Fix calcs, rename ratio, add docs

docs/telegram-usage.md

@@ -287,12 +287,17 @@ Return a summary of your profit/loss and performance.
 > **Best Performing:** `PAY/BTC: 50.23%`
 > **Trading volume:** `0.5 BTC`
 > **Profit factor:** `1.04`
+> **Win / Loss:** `102 / 36`
+> **Winrate:** `73.91%`
+> **Expectancy (Ratio):** `4.87 (1.66)`
 > **Max Drawdown:** `9.23% (0.01255 BTC)`
 
 The relative profit of `1.2%` is the average profit per trade.
 The relative profit of `15.2 Σ%` is be based on the starting capital - so in this case, the starting capital was `0.00485701 * 1.152 = 0.00738 BTC`.
 Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits.
 Profit Factor is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy.
+Expectancy corresponds to the average return per currency unit at risk, i.e. the winrate and the risk-reward ratio (the average gain of winning trades compared to the average loss of losing trades).
+Expectancy Ratio is expected profit or loss of a subsequent trade based on the performance of all past trades.
 Max drawdown corresponds to the backtesting metric `Absolute Drawdown (Account)` - calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`.
 Bot started date will refer to the date the bot was first started. For older bots, this will default to the first trade's open date.
 

freqtrade/rpc/api_server/api_schemas.py

@@ -138,7 +138,7 @@ class Profit(BaseModel):
     profit_factor: float
     winrate: float
     expectancy: float
-    expectancy_rate: float
+    expectancy_ratio: float
     max_drawdown: float
     max_drawdown_abs: float
     trading_volume: Optional[float]

freqtrade/rpc/rpc.py

@@ -524,15 +524,15 @@ class RPC:
         profit_factor = winning_profit / abs(losing_profit) if losing_profit else float('inf')
 
         mean_winning_profit = (winning_profit / winning_trades) if winning_trades > 0 else 0
-        mean_losing_profit = (losing_profit / losing_trades) if losing_trades > 0 else 0
+        mean_losing_profit = (abs(losing_profit) / losing_trades) if losing_trades > 0 else 0
 
         winrate = (winning_trades / closed_trade_count) * 100 if closed_trade_count > 0 else 0
         loserate = (100 - winrate)
 
-        expectancy, expectancy_rate = self.__calc_expectancy(mean_winning_profit,
+        expectancy, expectancy_ratio = self.__calc_expectancy(mean_winning_profit,
-                                                             mean_losing_profit,
+                                                              mean_losing_profit,
-                                                             winrate,
+                                                              winrate,
-                                                             loserate)
+                                                              loserate)
 
         trades_df = DataFrame([{'close_date': trade.close_date.strftime(DATETIME_PRINT_FORMAT),
                                 'profit_abs': trade.close_profit_abs}
@@ -591,7 +591,7 @@ class RPC:
             'profit_factor': profit_factor,
             'winrate': winrate,
             'expectancy': expectancy,
-            'expectancy_rate': expectancy_rate,
+            'expectancy_ratio': expectancy_ratio,
             'max_drawdown': max_drawdown,
             'max_drawdown_abs': max_drawdown_abs,
             'trading_volume': trading_volume,
@@ -629,20 +629,18 @@ class RPC:
             self, mean_winning_profit: float, mean_losing_profit: float,
             winrate: float, loserate: float) -> Tuple[float, float]:
 
-        expectancy = 1.0
+        expectancy = (
-        if mean_winning_profit > 0 and abs(mean_losing_profit) > 0:
-            expectancy = (
-                (1 + (mean_winning_profit / abs(mean_losing_profit))) * (winrate / 100) - 1
-            )
-        elif mean_winning_profit == 0:
-            expectancy = 0.0
-
-        expectancy_rate = (
             ((winrate / 100) * mean_winning_profit) -
             ((loserate / 100) * mean_losing_profit)
         )
 
-        return expectancy, expectancy_rate
+        expectancy_ratio = float('inf')
+        if mean_losing_profit > 0:
+            expectancy_ratio = (
+                ((1 + (mean_winning_profit / mean_losing_profit)) * (winrate / 100)) - 1
+            )
+
+        return expectancy, expectancy_ratio
 
     def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:
         """ Returns current account balance per crypto """

freqtrade/rpc/telegram.py

@@ -851,7 +851,7 @@ class Telegram(RPCHandler):
         best_pair_profit_ratio = stats['best_pair_profit_ratio']
         winrate = stats['winrate']
         expectancy = stats['expectancy']
-        expectancy_rate = stats['expectancy_rate']
+        expectancy_ratio = stats['expectancy_ratio']
 
         if stats['trade_count'] == 0:
             markdown_msg = f"No trades yet.\n*Bot started:* `{stats['bot_start_date']}`"
@@ -879,7 +879,7 @@ class Telegram(RPCHandler):
                 f"*Latest Trade opened:* `{latest_trade_date}`\n"
                 f"*Win / Loss:* `{stats['winning_trades']} / {stats['losing_trades']}`\n"
                 f"*Winrate:* `{winrate:.2f}%`\n"
-                f"*Expectancy (Rate):* `{expectancy:.2f} ({expectancy_rate:.2f})`"
+                f"*Expectancy (Ratio):* `{expectancy:.2f} ({expectancy_ratio:.2f})`"
             )
             if stats['closed_trade_count'] > 0:
                 markdown_msg += (

tests/rpc/test_rpc.py

@@ -403,7 +403,7 @@ def test_rpc_trade_statistics(default_conf_usdt, ticker, fee, mocker) -> None:
     assert res['latest_trade_date'] == ''
     assert res['latest_trade_timestamp'] == 0
     assert res['expectancy'] == 0
-    assert res['expectancy_rate'] == 0
+    assert res['expectancy_ratio'] == float('inf')
 
