXIT_SIGNAL, ExitType.CUSTOM_EXIT):
# Custom exit pricing only for sell-signals
if order_type == 'limit':
closerate = strategy_safe_wrapper(self.strategy.custom_exit_price,
@@ -540,9 +539,9 @@ class Backtesting:
# We can't place orders lower than current low.
# freqtrade does not support this in live, and the order would fill immediately
if trade.is_short:
closerate = min(closerate, sell_row[HIGH_IDX])
closerate = min(closerate, row[HIGH_IDX])
else:
closerate = max(closerate, sell_row[LOW_IDX])
closerate = max(closerate, row[LOW_IDX])
# Confirm trade exit:
time_in_force = self.strategy.order_time_in_force['exit']
@@ -558,13 +557,13 @@ class Backtesting:
trade.exit_reason = sell.exit_reason
# Checks and adds an exit tag, after checking that the length of the
# sell_row has the length for an exit tag column
# row has the length for an exit tag column
if(
len(sell_row) > EXIT_TAG_IDX
and sell_row[EXIT_TAG_IDX] is not None
and len(sell_row[EXIT_TAG_IDX]) > 0
len(row) > EXIT_TAG_IDX
and row[EXIT_TAG_IDX] is not None
and len(row[EXIT_TAG_IDX]) > 0
):
trade.exit_reason = sell_row[EXIT_TAG_IDX]
trade.exit_reason = row[EXIT_TAG_IDX]
self.order_id_counter += 1
order = Order(
@@ -592,8 +591,8 @@ class Backtesting:
return None
def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]:
sell_candle_time: datetime = sell_row[DATE_IDX].to_pydatetime()
def _get_sell_trade_entry(self, trade: LocalTrade, row: Tuple) -> Optional[LocalTrade]:
sell_candle_time: datetime = row[DATE_IDX].to_pydatetime()
if self.trading_mode == TradingMode.FUTURES:
trade.funding_fees = self.exchange.calculate_funding_fees(
@@ -614,13 +613,13 @@ class Backtesting:
].copy()
if len(detail_data) == 0:
# Fall back to "regular" data if no detail data was found for this candle
return self._get_sell_trade_entry_for_candle(trade, sell_row)
detail_data.loc[:, 'enter_long'] = sell_row[LONG_IDX]
detail_data.loc[:, 'exit_long'] = sell_row[ELONG_IDX]
detail_data.loc[:, 'enter_short'] = sell_row[SHORT_IDX]
detail_data.loc[:, 'exit_short'] = sell_row[ESHORT_IDX]
detail_data.loc[:, 'enter_tag'] = sell_row[ENTER_TAG_IDX]
detail_data.loc[:, 'exit_tag'] = sell_row[EXIT_TAG_IDX]
return self._get_sell_trade_entry_for_candle(trade, row)
detail_data.loc[:, 'enter_long'] = row[LONG_IDX]
detail_data.loc[:, 'exit_long'] = row[ELONG_IDX]
detail_data.loc[:, 'enter_short'] = row[SHORT_IDX]
detail_data.loc[:, 'exit_short'] = row[ESHORT_IDX]
detail_data.loc[:, 'enter_tag'] = row[ENTER_TAG_IDX]
detail_data.loc[:, 'exit_tag'] = row[EXIT_TAG_IDX]
headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
for det_row in detail_data[headers].values.tolist():
@@ -631,11 +630,11 @@ class Backtesting:
return None
else:
return self._get_sell_trade_entry_for_candle(trade, sell_row)
return self._get_sell_trade_entry_for_candle(trade, row)
def get_valid_price_and_stake(
self, pair: str, row: Tuple, propose_rate: float, stake_amount: Optional[float],
direction: str, current_time: datetime, entry_tag: Optional[str],
direction: LongShort, current_time: datetime, entry_tag: Optional[str],
trade: Optional[LocalTrade], order_type: str
) -> Tuple[float, float, float, float]:
@@ -643,7 +642,9 @@ class Backtesting:
propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=propose_rate)(
pair=pair, current_time=current_time,
proposed_rate=propose_rate, entry_tag=entry_tag) # default value is the open rate
proposed_rate=propose_rate, entry_tag=entry_tag,
side=direction,
) # default value is the open rate
# We can't place orders higher than current high (otherwise it'd be a stop limit buy)
# which freqtrade does not support in live.
if direction == "short":
@@ -694,7 +695,7 @@ class Backtesting:
return propose_rate, stake_amount_val, leverage, min_stake_amount
def _enter_trade(self, pair: str, row: Tuple, direction: str,
def _enter_trade(self, pair: str, row: Tuple, direction: LongShort,
stake_amount: Optional[float] = None,
trade: Optional[LocalTrade] = None) -> Optional[LocalTrade]:
@@ -725,6 +726,7 @@ class Backtesting:
if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
self.order_id_counter += 1
base_currency = self.exchange.get_pair_base_currency(pair)
amount = round((stake_amount / propose_rate) * leverage, 8)
is_short = (direction == 'short')
# Necessary for Margin trading. Disabled until support is enabled.
@@ -737,6 +739,8 @@ class Backtesting:
id=self.trade_id_counter,
open_order_id=self.order_id_counter,
pair=pair,
base_currency=base_currency,
stake_currency=self.config['stake_currency'],
open_rate=propose_rate,
open_rate_requested=propose_rate,
open_date=current_time,
@@ -772,8 +776,8 @@ class Backtesting:
ft_pair=trade.pair,
order_id=str(self.order_id_counter),
symbol=trade.pair,
ft_order_side=trade.enter_side,
side=trade.enter_side,
ft_order_side=trade.entry_side,
side=trade.entry_side,
order_type=order_type,
status="open",
order_date=current_time,
@@ -810,7 +814,7 @@ class Backtesting:
sell_row = data[pair][-1]
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
trade.exit_reason = ExitType.FORCE_SELL.value
trade.exit_reason = ExitType.FORCE_EXIT.value
trade.close(sell_row[OPEN_IDX], show_msg=False)
LocalTrade.close_bt_trade(trade)
# Deepcopy object to have wallets update correctly
@@ -827,7 +831,7 @@ class Backtesting:
self.rejected_trades += 1
return False
def check_for_trade_entry(self, row) -> Optional[str]:
def check_for_trade_entry(self, row) -> Optional[LongShort]:
enter_long = row[LONG_IDX] == 1
exit_long = row[ELONG_IDX] == 1
enter_short = self._can_short and row[SHORT_IDX] == 1
@@ -855,7 +859,7 @@ class Backtesting:
timedout = self.strategy.ft_check_timed_out(trade, order, current_time)
if timedout:
if order.side == trade.enter_side:
if order.side == trade.entry_side:
self.timedout_entry_orders += 1
if trade.nr_of_successful_entries == 0:
# Remove trade due to entry timeout expiration.
@@ -970,7 +974,7 @@ class Backtesting:
for trade in list(open_trades[pair]):
# 3. Process entry orders.
order = trade.select_order(trade.enter_side, is_open=True)
order = trade.select_order(trade.entry_side, is_open=True)
if order and self._get_order_filled(order.price, row):
order.close_bt_order(current_time)
trade.open_order_id = None

