TEST Simple

.gitignore

@@ -1,3 +1,5 @@
 .idea/
- __pycache__/
+__pycache__/
 Save/
+**/__pycache__/
+

Simple.py

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+# Zeus Strategy: First Generation of GodStra Strategy with maximum
+# AVG/MID profit in USDT
+# Author: @Mablue (Masoud Azizi)
+# github: https://github.com/mablue/
+# IMPORTANT: INSTALL TA BEFOUR RUN(pip install ta)
+# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --spaces buy sell roi --strategy Zeus
+# --- Do not remove these libs ---
+from datetime import timedelta, datetime
+from freqtrade.persistence import Trade
+from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter, stoploss_from_open,
+                                IntParameter, IStrategy, merge_informative_pair, informative, stoploss_from_absolute)
+import pandas as pd
+import numpy as np
+from pandas import DataFrame
+from typing import Optional, Union, Tuple
+from typing import List
+
+import logging
+import configparser
+from technical import pivots_points
+# --------------------------------
+
+# Add your lib to import here test git
+import ta
+import talib.abstract as talib
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+import requests
+from datetime import timezone, timedelta
+from scipy.signal import savgol_filter
+from ta.trend import SMAIndicator, EMAIndicator, MACD, ADXIndicator
+from collections import Counter
+
+logger = logging.getLogger(__name__)
+
+from tabulate import tabulate
+
+# Couleurs ANSI de base
+RED = "\033[31m"
+GREEN = "\033[32m"
+YELLOW = "\033[33m"
+BLUE = "\033[34m"
+MAGENTA = "\033[35m"
+CYAN = "\033[36m"
+RESET = "\033[0m"
+
+
+def pprint_df(dframe):
+    print(tabulate(dframe, headers='keys', tablefmt='psql', showindex=False))
+
+
+def normalize(df):
+    df = (df - df.min()) / (df.max() - df.min())
+    return df
+
+"""
+SMA z-score derivative strategy with trailing exit (large).
+- timeframe: 1h
+- sma5, relative derivatives, z-score normalization (rolling z over z_window)
+- smoothing: ewm(span=5) on z-scores
+- entry: z_d1_smooth > entry_z1 AND z_d2_smooth > entry_z2
+- exit: inversion (z_d1_smooth < 0) AND retrace from highest since entry >= trailing_stop
+"""
+class Simple(IStrategy):
+    levels = [1, 2, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]
+    startup_candle_count = 12 * 24 * 2
+
+    # ROI table:
+    minimal_roi = {
+        "0": 10
+    }
+    stakes = 40
+
+    # Stoploss:
+    stoploss = -1  # 0.256
+    # Custom stoploss
+    use_custom_stoploss = True
+
+    # Buy hypers
+    timeframe = '1h'
+
+    max_open_trades = 5
+    max_amount = 40
+
+    # DCA config
+    position_adjustment_enable = True
+
+    # Parameters (tweakable)
+    z_window = 50  # window for rolling mean/std to compute zscore
+    entry_z1 = 0.1  # threshold on z-score of first derivative
+    entry_z2 = 0.1  # threshold on z-score of second derivative
+    min_volume = 0.0  # minimal volume to accept an entry
+    min_relative_d1 = 1e-6  # clip tiny d1 relative values to reduce noise
+
+    # Trailing parameters for "large" trailing requested
+    trailing_stop_pct = 0.05  # 5% retracement from highest since entry
+
+    # Smoothing for z-scores
+    ewm_span = 5
+
+    # Plot config: price + sma5 + markers + slope/accel subplots
+    plot_config = {
+        "main_plot": {
+            "close": {"color": "blue"},
+            "sma5": {"color": "orange"},
+        },
+        "subplots": {
+            "slope_and_accel": {
+                "z_d1": {"color": "green"},
+                "z_d2": {"color": "red"},
+            }
+        },
+        # Markers (Freqtrade charting supports markers via these keys)
+        "markers": [
+            # buy marker: '^' green when enter_long==1
+            {"type": "buy", "column": "enter_long", "marker": "^", "color": "green", "markersize": 10},
+            # sell marker: 'v' red when exit_long==1
+            {"type": "sell", "column": "exit_long", "marker": "v", "color": "red", "markersize": 10},
+        ],
+    }
+
+    def informative_pairs(self):
+        return []
+
+    def _zscore(self, series: pd.Series, window: int) -> pd.Series:
+        mean = series.rolling(window=window, min_periods=3).mean()
+        std = series.rolling(window=window, min_periods=3).std(ddof=0)
+        z = (series - mean) / std
+        z = z.replace([np.inf, -np.inf], np.nan)
+        return z
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        df = dataframe
+
+        # SMA(5)
+        df['sma5'] = df['close'].rolling(5, min_periods=1).mean()
