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Merge branch 'develop' into feat/short

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This commit is contained in:
Matthias
2022-02-11 17:02:04 +01:00
parent 7237aa7edb 6a59103869
commit 0c6d92a7a6
63 changed files with 1158 additions and 349 deletions
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239
freqtrade/optimize/backtesting.py
View File

@@ -66,6 +66,8 @@ class Backtesting:
LoggingMixin.show_output = False
self.config = config
self.results: Dict[str, Any] = {}
self.trade_id_counter: int = 0
self.order_id_counter: int = 0
config['dry_run'] = True
self.run_ids: Dict[str, str] = {}
@@ -276,6 +278,8 @@ class Backtesting:
PairLocks.reset_locks()
Trade.reset_trades()
self.rejected_trades = 0
self.timedout_entry_orders = 0
self.timedout_exit_orders = 0
self.dataprovider.clear_cache()
if enable_protections:
self._load_protections(self.strategy)
@@ -322,6 +326,14 @@ class Backtesting:
# Trim startup period from analyzed dataframe
df_analyzed = processed[pair] = pair_data = trim_dataframe(
df_analyzed, self.timerange, startup_candles=self.required_startup)
# Update dataprovider cache
self.dataprovider._set_cached_df(
pair, self.timeframe, df_analyzed, self.config['candle_type_def'])
# Create a copy of the dataframe before shifting, that way the buy signal/tag
# remains on the correct candle for callbacks.
df_analyzed = df_analyzed.copy()
# To avoid using data from future, we use buy/sell signals shifted
# from the previous candle
for col in headers[5:]:
@@ -332,14 +344,6 @@ class Backtesting:
else:
df_analyzed.loc[:, col] = 0 if not tag_col else None
# Update dataprovider cache
self.dataprovider._set_cached_df(
pair,
self.timeframe,
df_analyzed,
self.config['candle_type_def']
)
df_analyzed = df_analyzed.drop(df_analyzed.head(1).index)
# Convert from Pandas to list for performance reasons
@@ -404,7 +408,10 @@ class Backtesting:
# use Open rate if open_rate > calculated sell rate
return sell_row[OPEN_IDX]
return close_rate
# 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])
else:
# This should not be reached...
@@ -430,10 +437,15 @@ class Backtesting:
pos_trade = self._enter_trade(
trade.pair, row, 'short' if trade.is_short else 'long', stake_amount, trade)
if pos_trade is not None:
self.wallets.update()
return pos_trade
return trade
def _get_order_filled(self, rate: float, row: Tuple) -> bool:
""" Rate is within candle, therefore filled"""
return row[LOW_IDX] <= rate <= row[HIGH_IDX]
def _get_sell_trade_entry_for_candle(self, trade: LocalTrade,
sell_row: Tuple) -> Optional[LocalTrade]:
@@ -462,18 +474,21 @@ class Backtesting:
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
# call the custom exit price,with default value as previous closerate
current_profit = trade.calc_profit_ratio(closerate)
order_type = self.strategy.order_types['sell']
if sell.sell_type in (SellType.SELL_SIGNAL, SellType.CUSTOM_SELL):
# Custom exit pricing only for sell-signals
closerate = strategy_safe_wrapper(self.strategy.custom_exit_price,
default_retval=closerate)(
pair=trade.pair, trade=trade,
current_time=sell_row[DATE_IDX],
proposed_rate=closerate, current_profit=current_profit)
# Use the maximum between close_rate and low as we cannot sell outside of a candle.
closerate = min(max(closerate, sell_row[LOW_IDX]), sell_row[HIGH_IDX])
if order_type == 'limit':
closerate = strategy_safe_wrapper(self.strategy.custom_exit_price,
default_retval=closerate)(
pair=trade.pair, trade=trade,
current_time=sell_candle_time,
proposed_rate=closerate, current_profit=current_profit)
