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Merge pull request #5924 from freqtrade/feat/leverage 

call leverage methods
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Matthias 2021-11-21 19:30:27 +01:00 committed by GitHub
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81
docs/backtesting.md
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@ -371,42 +371,48 @@ The last element of the backtest report is the summary metrics table.
It contains some useful key metrics about performance of your strategy on backtesting data.
```
=============== SUMMARY METRICS ===============
| Metric | Value |
|-----------------------+---------------------|
| Backtesting from | 2019-01-01 00:00:00 |
| Backtesting to | 2019-05-01 00:00:00 |
| Max open trades | 3 |
| | |
| Total/Daily Avg Trades| 429 / 3.575 |
| Starting balance | 0.01000000 BTC |
| Final balance | 0.01762792 BTC |
| Absolute profit | 0.00762792 BTC |
| Total profit % | 76.2% |
| Avg. stake amount | 0.001 BTC |
| Total trade volume | 0.429 BTC |
| | |
| Best Pair | LSK/BTC 26.26% |
| Worst Pair | ZEC/BTC -10.18% |
| Best Trade | LSK/BTC 4.25% |
| Worst Trade | ZEC/BTC -10.25% |
| Best day | 0.00076 BTC |
| Worst day | -0.00036 BTC |
| Days win/draw/lose | 12 / 82 / 25 |
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Rejected Buy signals | 3089 |
| | |
| Min balance | 0.00945123 BTC |
| Max balance | 0.01846651 BTC |
| Drawdown | 50.63% |
| Drawdown | 0.0015 BTC |
| Drawdown high | 0.0013 BTC |
| Drawdown low | -0.0002 BTC |
| Drawdown Start | 2019-02-15 14:10:00 |
| Drawdown End | 2019-04-11 18:15:00 |
| Market change | -5.88% |
===============================================
================ SUMMARY METRICS ===============
| Metric | Value |
|------------------------+---------------------|
| Backtesting from | 2019-01-01 00:00:00 |
| Backtesting to | 2019-05-01 00:00:00 |
| Max open trades | 3 |
| | |
| Total/Daily Avg Trades | 429 / 3.575 |
| Starting balance | 0.01000000 BTC |
| Final balance | 0.01762792 BTC |
| Absolute profit | 0.00762792 BTC |
| Total profit % | 76.2% |
| Avg. stake amount | 0.001 BTC |
| Total trade volume | 0.429 BTC |
| | |
| Long / Short | 352 / 77 |
| Total profit Long % | 1250.58% |
| Total profit Short % | -15.02% |
| Absolute profit Long | 0.00838792 BTC |
| Absolute profit Short | -0.00076 BTC |
| | |
| Best Pair | LSK/BTC 26.26% |
| Worst Pair | ZEC/BTC -10.18% |
| Best Trade | LSK/BTC 4.25% |
| Worst Trade | ZEC/BTC -10.25% |
| Best day | 0.00076 BTC |
| Worst day | -0.00036 BTC |
| Days win/draw/lose | 12 / 82 / 25 |
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Rejected Buy signals | 3089 |
| | |
| Min balance | 0.00945123 BTC |
| Max balance | 0.01846651 BTC |
| Drawdown | 50.63% |
| Drawdown | 0.0015 BTC |
| Drawdown high | 0.0013 BTC |
| Drawdown low | -0.0002 BTC |
| Drawdown Start | 2019-02-15 14:10:00 |
| Drawdown End | 2019-04-11 18:15:00 |
| Market change | -5.88% |
================================================
```
@ -430,6 +436,9 @@ It contains some useful key metrics about performance of your strategy on backte
- `Drawdown high` / `Drawdown low`: Profit at the beginning and end of the largest drawdown period. A negative low value means initial capital lost.
- `Drawdown Start` / `Drawdown End`: Start and end datetime for this largest drawdown (can also be visualized via the `plot-dataframe` sub-command).
- `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column.
- `Long / Short`: Split long/short values (Only shown when short trades were made).
- `Total profit Long %` / `Absolute profit Long`: Profit long trades only (Only shown when short trades were made).
- `Total profit Short %` / `Absolute profit Short`: Profit short trades only (Only shown when short trades were made).
### Daily / Weekly / Monthly breakdown

