Add CAGR calculation to backtesting

docs/backtesting.md

@@ -299,6 +299,7 @@ A backtesting result will look like that:
 | Final balance          | 0.01762792 BTC      |
 | Absolute profit        | 0.00762792 BTC      |
 | Total profit %         | 76.2%               |
+| CAGR %                 | 460.87%             |
 | Trades per day         | 3.575               |
 | Avg. stake amount      | 0.001      BTC      |
 | Total trade volume     | 0.429      BTC      |
@@ -388,6 +389,7 @@ It contains some useful key metrics about performance of your strategy on backte
 | Final balance          | 0.01762792 BTC      |
 | Absolute profit        | 0.00762792 BTC      |
 | Total profit %         | 76.2%               |
+| CAGR %                 | 460.87%             |
 | Avg. stake amount      | 0.001      BTC      |
 | Total trade volume     | 0.429      BTC      |
 |                        |                     |

freqtrade/data/btanalysis.py

@@ -553,3 +553,14 @@ def calculate_csum(trades: pd.DataFrame, starting_balance: float = 0) -> Tuple[f
     csum_max = csum_df['sum'].max() + starting_balance
 
     return csum_min, csum_max
+
+
+def calculate_cagr(days_passed: int, starting_balance: float, final_balance: float) -> float:
+    """
+    Calculate CAGR
+    :param days_passed: Days passed between start and ending balance
+    :param starting_balance: Starting balance
+    :param final_balance: Final balance to calculate CAGR against
+    :return: CAGR
+    """
+    return (final_balance / starting_balance) ** (1 / (days_passed / 365)) - 1

freqtrade/optimize/optimize_reports.py

@@ -9,7 +9,7 @@ from pandas import DataFrame, to_datetime
 from tabulate import tabulate
 
 from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT
-from freqtrade.data.btanalysis import (calculate_csum, calculate_market_change,
+from freqtrade.data.btanalysis import (calculate_cagr, calculate_csum, calculate_market_change,
                                        calculate_max_drawdown)
 from freqtrade.misc import (decimals_per_coin, file_dump_joblib, file_dump_json,
                             get_backtest_metadata_filename, round_coin_value)
@@ -446,6 +446,7 @@ def generate_strategy_stats(pairlist: List[str],
         '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(),
+        'cagr': calculate_cagr(backtest_days, start_balance, content['final_balance']),
         'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
         'backtest_start_ts': int(min_date.timestamp() * 1000),
         'backtest_end': max_date.strftime(DATETIME_PRINT_FORMAT),
@@ -746,6 +747,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
             ('Absolute profit ', round_coin_value(strat_results['profit_total_abs'],
                                                   strat_results['stake_currency'])),
             ('Total profit %', f"{strat_results['profit_total']:.2%}"),
+            ('CAGR %', f"{strat_results['cagr']:.2%}"),
             ('Trades per day', strat_results['trades_per_day']),
             ('Avg. daily profit %',
              f"{(strat_results['profit_total'] / strat_results['backtest_days']):.2%}"),

tests/data/test_btanalysis.py

@@ -8,13 +8,13 @@ from pandas import DataFrame, DateOffset, Timestamp, to_datetime
 
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import LAST_BT_RESULT_FN
-from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, analyze_trade_parallelism, calculate_csum,
+from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, analyze_trade_parallelism, calculate_cagr,
-                                       calculate_market_change, calculate_max_drawdown,
+                                       calculate_csum, calculate_market_change,
-                                       calculate_underwater, combine_dataframes_with_mean,
+                                       calculate_max_drawdown, calculate_underwater,
-                                       create_cum_profit, extract_trades_of_period,
+                                       combine_dataframes_with_mean, create_cum_profit,
-                                       get_latest_backtest_filename, get_latest_hyperopt_file,
+                                       extract_trades_of_period, get_latest_backtest_filename,
-                                       load_backtest_data, load_backtest_metadata, load_trades,
+                                       get_latest_hyperopt_file, load_backtest_data,
-                                       load_trades_from_db)
+                                       load_backtest_metadata, load_trades, load_trades_from_db)
 from freqtrade.data.history import load_data, load_pair_history
 from freqtrade.exceptions import OperationalException
 from tests.conftest import CURRENT_TEST_STRATEGY, create_mock_trades
@@ -336,6 +336,19 @@ def test_calculate_csum(testdatadir):
         csum_min, csum_max = calculate_csum(DataFrame())
 
 
+@pytest.mark.parametrize('start,end,days, expected', [
+    (64900, 176000, 3 * 365, 0.3945),
+    (64900, 176000, 365, 1.7119),
+    (1000, 1000, 365, 0.0),
+    (1000, 1500, 365, 0.5),
+    (1000, 1500, 100, 3.3927),  # sub year
+    (0.01000000, 0.01762792, 120, 4.6087),  # sub year BTC values
+])
+def test_calculate_cagr(start, end, days, expected):
+
+    assert round(calculate_cagr(days, start, end), 4) == expected
+
+
 def test_calculate_max_drawdown2():
     values = [0.011580, 0.010048, 0.011340, 0.012161, 0.010416, 0.010009, 0.020024,
               -0.024662, -0.022350, 0.020496, -0.029859, -0.030511, 0.010041, 0.010872,