Merge pull request #11561 from mrpabloyeah/calculate-and-save-all-metrics-per-pair

Calculate and save all metrics per pair
This commit is contained in:
Matthias
2025-04-05 18:12:35 +02:00
committed by GitHub
2 changed files with 107 additions and 11 deletions

View File

@@ -70,7 +70,11 @@ def generate_rejected_signals(
def _generate_result_line( def _generate_result_line(
result: DataFrame, starting_balance: float, first_column: str | list[str] result: DataFrame,
min_date: datetime,
max_date: datetime,
starting_balance: float,
first_column: str | list[str],
) -> dict: ) -> dict:
""" """
Generate one result dict, with "first_column" as key. Generate one result dict, with "first_column" as key.
@@ -78,6 +82,20 @@ def _generate_result_line(
profit_sum = result["profit_ratio"].sum() profit_sum = result["profit_ratio"].sum()
# (end-capital - starting capital) / starting capital # (end-capital - starting capital) / starting capital
profit_total = result["profit_abs"].sum() / starting_balance profit_total = result["profit_abs"].sum() / starting_balance
backtest_days = (max_date - min_date).days or 1
final_balance = starting_balance + result["profit_abs"].sum()
expectancy, expectancy_ratio = calculate_expectancy(result)
winning_profit = result.loc[result["profit_abs"] > 0, "profit_abs"].sum()
losing_profit = result.loc[result["profit_abs"] < 0, "profit_abs"].sum()
profit_factor = winning_profit / abs(losing_profit) if losing_profit else 0.0
try:
drawdown = calculate_max_drawdown(
result, value_col="profit_abs", starting_balance=starting_balance
)
except ValueError:
drawdown = None
return { return {
"key": first_column, "key": first_column,
@@ -106,6 +124,16 @@ def _generate_result_line(
"draws": len(result[result["profit_abs"] == 0]), "draws": len(result[result["profit_abs"] == 0]),
"losses": len(result[result["profit_abs"] < 0]), "losses": len(result[result["profit_abs"] < 0]),
"winrate": len(result[result["profit_abs"] > 0]) / len(result) if len(result) else 0.0, "winrate": len(result[result["profit_abs"] > 0]) / len(result) if len(result) else 0.0,
"cagr": calculate_cagr(backtest_days, starting_balance, final_balance),
"expectancy": expectancy,
"expectancy_ratio": expectancy_ratio,
"sortino": calculate_sortino(result, min_date, max_date, starting_balance),
"sharpe": calculate_sharpe(result, min_date, max_date, starting_balance),
"calmar": calculate_calmar(result, min_date, max_date, starting_balance),
"sqn": calculate_sqn(result, starting_balance),
"profit_factor": profit_factor,
"max_drawdown_account": drawdown.relative_account_drawdown if drawdown else 0.0,
"max_drawdown_abs": drawdown.drawdown_abs if drawdown else 0.0,
} }
@@ -121,6 +149,8 @@ def generate_pair_metrics( #
stake_currency: str, stake_currency: str,
starting_balance: float, starting_balance: float,
results: DataFrame, results: DataFrame,
min_date: datetime,
max_date: datetime,
skip_nan: bool = False, skip_nan: bool = False,
) -> list[dict]: ) -> list[dict]:
""" """
@@ -140,13 +170,18 @@ def generate_pair_metrics( #
if skip_nan and result["profit_abs"].isnull().all(): if skip_nan and result["profit_abs"].isnull().all():
continue continue
tabular_data.append(_generate_result_line(result, starting_balance, pair)) tabular_data.append(
_generate_result_line(result, min_date, max_date, starting_balance, pair)
)