1
docs/bot-basics.md
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@ -43,6 +43,7 @@ By default, loop runs every few seconds (`internals.process_throttle_secs`) and
* Determine buy-price based on `bid_strategy` configuration setting, or by using the `custom_entry_price()` callback.
* Determine stake size by calling the `custom_stake_amount()` callback.
* Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
* In Margin and Futures mode, `leverage()` strategy callback is called to determine the desired leverage.
This loop will be repeated again and again until the bot is stopped.

4
freqtrade/data/btanalysis.py
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@ -30,7 +30,9 @@ BT_DATA_COLUMNS = ['pair', 'stake_amount', 'amount', 'open_date', 'close_date',
'fee_open', 'fee_close', 'trade_duration',
'profit_ratio', 'profit_abs', 'sell_reason',
'initial_stop_loss_abs', 'initial_stop_loss_ratio', 'stop_loss_abs',
'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'buy_tag']
'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'buy_tag',
'is_short'
]
# TODO-lev: usage of the above might need compatibility code (buy_tag, is_short?, ...?)

23
freqtrade/freqtradebot.py
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@ -576,7 +576,6 @@ class FreqtradeBot(LoggingMixin):
stake_amount: float,
price: Optional[float] = None,
forcebuy: bool = False,
leverage: float = 1.0,
is_short: bool = False,
enter_tag: Optional[str] = None
) -> bool:
@ -590,6 +589,7 @@ class FreqtradeBot(LoggingMixin):
time_in_force = self.strategy.order_time_in_force['buy']
[side, name] = ['sell', 'Short'] if is_short else ['buy', 'Long']
trade_side = 'short' if is_short else 'long'
if price:
enter_limit_requested = price
@ -606,11 +606,14 @@ class FreqtradeBot(LoggingMixin):
if not enter_limit_requested:
raise PricingError(f'Could not determine {side} price.')
# Min-stake-amount should actually include Leverage - this way our "minimal"
# stake- amount might be higher than necessary.
# We do however also need min-stake to determine leverage, therefore this is ignored as
# edge-case for now.
min_stake_amount = self.exchange.get_min_pair_stake_amount(
pair,
enter_limit_requested,
self.strategy.stoploss,
leverage=leverage
)
if not self.edge:
@ -620,7 +623,7 @@ class FreqtradeBot(LoggingMixin):
pair=pair, current_time=datetime.now(timezone.utc),
current_rate=enter_limit_requested, proposed_stake=stake_amount,
min_stake=min_stake_amount, max_stake=max_stake_amount,
side='short' if is_short else 'long'
side=trade_side
)
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
@ -628,6 +631,18 @@ class FreqtradeBot(LoggingMixin):
if not stake_amount:
return False
max_leverage = self.exchange.get_max_leverage(pair, stake_amount)
leverage = strategy_safe_wrapper(self.strategy.leverage, default_retval=1.0)(
pair=pair,
current_time=datetime.now(timezone.utc),
current_rate=enter_limit_requested,
proposed_leverage=1.0,
max_leverage=max_leverage,
side=trade_side,
) if self.trading_mode != TradingMode.SPOT else 1.0
# Cap leverage between 1.0 and max_leverage.
leverage = min(max(leverage, 1.0), max_leverage)
logger.info(
f"{name} signal found: about create a new trade for {pair} with stake_amount: "
f"{stake_amount} ..."
@ -644,7 +659,7 @@ class FreqtradeBot(LoggingMixin):
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
time_in_force=time_in_force, current_time=datetime.now(timezone.utc),
side='short' if is_short else 'long'
side=trade_side
):
logger.info(f"User requested abortion of buying {pair}")
return False