+
+        # Absolute derivatives
+        df['sma5_d1'] = df['sma5'].diff().rolling(5).mean()
+        df['sma5_d2'] = df['sma5_d1'].diff().rolling(5).mean()
+
+        # Relative derivatives (percentage-like)
+        eps = 1e-9
+        df['sma5_d1_rel'] = df['sma5_d1'] / (df['sma5'].shift(1).replace(0, np.nan) + eps)
+        df['sma5_d2_rel'] = df['sma5_d2'] / (df['sma5'].shift(2).replace(0, np.nan) + eps)
+
+        # Clip micro-noise
+        df.loc[df['sma5_d1_rel'].abs() < self.min_relative_d1, 'sma5_d1_rel'] = 0.0
+        df.loc[df['sma5_d2_rel'].abs() < self.min_relative_d1, 'sma5_d2_rel'] = 0.0
+
+        # Z-scores on relative derivatives
+        df['z_d1'] = self._zscore(df['sma5_d1_rel'], self.z_window)
+        df['z_d2'] = self._zscore(df['sma5_d2_rel'], self.z_window)
+
+        # Smoothing z-scores with EWM to reduce jitter
+        df['z_d1_smooth'] = df['z_d1'].ewm(span=self.ewm_span, adjust=False).mean()
+        df['z_d2_smooth'] = df['z_d2'].ewm(span=self.ewm_span, adjust=False).mean()
+
+        # Prepare marker columns (for plots). They will be filled in populate_entry_trend/populate_exit_trend
+        df['enter_long'] = 0
+        df['exit_long'] = 0
+
+        return df
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        df = dataframe.copy()
+
+        # Use last closed candle for signals -> shift(1)
+        cond_entry = (
+                (df['z_d1'] > self.entry_z1) &
+                (df['z_d2'] > self.entry_z2) &
+                (df['volume'].shift(1) > self.min_volume)
+        )
+
+        df.loc[cond_entry, 'enter_long'] = 1
+        # Ensure others are explicitly zero (for clean plotting)
+        df.loc[~cond_entry, 'enter_long'] = 0
+
+        return df
+
+    def custom_exit(self, pair: str, trade: Trade, current_time, current_rate, current_profit, **kwargs) -> \
+    Optional[str]:
+        """
+        Exit policy (mode C - trailing large):
+        - Must detect inversion: z_d1_smooth < 0 on last closed candle
+        - Compute highest close since trade entry (inclusive)
+        - If price has retraced >= trailing_stop_pct from that highest point and we're in inversion -> exit
+        """
+
+        df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last = df.iloc[-1].squeeze()
+
+        z1 = last.get('z_d1_smooth', None)
+        if z1 is None:
+            return None
+
+        # Only consider exits when inversion detected (z1 < 0)
+        inversion = (z1 < 0)
+
+        if not inversion:
+            return None
+
+        # If we don't have profit info, be conservative
+        if current_profit is None:
+            return None
+
+        # Determine highest close since entry
+        highest_since_entry = None
+        try:
+            # trade.open_date_utc is available: find rows after that timestamp
+            # df.index is expected to be pd.DatetimeIndex in UTC or local; convert safely
+            if hasattr(trade, 'open_date_utc') and trade.open_date_utc:
+                # pandas comparison: ensure same tz awareness
+                entry_time = pd.to_datetime(trade.open_date_utc)
+                # select rows with index >= entry_time
+                mask = df.index >= entry_time
+                if mask.any():
+                    highest_since_entry = df.loc[mask, 'close'].max()
+            # fallback: use trade.open_rate or the max over full df
+        except Exception as e:
+            logger.debug(f"Couldn't compute highest_since_entry from open_date_utc: {e}")
+
+        if highest_since_entry is None:
+            # fallback: use the maximum close in the entire provided dataframe slice
+            highest_since_entry = df['close'].max() if not df['close'].empty else current_rate
+
+        # Calculate retracement ratio from the highest
+        if highest_since_entry and highest_since_entry > 0:
+            retrace = 1.0 - (current_rate / highest_since_entry)
+        else:
+            retrace = 0.0
+
+        # Exit if:
+        # - currently in profit AND
+        # - retracement >= trailing_stop_pct (i.e. price has fallen enough from top since entry) AND
+        # - inversion detected (z1 < 0)
+        if (current_profit > 0) and (retrace >= self.trailing_stop_pct):
+            # Mark the dataframe for plotting (if possible)
+            # Note: freqtrade expects strategies to set exit flags in populate_exit_trend,
+            # but we set exit via custom_exit return reason; plotting will read exit_long if populated.