     # Create some test data
     create_mock_trades_usdt(fee)
@@ -416,14 +416,14 @@ def test_rpc_trade_statistics(default_conf_usdt, ticker, fee, mocker) -> None:
     assert pytest.approx(stats['profit_all_percent_mean']) == -57.86
     assert pytest.approx(stats['profit_all_fiat']) == -85.205614098
     assert pytest.approx(stats['winrate']) == 66.666666667
-    assert pytest.approx(stats['expectancy']) == 0.223308883
+    assert pytest.approx(stats['expectancy']) == 0.9133333333333327
     assert stats['trade_count'] == 7
     assert stats['first_trade_humanized'] == '2 days ago'
     assert stats['latest_trade_humanized'] == '17 minutes ago'
     assert stats['avg_duration'] in ('0:17:40')
     assert stats['best_pair'] == 'XRP/USDT'
     assert stats['best_rate'] == 10.0
-    assert stats['expectancy_rate'] == 3.64
+    assert stats['expectancy_ratio'] == 0.22330888345558253
 
     # Test non-available pair
     mocker.patch(f'{EXMS}.get_rate',

tests/rpc/test_rpc_apiserver.py

@@ -829,8 +829,8 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
          'profit_closed_percent_mean': -0.75, 'profit_closed_ratio_sum': -0.015,
          'profit_closed_percent_sum': -1.5, 'profit_closed_ratio': -6.739057628404269e-06,
          'profit_closed_percent': -0.0, 'winning_trades': 0, 'losing_trades': 2,
-         'profit_factor': 0.0, 'winrate': 0.0, 'expectancy': 0.0, 'expectancy_rate': 0.0033695635,
+         'profit_factor': 0.0, 'winrate': 0.0, 'expectancy': -0.0033695635,
-         'trading_volume': 91.074,
+         'expectancy_ratio': -1.0, 'trading_volume': 91.074,
          }
     ),
     (
@@ -845,8 +845,8 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
          'profit_closed_percent_mean': 0.75, 'profit_closed_ratio_sum': 0.015,
          'profit_closed_percent_sum': 1.5, 'profit_closed_ratio': 7.391275897987988e-07,
          'profit_closed_percent': 0.0, 'winning_trades': 2, 'losing_trades': 0,
-         'profit_factor': None, 'winrate': 100.0, 'expectancy': 1.0,
+         'profit_factor': None, 'winrate': 100.0, 'expectancy': 0.0003695635,
-         'expectancy_rate': 0.0003695635, 'trading_volume': 91.074,
+         'expectancy_ratio': None, 'trading_volume': 91.074,
          }
     ),
     (
@@ -861,8 +861,9 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
          'profit_closed_percent_mean': 0.25, 'profit_closed_ratio_sum': 0.005,
          'profit_closed_percent_sum': 0.5, 'profit_closed_ratio': -5.429078808526421e-06,
          'profit_closed_percent': -0.0, 'winning_trades': 1, 'losing_trades': 1,
-         'profit_factor': 0.02775724835771106, 'winrate': 50.0, 'expectancy': -0.48612137582114445,
+         'profit_factor': 0.02775724835771106, 'winrate': 50.0,
-         'expectancy_rate': 0.0028695635, 'trading_volume': 91.074,
+         'expectancy': -0.0027145635000000003, 'expectancy_ratio': -0.48612137582114445,
+         'trading_volume': 91.074,
          }
     )
 ])
@@ -921,7 +922,7 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, is_short, expected)
         'profit_factor': expected['profit_factor'],
         'winrate': expected['winrate'],
         'expectancy': expected['expectancy'],
-        'expectancy_rate': expected['expectancy_rate'],
+        'expectancy_ratio': expected['expectancy_ratio'],
         'max_drawdown': ANY,
         'max_drawdown_abs': ANY,
         'trading_volume': expected['trading_volume'],

tests/rpc/test_rpc_telegram.py

@@ -800,7 +800,7 @@ async def test_telegram_profit_handle(
     assert '*Max Drawdown:*' in msg_mock.call_args_list[-1][0][0]
     assert '*Profit factor:*' in msg_mock.call_args_list[-1][0][0]
     assert '*Winrate:*' in msg_mock.call_args_list[-1][0][0]
-    assert '*Expectancy (Rate):*' in msg_mock.call_args_list[-1][0][0]
+    assert '*Expectancy (Ratio):*' in msg_mock.call_args_list[-1][0][0]
     assert '*Trading volume:* `126 USDT`' in msg_mock.call_args_list[-1][0][0]