commit
bb61250bfe
@ -300,6 +300,7 @@ A backtesting result will look like that:
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| Absolute profit | 0.00762792 BTC |
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| Total profit % | 76.2% |
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| CAGR % | 460.87% |
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| Profit factor | 1.11 |
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| Avg. stake amount | 0.001 BTC |
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| Total trade volume | 0.429 BTC |
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| | |
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@ -399,6 +400,7 @@ It contains some useful key metrics about performance of your strategy on backte
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| Absolute profit | 0.00762792 BTC |
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| Total profit % | 76.2% |
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| CAGR % | 460.87% |
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| Profit factor | 1.11 |
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| Avg. stake amount | 0.001 BTC |
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| Total trade volume | 0.429 BTC |
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| | |
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@ -444,6 +446,8 @@ It contains some useful key metrics about performance of your strategy on backte
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- `Final balance`: Final balance - starting balance + absolute profit.
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- `Absolute profit`: Profit made in stake currency.
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- `Total profit %`: Total profit. Aligned to the `TOTAL` row's `Tot Profit %` from the first table. Calculated as `(End capital − Starting capital) / Starting capital`.
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- `CAGR %`: Compound annual growth rate.
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- `Profit factor`: profit / loss.
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- `Avg. stake amount`: Average stake amount, either `stake_amount` or the average when using dynamic stake amount.
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- `Total trade volume`: Volume generated on the exchange to reach the above profit.
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- `Best Pair` / `Worst Pair`: Best and worst performing pair, and it's corresponding `Cum Profit %`.
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@ -270,10 +270,15 @@ Return a summary of your profit/loss and performance.
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> **Latest Trade opened:** `2 minutes ago`
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> **Avg. Duration:** `2:33:45`
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> **Best Performing:** `PAY/BTC: 50.23%`
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> **Trading volume:** `0.5 BTC`
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> **Profit factor:** `1.04`
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> **Max Drawdown:** `9.23% (0.01255 BTC)`
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The relative profit of `1.2%` is the average profit per trade.
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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`.
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Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits.
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Profit Factor is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy.
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Max drawdown corresponds to the backtesting metric `Absolute Drawdown (Account)` - calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`.
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### /forceexit <trade_id>
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@ -416,6 +416,9 @@ def generate_strategy_stats(pairlist: List[str],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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winning_profit = results.loc[results['profit_abs'] > 0, 'profit_abs'].sum()
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losing_profit = results.loc[results['profit_abs'] < 0, 'profit_abs'].sum()
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profit_factor = winning_profit / abs(losing_profit) if losing_profit else 0.0
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backtest_days = (max_date - min_date).days or 1
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strat_stats = {
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@ -443,6 +446,7 @@ def generate_strategy_stats(pairlist: List[str],
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'profit_total_long_abs': results.loc[~results['is_short'], 'profit_abs'].sum(),
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'profit_total_short_abs': results.loc[results['is_short'], 'profit_abs'].sum(),
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'cagr': calculate_cagr(backtest_days, start_balance, content['final_balance']),
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'profit_factor': profit_factor,
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'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
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'backtest_start_ts': int(min_date.timestamp() * 1000),
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'backtest_end': max_date.strftime(DATETIME_PRINT_FORMAT),
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@ -497,8 +501,10 @@ def generate_strategy_stats(pairlist: List[str],
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(drawdown_abs, drawdown_start, drawdown_end, high_val, low_val,
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max_drawdown) = calculate_max_drawdown(
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results, value_col='profit_abs', starting_balance=start_balance)
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# max_relative_drawdown = Underwater
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(_, _, _, _, _, max_relative_drawdown) = calculate_max_drawdown(
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results, value_col='profit_abs', starting_balance=start_balance, relative=True)
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strat_stats.update({
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'max_drawdown': max_drawdown_legacy, # Deprecated - do not use
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'max_drawdown_account': max_drawdown,
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@ -777,6 +783,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
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strat_results['stake_currency'])),
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('Total profit %', f"{strat_results['profit_total']:.2%}"),
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('CAGR %', f"{strat_results['cagr']:.2%}" if 'cagr' in strat_results else 'N/A'),
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('Profit factor', f'{strat_results["profit_factor"]:.2f}' if 'profit_factor'
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in strat_results else 'N/A'),
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('Trades per day', strat_results['trades_per_day']),
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('Avg. daily profit %',
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f"{(strat_results['profit_total'] / strat_results['backtest_days']):.2%}"),
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@ -1352,3 +1352,18 @@ class Trade(_DECL_BASE, LocalTrade):
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.group_by(Trade.pair) \
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.order_by(desc('profit_sum')).first()
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return best_pair
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@staticmethod
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def get_trading_volume(start_date: datetime = datetime.fromtimestamp(0)) -> float:
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"""
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Get Trade volume based on Orders
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NOTE: Not supported in Backtesting.