+            return "zscore"
+
+        # Otherwise, do not exit yet
+        return None
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        For plotting only: mark exit points where our logic would trigger.
+        This is approximate: we mark an exit when z_d1_smooth < 0 and the price has retraced >= trailing_stop_pct
+        based on the available dataframe window (best-effort).
+        """
+        df = dataframe
+        # df['exit_long'] = 0
+        #
+        # # compute highest close since each possible entry (best-effort: use rolling max up to current index)
+        # rolling_max = df['close'].cummax()
+        #
+        # # retracement relative to rolling max
+        # retrace = 1.0 - (df['close'] / rolling_max.replace(0, np.nan))
+        #
+        # # mark exits where inversion and retrace >= threshold
+        # cond_exit = (df['z_d1_smooth'] < 0) & (retrace >= self.trailing_stop_pct)
+        # # shift by 0: we mark the candle where the exit condition appears
+        # df.loc[cond_exit, 'exit_long'] = 1
+
+        return df

Simple_01.py

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+# sma_zscore_trailing_dca.py
+from freqtrade.strategy.interface import IStrategy
+from freqtrade.persistence import Trade
+from pandas import DataFrame
+import pandas as pd
+import numpy as np
+from typing import Optional
+import logging
+from datetime import timedelta, datetime
+import talib.abstract as talib
+
+logger = logging.getLogger(__name__)
+
+class Simple_01(IStrategy):
+    """
+    SMA z-score derivative strategy with trailing exit and intelligent DCA (large pullback).
+    - timeframe: 1h
+    - sma5, relative derivatives, z-score normalization (rolling z over z_window)
+    - smoothing: ewm(span=5) on z-scores
+    - entry: z_d1_smooth > entry_z1 AND z_d2_smooth > entry_z2
+    - exit: inversion (z_d1_smooth < 0) AND retrace from highest since entry >= trailing_stop_pct
+    - adjust_trade_position: add to position on controlled pullback (large = 4-6%)
+    """
+
+    timeframe = "1h"
+    startup_candle_count = 24
+    # Risk mgmt (we handle exit in custom_exit)
+    minimal_roi = {"0": 0.99}
+    stoploss = -0.99
+    use_custom_exit = True
+    position_adjustment_enable = True
+
+    columns_logged = False
+
+    # Parameters
+    z_window = 10              # window for rolling mean/std to compute zscore
+    entry_z1 = 0.1             # threshold on z-score of first derivative
+    entry_z2 = 0               # threshold on z-score of second derivative
+    min_volume = 0.0           # minimal volume to accept an entry
+    min_relative_d1 = 1e-6     # clip tiny d1 relative values to reduce noise
+
+    # Trailing parameters for "large" trailing (exit)
+    trailing_stop_pct = 0.01   # 5% retracement from highest since entry
+
+    # Smoothing for z-scores
+    ewm_span = 5
+
+    # DCA intelligent (adjust_trade_position) parameters for "large" pullback
+    dca_enabled = True
+    # Pullback bounds (large): allow adding when retrace is between 4% and 6%
+    dca_pullback_min = 0.01
+    dca_pullback_max = 0.02
+    # Maximum number of adds per trade (to avoid infinite pyramiding)
+    dca_max_adds = 8
+    # Percentage of base position to add on each reinforcement (50% of original size by default)
+    dca_add_ratio = 0.5
+    # Require momentum still positive to add
+    dca_require_z1_positive = True
+    dca_require_z2_positive = True
+    # Do not add if current_profit < min_profit_to_add (avoid averaging down when deep in loss)
+    min_profit_to_add = -0.02  # allow small loss but not big drawdown
+
+    pairs = {
+        pair: {
+            "first_buy": 0,
+            "last_buy": 0.0,
+            "first_amount": 0.0,
+            "last_min": 999999999999999.5,
+            "last_max": 0,
+            "trade_info": {},
+            "max_touch": 0.0,
+            "last_sell": 0.0,
+            'count_of_buys': 0,
+            'current_profit': 0,
+            'expected_profit': 0,
+            "last_candle": {},
+            "last_trade": None,
+            "last_count_of_buys": 0,
+            'base_stake_amount': 0,
+            'stop_buy': False,
+            'last_date': 0,
+            'stop': False,
+            'max_profit': 0,