4
freqtrade/optimize/hyperopt.py
View File

@@ -114,8 +114,8 @@ class Hyperopt:
self.position_stacking = self.config.get('position_stacking', False)
if HyperoptTools.has_space(self.config, 'sell'):
# Make sure use_sell_signal is enabled
self.config['use_sell_signal'] = True
# Make sure use_exit_signal is enabled
self.config['use_exit_signal'] = True
self.print_all = self.config.get('print_all', False)
self.hyperopt_table_header = 0

10
freqtrade/optimize/hyperopt_tools.py
View File

@@ -390,8 +390,8 @@ class HyperoptTools():
lambda x: '{} {}'.format(
round_coin_value(x['Total profit'], stake_currency, keep_trailing_zeros=True),
f"({x['Profit']:,.2%})".rjust(10, ' ')
).rjust(25+len(stake_currency))
if x['Total profit'] != 0.0 else '--'.rjust(25+len(stake_currency)),
).rjust(25 + len(stake_currency))
if x['Total profit'] != 0.0 else '--'.rjust(25 + len(stake_currency)),
axis=1
)
trials = trials.drop(columns=['Total profit'])
@@ -399,11 +399,11 @@ class HyperoptTools():
if print_colorized:
for i in range(len(trials)):
if trials.loc[i]['is_profit']:
for j in range(len(trials.loc[i])-3):
for j in range(len(trials.loc[i]) - 3):
trials.iat[i, j] = "{}{}{}".format(Fore.GREEN,
str(trials.loc[i][j]), Fore.RESET)
if trials.loc[i]['is_best'] and highlight_best:
for j in range(len(trials.loc[i])-3):
for j in range(len(trials.loc[i]) - 3):
trials.iat[i, j] = "{}{}{}".format(Style.BRIGHT,
str(trials.loc[i][j]), Style.RESET_ALL)
@@ -459,7 +459,7 @@ class HyperoptTools():
'loss', 'is_initial_point', 'is_best']
perc_multi = 100
param_metrics = [("params_dict."+param) for param in results[0]['params_dict'].keys()]
param_metrics = [("params_dict." + param) for param in results[0]['params_dict'].keys()]
trials = trials[base_metrics + param_metrics]
base_columns = ['Best', 'Epoch', 'Trades', 'Avg profit', 'Median profit', 'Total profit',

8
freqtrade/optimize/optimize_reports.py
View File

@@ -460,10 +460,10 @@ def generate_strategy_stats(pairlist: List[str],
'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False),
'use_custom_stoploss': config.get('use_custom_stoploss', False),
'minimal_roi': config['minimal_roi'],
'use_sell_signal': config['use_sell_signal'],
'sell_profit_only': config['sell_profit_only'],
'sell_profit_offset': config['sell_profit_offset'],
'ignore_roi_if_buy_signal': config['ignore_roi_if_buy_signal'],
'use_exit_signal': config['use_exit_signal'],
'exit_profit_only': config['exit_profit_only'],
'exit_profit_offset': config['exit_profit_offset'],
'ignore_roi_if_entry_signal': config['ignore_roi_if_entry_signal'],
**daily_stats,
**trade_stats
}