# We can't place orders lower than current low.
# freqtrade does not support this in live, and the order would fill immediately
closerate = max(closerate, sell_row[LOW_IDX])
# Confirm trade exit:
time_in_force = self.strategy.order_time_in_force['sell']
if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
pair=trade.pair, trade=trade, order_type='limit', amount=trade.amount,
rate=closerate,
@@ -493,7 +508,28 @@ class Backtesting:
):
trade.sell_reason = sell_row[EXIT_TAG_IDX]
trade.close(closerate, show_msg=False)
self.order_id_counter += 1
order = Order(
id=self.order_id_counter,
ft_trade_id=trade.id,
order_date=sell_candle_time,
order_update_date=sell_candle_time,
ft_is_open=True,
ft_pair=trade.pair,
order_id=str(self.order_id_counter),
symbol=trade.pair,
ft_order_side="sell",
side="sell",
order_type=order_type,
status="open",
price=closerate,
average=closerate,
amount=trade.amount,
filled=0,
remaining=trade.amount,
cost=trade.amount * closerate,
)
trade.orders.append(order)
return trade
return None
@@ -547,13 +583,16 @@ class Backtesting:
current_time = row[DATE_IDX].to_pydatetime()
entry_tag = row[ENTER_TAG_IDX] if len(row) >= ENTER_TAG_IDX + 1 else None
# let's call the custom entry price, using the open price as default price
propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=row[OPEN_IDX])(
pair=pair, current_time=current_time,
proposed_rate=row[OPEN_IDX], entry_tag=entry_tag) # default value is the open rate
# Move rate to within the candle's low/high rate
propose_rate = min(max(propose_rate, row[LOW_IDX]), row[HIGH_IDX])
order_type = self.strategy.order_types['buy']
propose_rate = row[OPEN_IDX]
if order_type == 'limit':
propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=row[OPEN_IDX])(
pair=pair, current_time=current_time,
proposed_rate=propose_rate, entry_tag=entry_tag) # 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.
propose_rate = min(propose_rate, row[HIGH_IDX])
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, propose_rate, -0.05) or 0
max_stake_amount = self.exchange.get_max_pair_stake_amount(pair, propose_rate)
@@ -562,9 +601,9 @@ class Backtesting:
pos_adjust = trade is not None
if not pos_adjust:
try:
stake_amount = self.wallets.get_trade_stake_amount(pair, None)
stake_amount = self.wallets.get_trade_stake_amount(pair, None, update=False)
except DependencyException:
return trade
return None
stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
default_retval=stake_amount)(
@@ -598,7 +637,7 @@ class Backtesting:
leverage = min(max(leverage, 1.0), max_leverage)
order_type = self.strategy.order_types['buy']
time_in_force = self.strategy.order_time_in_force['sell']
time_in_force = self.strategy.order_time_in_force['buy']
# Confirm trade entry:
if not pos_adjust:
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
@@ -608,15 +647,21 @@ class Backtesting:
return None
if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
self.order_id_counter += 1
amount = round((stake_amount / propose_rate) * leverage, 8)
if trade is None:
# Enter trade
self.trade_id_counter += 1
trade = LocalTrade(
id=self.trade_id_counter,
open_order_id=self.order_id_counter,
pair=pair,
open_rate=propose_rate,
open_rate_requested=propose_rate,
open_date=current_time,
stake_amount=stake_amount,
amount=amount,
amount_requested=amount,
fee_open=self.fee,
fee_close=self.fee,
is_open=True,
@@ -627,28 +672,36 @@ class Backtesting:
leverage=leverage,
orders=[]
)
trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
order = Order(
ft_is_open=False,
id=self.order_id_counter,
ft_trade_id=trade.id,
ft_is_open=True,
ft_pair=trade.pair,
order_id=str(self.order_id_counter),
symbol=trade.pair,
ft_order_side="buy",
side="buy",
order_type="market",
status="closed",
order_type=order_type,
status="open",
order_date=current_time,
order_filled_date=current_time,
order_update_date=current_time,
price=propose_rate,
average=propose_rate,
amount=amount,
filled=amount,
cost=stake_amount + trade.fee_open
filled=0,
remaining=amount,
cost=stake_amount + trade.fee_open,
)
if pos_adjust and self._get_order_filled(order.price, row):
order.close_bt_order(current_time)
else:
trade.open_order_id = str(self.order_id_counter)
trade.orders.append(order)
if pos_adjust:
trade.recalc_trade_from_orders()
trade.recalc_trade_from_orders()
return trade
@@ -661,6 +714,9 @@ class Backtesting:
for pair in open_trades.keys():
if len(open_trades[pair]) > 0:
for trade in open_trades[pair]:
if trade.open_order_id and trade.nr_of_successful_buys == 0:
# Ignore trade if buy-order did not fill yet
continue
sell_row = data[pair][-1]
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
@@ -695,6 +751,51 @@ class Backtesting:
return 'short'
return None
def run_protections(self, enable_protections, pair: str, current_time: datetime):
if enable_protections:
self.protections.stop_per_pair(pair, current_time)
self.protections.global_stop(current_time)
def check_order_cancel(self, trade: LocalTrade, current_time) -> bool:
"""
Check if an order has been canceled.