25
freqtrade/optimize/backtesting.py
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@ -368,6 +368,10 @@ class Backtesting:
def _get_sell_trade_entry_for_candle(self, trade: LocalTrade,
sell_row: Tuple) -> Optional[LocalTrade]:
# TODO-lev: add interest / funding fees to trade object ->
# Must be done either here, or one level higher ->
# (if we don't want to do it at "detail" level)
sell_candle_time = 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]
@ -443,13 +447,13 @@ class Backtesting:
stake_amount = self.wallets.get_trade_stake_amount(pair, None)
except DependencyException:
return None
current_time = row[DATE_IDX].to_pydatetime()
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05) or 0
max_stake_amount = self.wallets.get_available_stake_amount()
stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
default_retval=stake_amount)(
pair=pair, current_time=row[DATE_IDX].to_pydatetime(), current_rate=row[OPEN_IDX],
pair=pair, current_time=current_time, current_rate=row[OPEN_IDX],
proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount,
side=direction)
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
@ -457,12 +461,24 @@ class Backtesting:
if not stake_amount:
return None
max_leverage = self.exchange.get_max_leverage(pair, stake_amount)
leverage = strategy_safe_wrapper(self.strategy.leverage, default_retval=1.0)(
pair=pair,
current_time=current_time,
current_rate=row[OPEN_IDX],
proposed_leverage=1.0,
max_leverage=max_leverage,
side=direction,
) if self._can_short else 1.0
# Cap leverage between 1.0 and max_leverage.
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']
# Confirm trade entry:
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=stake_amount, rate=row[OPEN_IDX],
time_in_force=time_in_force, current_time=row[DATE_IDX].to_pydatetime(),
time_in_force=time_in_force, current_time=current_time,
side=direction):
return None
@ -472,7 +488,7 @@ class Backtesting:
trade = LocalTrade(
pair=pair,
open_rate=row[OPEN_IDX],
open_date=row[DATE_IDX].to_pydatetime(),
open_date=current_time,
stake_amount=stake_amount,
amount=round(stake_amount / row[OPEN_IDX], 8),
fee_open=self.fee,
@ -481,6 +497,7 @@ class Backtesting:
buy_tag=row[ENTER_TAG_IDX] if has_enter_tag else None,
exchange=self._exchange_name,
is_short=(direction == 'short'),
leverage=leverage,
)
return trade
return None