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:returns: Tuple containing (pair, profit_sum)
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"""
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trading_volume = Order.query.with_entities(
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func.sum(Order.cost).label('volume')
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).filter(
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Order.order_filled_date >= start_date,
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Order.status == 'closed'
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).scalar()
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return trading_volume
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@ -104,6 +104,10 @@ class Profit(BaseModel):
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best_pair_profit_ratio: float
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winning_trades: int
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losing_trades: int
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profit_factor: float
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max_drawdown: float
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max_drawdown_abs: float
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trading_volume: Optional[float]
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class SellReason(BaseModel):
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@ -18,6 +18,7 @@ from freqtrade import __version__
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from freqtrade.configuration.timerange import TimeRange
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from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT
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from freqtrade.data.history import load_data
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from freqtrade.data.metrics import calculate_max_drawdown
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from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State,
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TradingMode)
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from freqtrade.exceptions import ExchangeError, PricingError
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@ -415,6 +416,8 @@ class RPC:
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durations = []
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winning_trades = 0
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losing_trades = 0
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winning_profit = 0.0
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losing_profit = 0.0
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for trade in trades:
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current_rate: float = 0.0
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@ -430,8 +433,10 @@ class RPC:
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profit_closed_ratio.append(profit_ratio)
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if trade.close_profit >= 0:
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winning_trades += 1
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winning_profit += trade.close_profit_abs
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else:
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losing_trades += 1
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losing_profit += trade.close_profit_abs
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else:
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# Get current rate
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try:
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@ -447,6 +452,7 @@ class RPC:
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profit_all_ratio.append(profit_ratio)
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best_pair = Trade.get_best_pair(start_date)
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trading_volume = Trade.get_trading_volume(start_date)
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# Prepare data to display
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profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
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@ -470,6 +476,21 @@ class RPC:
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profit_closed_ratio_fromstart = profit_closed_coin_sum / starting_balance
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profit_all_ratio_fromstart = profit_all_coin_sum / starting_balance
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profit_factor = winning_profit / abs(losing_profit) if losing_profit else float('inf')
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trades_df = DataFrame([{'close_date': trade.close_date.strftime(DATETIME_PRINT_FORMAT),
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'profit_abs': trade.close_profit_abs}
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for trade in trades if not trade.is_open])
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max_drawdown_abs = 0.0
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max_drawdown = 0.0
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if len(trades_df) > 0:
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try:
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(max_drawdown_abs, _, _, _, _, max_drawdown) = calculate_max_drawdown(
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trades_df, value_col='profit_abs', starting_balance=starting_balance)
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except ValueError:
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# ValueError if no losing trade.