Returns True if the trade should be Deleted (initial order was canceled).
"""
for order in [o for o in trade.orders if o.ft_is_open]:
timedout = self.strategy.ft_check_timed_out(order.side, trade, order, current_time)
if timedout:
if order.side == 'buy':
self.timedout_entry_orders += 1
if trade.nr_of_successful_buys == 0:
# Remove trade due to buy timeout expiration.
return True
else:
# Close additional buy order
del trade.orders[trade.orders.index(order)]
if order.side == 'sell':
self.timedout_exit_orders += 1
# Close sell order and retry selling on next signal.
del trade.orders[trade.orders.index(order)]
return False
def validate_row(
self, data: Dict, pair: str, row_index: int, current_time: datetime) -> Optional[Tuple]:
try:
# Row is treated as "current incomplete candle".
# Buy / sell signals are shifted by 1 to compensate for this.
row = data[pair][row_index]
except IndexError:
# missing Data for one pair at the end.
# Warnings for this are shown during data loading
return None
# Waits until the time-counter reaches the start of the data for this pair.
if row[DATE_IDX] > current_time:
return None
return row
def backtest(self, processed: Dict,
start_date: datetime, end_date: datetime,
max_open_trades: int = 0, position_stacking: bool = False,
@@ -717,14 +818,15 @@ class Backtesting:
"""
trades: List[LocalTrade] = []
self.prepare_backtest(enable_protections)
# Ensure wallets are uptodate (important for --strategy-list)
self.wallets.update()
# Use dict of lists with data for performance
# (looping lists is a lot faster than pandas DataFrames)
data: Dict = self._get_ohlcv_as_lists(processed)
# Indexes per pair, so some pairs are allowed to have a missing start.
indexes: Dict = defaultdict(int)
tmp = start_date + timedelta(minutes=self.timeframe_min)
current_time = start_date + timedelta(minutes=self.timeframe_min)
open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
open_trade_count = 0
@@ -733,28 +835,20 @@ class Backtesting:
(end_date - start_date) / timedelta(minutes=self.timeframe_min)))
# Loop timerange and get candle for each pair at that point in time
while tmp <= end_date:
while current_time <= end_date:
open_trade_count_start = open_trade_count
self.check_abort()
for i, pair in enumerate(data):
row_index = indexes[pair]
try:
# Row is treated as "current incomplete candle".
# Buy / sell signals are shifted by 1 to compensate for this.
row = data[pair][row_index]
except IndexError:
# missing Data for one pair at the end.
# Warnings for this are shown during data loading
continue
# Waits until the time-counter reaches the start of the data for this pair.
if row[DATE_IDX] > tmp:
row = self.validate_row(data, pair, row_index, current_time)
if not row:
continue
row_index += 1
indexes[pair] = row_index
self.dataprovider._set_dataframe_max_index(row_index)
