Merge pull request #5924 from freqtrade/feat/leverage

call leverage methods

docs/backtesting.md

@@ -371,14 +371,14 @@ 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 ===============
+================ 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         |
+| Total/Daily Avg Trades | 429 / 3.575         |
 | Starting balance       | 0.01000000 BTC      |
 | Final balance          | 0.01762792 BTC      |
 | Absolute profit        | 0.00762792 BTC      |
@@ -386,6 +386,12 @@ It contains some useful key metrics about performance of your strategy on backte
 | 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%       |
@@ -406,7 +412,7 @@ It contains some useful key metrics about performance of your strategy on backte
 | 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
 

docs/bot-basics.md

@@ -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.
 

freqtrade/data/btanalysis.py

@@ -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?, ...?)
 
 

freqtrade/freqtradebot.py

@@ -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

freqtrade/optimize/backtesting.py

@@ -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

freqtrade/optimize/optimize_reports.py

@@ -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,
+        'starting_balance': start_balance,
-        'dry_run_wallet': starting_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%}"),

tests/optimize/test_backtesting.py

@@ -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],

tests/optimize/test_hyperopt.py

@@ -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]

tests/optimize/test_optimize_reports.py

@@ -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]

tests/test_freqtradebot.py

@@ -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))