37
freqtrade/optimize/optimize_reports.py
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@ -415,20 +415,20 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
return {}
config = content['config']
max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
starting_balance = config['dry_run_wallet']
start_balance = config['dry_run_wallet']
stake_currency = config['stake_currency']
pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
starting_balance=starting_balance,
starting_balance=start_balance,
results=results, skip_nan=False)
buy_tag_results = generate_tag_metrics("buy_tag", starting_balance=starting_balance,
buy_tag_results = generate_tag_metrics("buy_tag", starting_balance=start_balance,
results=results, skip_nan=False)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
results=results)
left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
starting_balance=starting_balance,
starting_balance=start_balance,
results=results.loc[results['is_open']],
skip_nan=True)
daily_stats = generate_daily_stats(results)
@ -454,12 +454,18 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
# 'days_breakdown_stats': days_breakdown_stats,
'total_trades': len(results),
'trade_count_long': len(results.loc[~results['is_short']]),
'trade_count_short': len(results.loc[results['is_short']]),
'total_volume': float(results['stake_amount'].sum()),
'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0,
'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0,
'profit_median': results['profit_ratio'].median() if len(results) > 0 else 0,
'profit_total': results['profit_abs'].sum() / starting_balance,
'profit_total': results['profit_abs'].sum() / start_balance,
'profit_total_long': results.loc[~results['is_short'], 'profit_abs'].sum() / start_balance,
'profit_total_short': results.loc[results['is_short'], 'profit_abs'].sum() / start_balance,
'profit_total_abs': results['profit_abs'].sum(),
'profit_total_long_abs': results.loc[~results['is_short'], 'profit_abs'].sum(),
'profit_total_short_abs': results.loc[results['is_short'], 'profit_abs'].sum(),
'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
'backtest_start_ts': int(min_date.timestamp() * 1000),
'backtest_end': max_date.strftime(DATETIME_PRINT_FORMAT),
@ -475,8 +481,8 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
'stake_amount': config['stake_amount'],
'stake_currency': config['stake_currency'],
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'starting_balance': starting_balance,
'dry_run_wallet': starting_balance,
'starting_balance': start_balance,
'dry_run_wallet': start_balance,
'final_balance': content['final_balance'],
'rejected_signals': content['rejected_signals'],
'max_open_trades': max_open_trades,
@ -520,7 +526,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
'max_drawdown_high': high_val,
})
csum_min, csum_max = calculate_csum(results, starting_balance)
csum_min, csum_max = calculate_csum(results, start_balance)
strat_stats.update({
'csum_min': csum_min,
'csum_max': csum_max
@ -709,6 +715,19 @@ def text_table_add_metrics(strat_results: Dict) -> str:
best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio'])
worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio'])
short_metrics = [
('', ''), # Empty line to improve readability
('Long / Short',
f"{strat_results.get('trade_count_long', 'total_trades')} / "
f"{strat_results.get('trade_count_short', 0)}"),
('Total profit Long %', f"{strat_results['profit_total_long']:.2%}"),
('Total profit Short %', f"{strat_results['profit_total_short']:.2%}"),
('Absolute profit Long', round_coin_value(strat_results['profit_total_long_abs'],
strat_results['stake_currency'])),
('Absolute profit Short', round_coin_value(strat_results['profit_total_short_abs'],
strat_results['stake_currency'])),
] if strat_results.get('trade_count_short', 0) > 0 else []
# Newly added fields should be ignored if they are missing in strat_results. hyperopt-show
# command stores these results and newer version of freqtrade must be able to handle old
# results with missing new fields.
@ -719,6 +738,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('', ''), # Empty line to improve readability
('Total/Daily Avg Trades',
f"{strat_results['total_trades']} / {strat_results['trades_per_day']}"),
('Starting balance', round_coin_value(strat_results['starting_balance'],
strat_results['stake_currency'])),
('Final balance', round_coin_value(strat_results['final_balance'],
@ -733,6 +753,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
strat_results['stake_currency'])),
('Total trade volume', round_coin_value(strat_results['total_volume'],
strat_results['stake_currency'])),
*short_metrics,
('', ''), # Empty line to improve readability
('Best Pair', f"{strat_results['best_pair']['key']} "
f"{strat_results['best_pair']['profit_sum']:.2%}"),

8
tests/optimize/test_backtesting.py
View File

@ -698,7 +698,8 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
'min_rate': [0.10370188, 0.10300000000000001],
'max_rate': [0.10501, 0.1038888],
'is_open': [False, False],
'buy_tag': [None, None]
'buy_tag': [None, None],
"is_short": [False, False],
})
pd.testing.assert_frame_equal(results, expected)
data_pair = processed[pair]
@ -1074,6 +1075,8 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
'stake_amount': [0.01, 0.01],
'open_rate': [0.104445, 0.10302485],
'close_rate': [0.104969, 0.103541],
"is_short": [False, False],
'sell_reason': [SellType.ROI, SellType.ROI]
})
result2 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'],
@ -1091,6 +1094,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
'stake_amount': [0.01, 0.01, 0.01],
'open_rate': [0.104445, 0.10302485, 0.122541],
'close_rate': [0.104969, 0.103541, 0.123541],
"is_short": [False, False, False],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
})
backtestmock = MagicMock(side_effect=[
@ -1180,6 +1184,7 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
'2018-01-30 05:35:00', ], utc=True),
'trade_duration': [235, 40],
'is_open': [False, False],
'is_short': [False, False],
'stake_amount': [0.01, 0.01],
'open_rate': [0.104445, 0.10302485],
'close_rate': [0.104969, 0.103541],
@ -1197,6 +1202,7 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
'2018-01-30 08:30:00'], utc=True),
'trade_duration': [47, 40, 20],
'is_open': [False, False, False],
'is_short': [False, False, False],
'stake_amount': [0.01, 0.01, 0.01],
'open_rate': [0.104445, 0.10302485, 0.122541],
'close_rate': [0.104969, 0.103541, 0.123541],