# Sort by total profit %: # Sort by total profit %:
tabular_data = sorted(tabular_data, key=lambda k: k["profit_total_abs"], reverse=True) tabular_data = sorted(tabular_data, key=lambda k: k["profit_total_abs"], reverse=True)
# Append Total # Append Total
tabular_data.append(_generate_result_line(results, starting_balance, "TOTAL")) tabular_data.append(
_generate_result_line(results, min_date, max_date, starting_balance, "TOTAL")
)
return tabular_data return tabular_data
@@ -154,6 +189,8 @@ def generate_tag_metrics(
tag_type: Literal["enter_tag", "exit_reason"] | list[Literal["enter_tag", "exit_reason"]], tag_type: Literal["enter_tag", "exit_reason"] | list[Literal["enter_tag", "exit_reason"]],
starting_balance: float, starting_balance: float,
results: DataFrame, results: DataFrame,
min_date: datetime,
max_date: datetime,
skip_nan: bool = False, skip_nan: bool = False,
) -> list[dict]: ) -> list[dict]:
""" """
@@ -173,13 +210,17 @@ def generate_tag_metrics(
if skip_nan and group["profit_abs"].isnull().all(): if skip_nan and group["profit_abs"].isnull().all():
continue continue
tabular_data.append(_generate_result_line(group, starting_balance, tags)) tabular_data.append(
_generate_result_line(group, min_date, max_date, starting_balance, tags)
)
# Sort by total profit %: # Sort by total profit %:
tabular_data = sorted(tabular_data, key=lambda k: k["profit_total_abs"], reverse=True) tabular_data = sorted(tabular_data, key=lambda k: k["profit_total_abs"], reverse=True)
# Append Total # Append Total
tabular_data.append(_generate_result_line(results, starting_balance, "TOTAL")) tabular_data.append(
_generate_result_line(results, min_date, max_date, starting_balance, "TOTAL")
)
return tabular_data return tabular_data
else: else:
return [] return []
@@ -395,19 +436,33 @@ def generate_strategy_stats(
stake_currency=stake_currency, stake_currency=stake_currency,
starting_balance=start_balance, starting_balance=start_balance,
results=results, results=results,
min_date=min_date,
max_date=max_date,
skip_nan=False, skip_nan=False,
) )
enter_tag_stats = generate_tag_metrics( enter_tag_stats = generate_tag_metrics(
"enter_tag", starting_balance=start_balance, results=results, skip_nan=False "enter_tag",
starting_balance=start_balance,
results=results,
min_date=min_date,
max_date=max_date,
skip_nan=False,
) )
exit_reason_stats = generate_tag_metrics( exit_reason_stats = generate_tag_metrics(
"exit_reason", starting_balance=start_balance, results=results, skip_nan=False "exit_reason",
starting_balance=start_balance,
results=results,
min_date=min_date,
max_date=max_date,
skip_nan=False,
) )
mix_tag_stats = generate_tag_metrics( mix_tag_stats = generate_tag_metrics(
["enter_tag", "exit_reason"], ["enter_tag", "exit_reason"],
starting_balance=start_balance, starting_balance=start_balance,
results=results, results=results,
min_date=min_date,
max_date=max_date,
skip_nan=False, skip_nan=False,
) )
left_open_results = generate_pair_metrics( left_open_results = generate_pair_metrics(
@@ -415,6 +470,8 @@ def generate_strategy_stats(
stake_currency=stake_currency, stake_currency=stake_currency,
starting_balance=start_balance, starting_balance=start_balance,
results=results.loc[results["exit_reason"] == "force_exit"], results=results.loc[results["exit_reason"] == "force_exit"],
min_date=min_date,
max_date=max_date,
skip_nan=True, skip_nan=True,
) )

