Update drawdown calculation to account drawdown

docs/backtesting.md

@@ -312,7 +312,7 @@ A backtesting result will look like that:
 |                       |                     |
 | Min balance           | 0.00945123 BTC      |
 | Max balance           | 0.01846651 BTC      |
-| Drawdown              | 50.63%              |
+| Drawdown (Account)    | 13.33%              |
 | Drawdown              | 0.0015 BTC          |
 | Drawdown high         | 0.0013 BTC          |
 | Drawdown low          | -0.0002 BTC         |
@@ -399,7 +399,7 @@ It contains some useful key metrics about performance of your strategy on backte
 |                       |                     |
 | Min balance           | 0.00945123 BTC      |
 | Max balance           | 0.01846651 BTC      |
-| Drawdown              | 50.63%              |
+| Drawdown (Account)    | 13.33%              |
 | Drawdown              | 0.0015 BTC          |
 | Drawdown high         | 0.0013 BTC          |
 | Drawdown low          | -0.0002 BTC         |
@@ -426,7 +426,8 @@ It contains some useful key metrics about performance of your strategy on backte
 - `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
 - `Rejected Buy signals`: Buy signals that could not be acted upon due to max_open_trades being reached.
 - `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period.
-- `Drawdown`: Maximum drawdown experienced. For example, the value of 50% means that from highest to subsequent lowest point, a 50% drop was experienced).
+- `Drawdown (Account)`: Maximum Account Drawdown experienced. Calculated as $(Absolute Drawdown) / (DrawdownHigh + startingBalance)$.
+- `Drawdown`: Maximum, absolute drawdown experienced. Difference between Drawdown High and Low.
 - `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.

freqtrade/data/btanalysis.py

@@ -392,15 +392,17 @@ def calculate_underwater(trades: pd.DataFrame, *, date_col: str = 'close_date',
 
 
 def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date',
-                           value_col: str = 'profit_ratio'
+                           value_col: str = 'profit_abs', starting_balance: float = 0
-                           ) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float]:
+                           ) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float, float]:
     """
     Calculate max drawdown and the corresponding close dates
     :param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
     :param date_col: Column in DataFrame to use for dates (defaults to 'close_date')
-    :param value_col: Column in DataFrame to use for values (defaults to 'profit_ratio')
+    :param value_col: Column in DataFrame to use for values (defaults to 'profit_abs')
-    :return: Tuple (float, highdate, lowdate, highvalue, lowvalue) with absolute max drawdown,
+    :param starting_balance: Portfolio starting balance - properly calculate relative drawdown.
-             high and low time and high and low value.
+    :return: Tuple (float, highdate, lowdate, highvalue, lowvalue, relative_drawdown)
+             with absolute max drawdown, high and low time and high and low value,
+             and the relative account drawdown
     :raise: ValueError if trade-dataframe was found empty.
     """
     if len(trades) == 0:
@@ -416,7 +418,17 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
     high_val = max_drawdown_df.loc[max_drawdown_df.iloc[:idxmin]
                                    ['high_value'].idxmax(), 'cumulative']
     low_val = max_drawdown_df.loc[idxmin, 'cumulative']
-    return abs(min(max_drawdown_df['drawdown'])), high_date, low_date, high_val, low_val
+
+    max_drawdown_rel = (high_val - low_val) / (high_val + starting_balance)
+
+    return (
+        abs(min(max_drawdown_df['drawdown'])),
+        high_date,
+        low_date,
+        high_val,
+        low_val,
+        max_drawdown_rel
+    )
 
 
 def calculate_csum(trades: pd.DataFrame, starting_balance: float = 0) -> Tuple[float, float]:

freqtrade/optimize/optimize_reports.py

@@ -462,12 +462,11 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
     }
 
     try:
-        max_drawdown, _, _, _, _ = calculate_max_drawdown(
+        (drawdown_abs, drawdown_start, drawdown_end, high_val, low_val,
-            results, value_col='profit_ratio')
+         max_drawdown) = calculate_max_drawdown(
-        drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown(
+             results, value_col='profit_abs', starting_balance=starting_balance)
-            results, value_col='profit_abs')
         strat_stats.update({
-            'max_drawdown': max_drawdown,
+            'max_drawdown_account': max_drawdown,
             'max_drawdown_abs': drawdown_abs,
             'drawdown_start': drawdown_start.strftime(DATETIME_PRINT_FORMAT),
             'drawdown_start_ts': drawdown_start.timestamp() * 1000,
@@ -486,7 +485,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
 
     except ValueError:
         strat_stats.update({
-            'max_drawdown': 0.0,
+            'max_drawdown_account': 0.0,
             'max_drawdown_abs': 0.0,
             'max_drawdown_low': 0.0,
             'max_drawdown_high': 0.0,
@@ -716,7 +715,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
             ('Max balance', round_coin_value(strat_results['csum_max'],
                                              strat_results['stake_currency'])),
 
-            ('Drawdown', f"{strat_results['max_drawdown']:.2%}"),
+            ('Drawdown (Account)', f"{strat_results['max_drawdown_account']:.2%}"),
             ('Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
                                           strat_results['stake_currency'])),
             ('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],

freqtrade/plot/plotting.py

@@ -161,7 +161,7 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
     Add scatter points indicating max drawdown
     """
     try:
-        max_drawdown, highdate, lowdate, _, _ = calculate_max_drawdown(trades)
+        _, highdate, lowdate, _, _, max_drawdown = calculate_max_drawdown(trades)
 
         drawdown = go.Scatter(
             x=[highdate, lowdate],