# 1. Process buys.
# without positionstacking, we can only have one open trade per pair.
# max_open_trades must be respected
# don't open on the last row
@@ -762,39 +856,58 @@ class Backtesting:
if (
(position_stacking or len(open_trades[pair]) == 0)
and self.trade_slot_available(max_open_trades, open_trade_count_start)
and tmp != end_date
and current_time != end_date
and trade_dir is not None
and not PairLocks.is_pair_locked(pair, row[DATE_IDX])
):
trade = self._enter_trade(pair, row, trade_dir)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behaviour - not sure if this is correct
# This emulates previous behavior - not sure if this is correct
# Prevents buying if the trade-slot was freed in this candle
open_trade_count_start += 1
open_trade_count += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
open_trades[pair].append(trade)
LocalTrade.add_bt_trade(trade)
for trade in list(open_trades[pair]):
# also check the buying candle for sell conditions.
trade_entry = self._get_sell_trade_entry(trade, row)
# Sell occurred
if trade_entry:
# 2. Process buy orders.
order = trade.select_order('buy', is_open=True)
if order and self._get_order_filled(order.price, row):
order.close_bt_order(current_time)
trade.open_order_id = None
LocalTrade.add_bt_trade(trade)
self.wallets.update()
# 3. Create sell orders (if any)
if not trade.open_order_id:
self._get_sell_trade_entry(trade, row) # Place sell order if necessary
# 4. Process sell orders.
order = trade.select_order('sell', is_open=True)
if order and self._get_order_filled(order.price, row):
trade.open_order_id = None
trade.close_date = current_time
trade.close(order.price, show_msg=False)
# logger.debug(f"{pair} - Backtesting sell {trade}")
open_trade_count -= 1
open_trades[pair].remove(trade)
LocalTrade.close_bt_trade(trade)
trades.append(trade_entry)
if enable_protections:
self.protections.stop_per_pair(pair, row[DATE_IDX])
self.protections.global_stop(tmp)
trades.append(trade)
self.wallets.update()
self.run_protections(enable_protections, pair, current_time)
# 5. Cancel expired buy/sell orders.
if self.check_order_cancel(trade, current_time):
# Close trade due to buy timeout expiration.
open_trade_count -= 1
open_trades[pair].remove(trade)
self.wallets.update()
# Move time one configured time_interval ahead.
self.progress.increment()
tmp += timedelta(minutes=self.timeframe_min)
current_time += timedelta(minutes=self.timeframe_min)
trades += self.handle_left_open(open_trades, data=data)
self.wallets.update()
@@ -805,6 +918,8 @@ class Backtesting:
'config': self.strategy.config,
'locks': PairLocks.get_all_locks(),
'rejected_signals': self.rejected_trades,
'timedout_entry_orders': self.timedout_entry_orders,
'timedout_exit_orders': self.timedout_exit_orders,
'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']),
}

30
freqtrade/optimize/hyperopt_loss_profit_drawdown.py Normal file
View File

@@ -0,0 +1,30 @@
"""
ProfitDrawDownHyperOptLoss
This module defines the alternative HyperOptLoss class based on Profit &
Drawdown objective which can be used for Hyperoptimization.
Possible to change `DRAWDOWN_MULT` to penalize drawdown objective for
individual needs.
"""
from pandas import DataFrame
from freqtrade.data.btanalysis import calculate_max_drawdown
from freqtrade.optimize.hyperopt import IHyperOptLoss
# higher numbers penalize drawdowns more severely
DRAWDOWN_MULT = 0.075
class ProfitDrawDownHyperOptLoss(IHyperOptLoss):
@staticmethod
def hyperopt_loss_function(results: DataFrame, trade_count: int, *args, **kwargs) -> float:
total_profit = results["profit_abs"].sum()
try:
max_drawdown_abs = calculate_max_drawdown(results, value_col="profit_abs")[5]
except ValueError:
max_drawdown_abs = 0
return -1 * (total_profit * (1 - max_drawdown_abs * DRAWDOWN_MULT))

5
freqtrade/optimize/optimize_reports.py
View File

@@ -442,6 +442,8 @@ def generate_strategy_stats(pairlist: List[str],
'dry_run_wallet': start_balance,
'final_balance': content['final_balance'],
'rejected_signals': content['rejected_signals'],
'timedout_entry_orders': content['timedout_entry_orders'],
'timedout_exit_orders': content['timedout_exit_orders'],
'max_open_trades': max_open_trades,
'max_open_trades_setting': (config['max_open_trades']
if config['max_open_trades'] != float('inf') else -1),
@@ -747,6 +749,9 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')),
('Entry/Exit Timeouts',
f"{strat_results.get('timedout_entry_orders', 'N/A')} / "
f"{strat_results.get('timedout_exit_orders', 'N/A')}"),
('', ''), # Empty line to improve readability
('Min balance', round_coin_value(strat_results['csum_min'],