View File

@@ -68,11 +68,21 @@ def test_text_table_bt_results(capsys):
"profit_ratio": [0.1, 0.2, -0.05], "profit_ratio": [0.1, 0.2, -0.05],
"profit_abs": [0.2, 0.4, -0.1], "profit_abs": [0.2, 0.4, -0.1],
"trade_duration": [10, 30, 20], "trade_duration": [10, 30, 20],
"close_date": [
dt_utc(2017, 11, 14, 21, 35, 00),
dt_utc(2017, 11, 14, 22, 10, 00),
dt_utc(2017, 11, 14, 22, 43, 00),
],
} }
) )
pair_results = generate_pair_metrics( pair_results = generate_pair_metrics(
["ETH/BTC"], stake_currency="BTC", starting_balance=4, results=results ["ETH/BTC"],
stake_currency="BTC",
starting_balance=4,
results=results,
min_date=dt_from_ts(1510688220),
max_date=dt_from_ts(1510700340),
) )
text_table_bt_results(pair_results, stake_currency="BTC", title="title") text_table_bt_results(pair_results, stake_currency="BTC", title="title")
text = capsys.readouterr().out text = capsys.readouterr().out
@@ -420,6 +430,10 @@ def test_generate_pair_metrics():
"profit_ratio": [0.1, 0.2], "profit_ratio": [0.1, 0.2],
"profit_abs": [0.2, 0.4], "profit_abs": [0.2, 0.4],
"trade_duration": [10, 30], "trade_duration": [10, 30],
"close_date": [
dt_utc(2017, 11, 14, 21, 35, 00),
dt_utc(2017, 11, 14, 22, 10, 00),
],
"wins": [2, 0], "wins": [2, 0],
"draws": [0, 0], "draws": [0, 0],
"losses": [0, 0], "losses": [0, 0],
@@ -427,7 +441,12 @@ def test_generate_pair_metrics():
) )
pair_results = generate_pair_metrics( pair_results = generate_pair_metrics(
["ETH/BTC"], stake_currency="BTC", starting_balance=2, results=results ["ETH/BTC"],
stake_currency="BTC",
starting_balance=2,
results=results,
min_date=dt_from_ts(1510688220),
max_date=dt_from_ts(1510700340),
) )
assert isinstance(pair_results, list) assert isinstance(pair_results, list)
assert len(pair_results) == 2 assert len(pair_results) == 2
@@ -512,6 +531,11 @@ def test_text_table_exit_reason(capsys):
"profit_ratio": [0.1, 0.2, -0.1], "profit_ratio": [0.1, 0.2, -0.1],
"profit_abs": [0.2, 0.4, -0.2], "profit_abs": [0.2, 0.4, -0.2],
"trade_duration": [10, 30, 10], "trade_duration": [10, 30, 10],
"close_date": [
dt_utc(2017, 11, 14, 21, 35, 00),
dt_utc(2017, 11, 14, 22, 10, 00),
dt_utc(2017, 11, 14, 22, 43, 00),
],
"wins": [2, 0, 0], "wins": [2, 0, 0],
"draws": [0, 0, 0], "draws": [0, 0, 0],
"losses": [0, 0, 1], "losses": [0, 0, 1],
@@ -520,7 +544,12 @@ def test_text_table_exit_reason(capsys):
) )
exit_reason_stats = generate_tag_metrics( exit_reason_stats = generate_tag_metrics(
"exit_reason", starting_balance=22, results=results, skip_nan=False "exit_reason",
starting_balance=22,
results=results,
min_date=dt_from_ts(1510688220),
max_date=dt_from_ts(1510700340),
skip_nan=False,
) )
text_table_tags("exit_tag", exit_reason_stats, "BTC") text_table_tags("exit_tag", exit_reason_stats, "BTC")
text = capsys.readouterr().out text = capsys.readouterr().out
@@ -550,6 +579,11 @@ def test_generate_sell_reason_stats():
"profit_ratio": [0.1, 0.2, -0.1], "profit_ratio": [0.1, 0.2, -0.1],
"profit_abs": [0.2, 0.4, -0.2], "profit_abs": [0.2, 0.4, -0.2],
"trade_duration": [10, 30, 10], "trade_duration": [10, 30, 10],
"close_date": [
dt_utc(2017, 11, 14, 21, 35, 00),
dt_utc(2017, 11, 14, 22, 10, 00),
dt_utc(2017, 11, 14, 22, 43, 00),
],
"wins": [2, 0, 0], "wins": [2, 0, 0],
"draws": [0, 0, 0], "draws": [0, 0, 0],
"losses": [0, 0, 1], "losses": [0, 0, 1],
@@ -558,7 +592,12 @@ def test_generate_sell_reason_stats():
) )
exit_reason_stats = generate_tag_metrics( exit_reason_stats = generate_tag_metrics(
"exit_reason", starting_balance=22, results=results, skip_nan=False "exit_reason",
starting_balance=22,
results=results,
min_date=dt_from_ts(1510688220),
max_date=dt_from_ts(1510700340),
skip_nan=False,
) )
roi_result = exit_reason_stats[0] roi_result = exit_reason_stats[0]
assert roi_result["key"] == "roi" assert roi_result["key"] == "roi"