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pass
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profit_all_fiat = self._fiat_converter.convert_amount(
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profit_all_coin_sum,
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stake_currency,
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@ -508,6 +529,10 @@ class RPC:
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'best_pair_profit_ratio': best_pair[1] if best_pair else 0,
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'winning_trades': winning_trades,
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'losing_trades': losing_trades,
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'profit_factor': profit_factor,
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'max_drawdown': max_drawdown,
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'max_drawdown_abs': max_drawdown_abs,
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'trading_volume': trading_volume,
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}
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def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:
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@ -730,12 +730,18 @@ class Telegram(RPCHandler):
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f"*Total Trade Count:* `{trade_count}`\n"
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f"*{'First Trade opened' if not timescale else 'Showing Profit since'}:* "
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f"`{first_trade_date}`\n"
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f"*Latest Trade opened:* `{latest_trade_date}\n`"
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f"*Latest Trade opened:* `{latest_trade_date}`\n"
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f"*Win / Loss:* `{stats['winning_trades']} / {stats['losing_trades']}`"
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)
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if stats['closed_trade_count'] > 0:
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markdown_msg += (f"\n*Avg. Duration:* `{avg_duration}`\n"
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f"*Best Performing:* `{best_pair}: {best_pair_profit_ratio:.2%}`")
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markdown_msg += (
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f"\n*Avg. Duration:* `{avg_duration}`\n"
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f"*Best Performing:* `{best_pair}: {best_pair_profit_ratio:.2%}`\n"
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f"*Trading volume:* `{round_coin_value(stats['trading_volume'], stake_cur)}`\n"
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f"*Profit factor:* `{stats['profit_factor']:.2f}`\n"
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f"*Max Drawdown:* `{stats['max_drawdown']:.2%} "
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f"({round_coin_value(stats['max_drawdown_abs'], stake_cur)})`"
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)
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self._send_msg(markdown_msg, reload_able=True, callback_path="update_profit",
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query=update.callback_query)
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@ -29,6 +29,7 @@ def mock_order_1(is_short: bool):
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'average': 0.123,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.129,
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'remaining': 0.0,
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}
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@ -65,6 +66,7 @@ def mock_order_2(is_short: bool):
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'price': 0.123,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.129,
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'remaining': 0.0,
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}
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@ -79,6 +81,7 @@ def mock_order_2_sell(is_short: bool):
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'price': 0.128,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.129,
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'remaining': 0.0,
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}
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@ -126,6 +129,7 @@ def mock_order_3(is_short: bool):
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'price': 0.05,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.129,
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'remaining': 0.0,
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}
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@ -141,6 +145,7 @@ def mock_order_3_sell(is_short: bool):
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'average': 0.06,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.129,
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'remaining': 0.0,
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}
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@ -186,6 +191,7 @@ def mock_order_4(is_short: bool):
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'price': 0.123,
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'amount': 123.0,
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'filled': 0.0,
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'cost': 15.129,
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'remaining': 123.0,
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}
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@ -225,6 +231,7 @@ def mock_order_5(is_short: bool):
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'price': 0.123,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.129,
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'remaining': 0.0,
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}
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@ -239,6 +246,7 @@ def mock_order_5_stoploss(is_short: bool):
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'price': 0.123,
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'amount': 123.0,
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'filled': 0.0,
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'cost': 0.0,
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'remaining': 123.0,
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}
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@ -281,6 +289,7 @@ def mock_order_6(is_short: bool):
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'price': 0.15,
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'amount': 2.0,
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'filled': 2.0,
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'cost': 0.3,
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'remaining': 0.0,
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}
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@ -295,6 +304,7 @@ def mock_order_6_sell(is_short: bool):
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'price': 0.15 if is_short else 0.20,
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'amount': 2.0,
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'filled': 0.0,
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'cost': 0.0,
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'remaining': 2.0,
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}
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@ -337,6 +347,7 @@ def short_order():
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'price': 0.123,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.129,
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'remaining': 0.0,
