Result with Large Numbers and closing on chart on the same bar only

[pazooki]

why are the value of Equity Final [$] so large? is this the symptom of a deeper issue in my code?

TRADE Closed high:  0.02129583263633328
TRADE Closed Loss:  -0.05504850412714313
Start                     2018-12-01 00:00:00
End                       2022-12-31 23:59:00
Duration                   1491 days 23:59:00
Exposure Time [%]                   99.285114
Equity Final [$]          1066407785447538...
Equity Peak [$]           1588205732196593...
Return [%]                6665048659047115...
Buy & Hold Return [%]               315.84562
Return (Ann.) [%]           1059751111.017594
Volatility (Ann.) [%]     1441411030924.83...
Sharpe Ratio                         0.000735
Sortino Ratio                  7210940.767676
Calmar Ratio                  13582380.164676
Max. Drawdown [%]                  -78.023962
Avg. Drawdown [%]                   -3.452744
Max. Drawdown Duration       57 days 21:44:00
Avg. Drawdown Duration        0 days 08:20:00
# Trades                                 2747
Win Rate [%]                        82.271569
Best Trade [%]                       10.94706
Worst Trade [%]                    -11.164487
Avg. Trade [%]                       0.750508
Max. Trade Duration          15 days 14:30:00
Avg. Trade Duration           0 days 12:56:00
Profit Factor                        1.844796
Expectancy [%]                        0.79215
SQN                                  1.287107
_strategy                           DarkSteps

[pazooki]

Here is my code:

class MyStrategy(Strategy): 
    def next(self):
        if self.position:
            if self.position.pl_pct >= 0.015:
                self.position.close()
            elif self.position.pl_pct <= -0.002:
                self.position.close()
            else:
                print('Passing')
        else:
            if self.ema_buy:               
                self.buy(
                    limit=self.data.Close[-1], 
                    tp=self.data.Close[-1] + (self.data.Close[-1] * 0.5), 
                    stop=self.data.Low[-1] - (self.data.Low[-1] * 0.02)
                )
            elif ema_sell:                
                self.sell(
                    limit=self.data.High[-1] + (self.data.High[-1] * 0.05),  
                    tp=self.data.High[-1] - (self.data.High[-1] * 0.5),
                    stop=self.data.High[-1] - (self.data.High[-1] * 0.05), 
                    sl=self.data.High[-1] + (self.data.High[-1] * 0.06)
                )

The result has very large numbers in it and surprisingly almost no loss. the numbers look too good to be true.

/usr/local/lib/python3.9/dist-packages/backtesting/_stats.py:112: RuntimeWarning: overflow encountered in double_scalars
  annualized_return = (1 + gmean_day_return)**annual_trading_days - 1
/usr/local/lib/python3.9/dist-packages/backtesting/_stats.py:114: RuntimeWarning: overflow encountered in double_scalars
  s.loc['Volatility (Ann.) [%]'] = np.sqrt((day_returns.var(ddof=int(bool(day_returns.shape))) + (1 + gmean_day_return)**2)**annual_trading_days - (1 + gmean_day_return)**(2*annual_trading_days)) * 100  # noqa: E501
Start                     2022-12-29 00:00:00
End                       2022-12-31 23:59:00
Duration                      2 days 23:59:00
Exposure Time [%]                   16.848204
Equity Final [$]          5695611534104763...
Equity Peak [$]           5695611534104763...
Return [%]                3797074356069842...
Buy & Hold Return [%]               -0.080404
Return (Ann.) [%]                         inf
Volatility (Ann.) [%]                     NaN
Sharpe Ratio                              NaN
Sortino Ratio                             inf
Calmar Ratio                              inf
Max. Drawdown [%]                   -1.145696
Avg. Drawdown [%]                    -1.06802
Max. Drawdown Duration        0 days 00:29:00
Avg. Drawdown Duration        0 days 00:23:00
# Trades                                  727
Win Rate [%]                        99.449794
Best Trade [%]                       2.146799
Worst Trade [%]                     -0.286424
Avg. Trade [%]                       1.768782
Max. Trade Duration           0 days 00:00:00
Avg. Trade Duration           0 days 00:00:00
Profit Factor                     1205.088251
Expectancy [%]                       1.768901
SQN                                  5.505598
_strategy                           MyStrategy
_equity_curve                             ...
_trades                                   ...
dtype: object

[pazooki]

also welcoming any other improvements you suggest

[pazooki]

And this is how the chart looks like:
https://imgur.com/y5EGXMN

[pazooki]

bt = Backtest(
    df['2022-12-29':'2022-12-31'], 
    MyStrategy, 
    cash=15.0, commission=.0026, margin=0.25, 
    hedging=False, exclusive_orders=True, trade_on_close=True
)
stat = bt.run()

[masafumimori]

how about looking into trades history?

stat = bt.run()
stat._trades # This will show all the trades executed