2
tests/optimize/test_hyperopt.py
View File

@ -344,6 +344,7 @@ def test_hyperopt_format_results(hyperopt):
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
@ -412,6 +413,7 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]

2
tests/optimize/test_optimize_reports.py
View File

@ -76,6 +76,7 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
@ -124,6 +125,7 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.ROI,
SellType.STOP_LOSS, SellType.FORCE_SELL]

21
tests/test_freqtradebot.py
View File

@ -701,17 +701,26 @@ def test_process_informative_pairs_added(default_conf_usdt, ticker_usdt, mocker)
assert ("ETH/USDT", default_conf_usdt["timeframe"]) in refresh_mock.call_args[0][0]
@pytest.mark.parametrize("trading_mode", [
'spot',
# TODO-lev: Enable other modes
# 'margin', 'futures'
]
)
@pytest.mark.parametrize("is_short", [False, True])
def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
limit_order_open, is_short) -> None:
limit_order_open, is_short, trading_mode) -> None:
open_order = limit_order_open[enter_side(is_short)]
order = limit_order[enter_side(is_short)]
default_conf_usdt['trading_mode'] = trading_mode
leverage = 1.0 if trading_mode == 'spot' else 3.0
default_conf_usdt['collateral'] = 'cross'
patch_RPCManager(mocker)
patch_exchange(mocker)
freqtrade = FreqtradeBot(default_conf_usdt)
freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=False)
freqtrade.strategy.leverage = MagicMock(return_value=leverage)
stake_amount = 2
bid = 0.11
enter_rate_mock = MagicMock(return_value=bid)
@ -727,6 +736,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
create_order=enter_mm,
get_min_pair_stake_amount=MagicMock(return_value=1),
get_fee=fee,
get_funding_fees=MagicMock(return_value=0),
)
pair = 'ETH/USDT'
@ -744,7 +754,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
call_args = enter_mm.call_args_list[0][1]
assert call_args['pair'] == pair
assert call_args['rate'] == bid
assert call_args['amount'] == round(stake_amount / bid, 8)
assert pytest.approx(call_args['amount'], round(stake_amount / bid * leverage, 8))
enter_rate_mock.reset_mock()
# Should create an open trade with an open order id
@ -766,7 +776,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
call_args = enter_mm.call_args_list[1][1]
assert call_args['pair'] == pair
assert call_args['rate'] == fix_price
assert call_args['amount'] == round(stake_amount / fix_price, 8)
assert pytest.approx(call_args['amount'], round(stake_amount / fix_price * leverage, 8))
# In case of closed order
order['status'] = 'closed'
@ -824,7 +834,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
# In case of the order is rejected and not filled at all
order['status'] = 'rejected'
order['amount'] = 30.0
order['amount'] = 30.0 * leverage
order['filled'] = 0.0
order['remaining'] = 30.0
order['price'] = 0.5
@ -833,6 +843,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
mocker.patch('freqtrade.exchange.Exchange.create_order',
MagicMock(return_value=order))
assert not freqtrade.execute_entry(pair, stake_amount)
assert freqtrade.strategy.leverage.call_count == 0 if trading_mode == 'spot' else 2
# Fail to get price...
mocker.patch('freqtrade.exchange.Exchange.get_rate', MagicMock(return_value=0.0))