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}
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@ -351,6 +362,7 @@ def exit_short_order():
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'price': 0.128,
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'amount': 123.0,
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'filled': 123.0,
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'cost': 15.744,
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'remaining': 0.0,
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}
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@ -424,6 +436,7 @@ def leverage_order():
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'amount': 123.0,
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'filled': 123.0,
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'remaining': 0.0,
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'cost': 15.129,
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'leverage': 5.0
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}
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@ -439,6 +452,7 @@ def leverage_order_sell():
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'amount': 123.0,
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'filled': 123.0,
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'remaining': 0.0,
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'cost': 15.744,
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'leverage': 5.0
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}
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@ -724,7 +724,9 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
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'profit_closed_fiat': -83.19455985, 'profit_closed_ratio_mean': -0.0075,
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'profit_closed_percent_mean': -0.75, 'profit_closed_ratio_sum': -0.015,
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'profit_closed_percent_sum': -1.5, 'profit_closed_ratio': -6.739057628404269e-06,
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'profit_closed_percent': -0.0, 'winning_trades': 0, 'losing_trades': 2}
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'profit_closed_percent': -0.0, 'winning_trades': 0, 'losing_trades': 2,
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'profit_factor': 0.0, 'trading_volume': 91.074,
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}
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),
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(
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False,
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@ -737,7 +739,9 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
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'profit_closed_fiat': 9.124559849999999, 'profit_closed_ratio_mean': 0.0075,
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'profit_closed_percent_mean': 0.75, 'profit_closed_ratio_sum': 0.015,
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'profit_closed_percent_sum': 1.5, 'profit_closed_ratio': 7.391275897987988e-07,
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'profit_closed_percent': 0.0, 'winning_trades': 2, 'losing_trades': 0}
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'profit_closed_percent': 0.0, 'winning_trades': 2, 'losing_trades': 0,
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'profit_factor': None, 'trading_volume': 91.074,
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}
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),
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(
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None,
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@ -750,7 +754,9 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
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'profit_closed_fiat': -67.02260985, 'profit_closed_ratio_mean': 0.0025,
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'profit_closed_percent_mean': 0.25, 'profit_closed_ratio_sum': 0.005,
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'profit_closed_percent_sum': 0.5, 'profit_closed_ratio': -5.429078808526421e-06,
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'profit_closed_percent': -0.0, 'winning_trades': 1, 'losing_trades': 1}
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'profit_closed_percent': -0.0, 'winning_trades': 1, 'losing_trades': 1,
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'profit_factor': 0.02775724835771106, 'trading_volume': 91.074,
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}
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)
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])
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def test_api_profit(botclient, mocker, ticker, fee, markets, is_short, expected):
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@ -803,6 +809,10 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, is_short, expected)
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'closed_trade_count': 2,
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'winning_trades': expected['winning_trades'],
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'losing_trades': expected['losing_trades'],
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'profit_factor': expected['profit_factor'],
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'max_drawdown': ANY,
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'max_drawdown_abs': ANY,
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'trading_volume': expected['trading_volume'],
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}
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|
@ -704,11 +704,13 @@ def test_profit_handle(default_conf_usdt, update, ticker_usdt, ticker_sell_up, f
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assert '∙ `6.253 USD`' in msg_mock.call_args_list[-1][0][0]
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assert '*Best Performing:* `ETH/USDT: 9.45%`' in msg_mock.call_args_list[-1][0][0]
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assert '*Max Drawdown:*' in msg_mock.call_args_list[-1][0][0]
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assert '*Profit factor:*' in msg_mock.call_args_list[-1][0][0]
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assert '*Trading volume:* `60 USDT`' in msg_mock.call_args_list[-1][0][0]
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@pytest.mark.parametrize('is_short', [True, False])
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def test_telegram_stats(default_conf, update, ticker, ticker_sell_up, fee,
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limit_buy_order, limit_sell_order, mocker, is_short) -> None:
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def test_telegram_stats(default_conf, update, ticker, fee, mocker, is_short) -> None:
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mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
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mocker.patch.multiple(
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'freqtrade.exchange.Exchange',
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|
@ -2269,6 +2269,7 @@ def test_Trade_object_idem():
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'get_exit_reason_performance',
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'get_enter_tag_performance',
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'get_mix_tag_performance',
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'get_trading_volume',
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)
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|
Loading…
Reference in New Issue
Block a user