+            'last_palier_index': -1,
+            'total_amount': 0,
+            'has_gain': 0,
+            'force_sell': False,
+            'force_buy': False
+        }
+        for pair in ["BTC/USDC", "ETH/USDC", "DOGE/USDC", "XRP/USDC", "SOL/USDC",
+                     "BTC/USDT", "ETH/USDT", "DOGE/USDT", "XRP/USDT", "SOL/USDT"]
+    }
+
+    # Plot config
+    plot_config = {
+        "main_plot": {
+            "close": {"color": "blue"},
+            "sma5": {"color": "orange"},
+        },
+        "subplots": {
+            "slope_and_accel": {
+                "z_d1_smooth": {"color": "green"},
+                "z_d2_smooth": {"color": "red"},
+            },
+            "sma_deriv": {
+                "sma5_deriv1_rel": {"color": "green"},
+                "sma5_deriv2_rel": {"color": "red"},
+            },
+            "rsi": {
+                "rsi": {"color": "blue"}
+            }
+
+        },
+        "markers": [
+            {"type": "buy", "column": "enter_long", "marker": "^", "color": "green", "markersize": 10},
+            {"type": "sell", "column": "exit_long", "marker": "v", "color": "red", "markersize": 10},
+        ],
+    }
+
+    def informative_pairs(self):
+        return []
+
+    def _zscore(self, series: pd.Series, window: int) -> pd.Series:
+        mean = series.rolling(window=window, min_periods=3).mean()
+        std = series.rolling(window=window, min_periods=3).std(ddof=0)
+        z = (series - mean) / std
+        z = z.replace([np.inf, -np.inf], np.nan)
+        return z
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        df = dataframe
+
+        # SMA(5)
+        df['sma5'] = df['close'].rolling(5, min_periods=1).mean()
+
+        # Absolute derivatives
+        df['sma5_deriv1'] = df['sma5'].diff()
+        df['sma5_deriv2'] = df['sma5_deriv1'].diff()
+
+        # Relative derivatives (percentage-like)
+        eps = 1e-9
+        df['sma5_deriv1_rel'] = df['sma5_deriv1'] / (df['sma5'].shift(1).replace(0, np.nan) + eps)
+        df['sma5_deriv2_rel'] = df['sma5_deriv2'] / (df['sma5'].shift(2).replace(0, np.nan) + eps)
+
+        # Clip micro-noise
+        df.loc[df['sma5_deriv1_rel'].abs() < self.min_relative_d1, 'sma5_deriv1_rel'] = 0.0
+        df.loc[df['sma5_deriv2_rel'].abs() < self.min_relative_d1, 'sma5_deriv2_rel'] = 0.0
+
+        # Z-scores on relative derivatives
+        df['z_d1'] = self._zscore(df['sma5_deriv1_rel'], self.z_window)
+        df['z_d2'] = self._zscore(df['sma5_deriv2_rel'], self.z_window)
+
+        # Smoothing z-scores with EWM to reduce jitter
+        df['z_d1_smooth'] = df['z_d1'].ewm(span=self.ewm_span, adjust=False).mean()
+        df['z_d2_smooth'] = df['z_d2'].ewm(span=self.ewm_span, adjust=False).mean()
+
+        # Prepare marker columns (for plots)
+        df['enter_long'] = 0
+        df['exit_long'] = 0
+        df['rsi'] = talib.RSI(df['close'], timeperiod=14)
+        df['max_rsi_12'] = talib.MAX(df['rsi'], timeperiod=12)
+        df['min_rsi_12'] = talib.MIN(df['rsi'], timeperiod=12)
+        # self.calculeDerivees(df, 'rsi', horizon=12)
+
+        return df
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        df = dataframe
+
+        # Use last closed candle for signals -> shift(1)
+        cond_entry = (
+            (df['z_d1_smooth'] > self.entry_z1) &
+            (df['z_d2_smooth'] > self.entry_z2) &
+            (df['max_rsi_12'] < 70) &
+            (df['volume'] > self.min_volume)
+        )
+
+        df.loc[cond_entry, 'enter_long'] = 1
+        df.loc[~cond_entry, 'enter_long'] = 0
+
+        return df
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        df = dataframe
+        # df['exit_long'] = 0
+        #
+        # # compute rolling max (best-effort for plotting)
+        # rolling_max = df['close'].cummax()
+        # retrace = 1.0 - (df['close'] / rolling_max.replace(0, np.nan))
+        #
+        # cond_exit = (df['z_d1_smooth'] < 0) & (retrace >= self.trailing_stop_pct)
+        # df.loc[cond_exit, 'exit_long'] = 1
+
+        return df
+
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float, rate: float,
+                           time_in_force: str,
+                           exit_reason: str, current_time, **kwargs, ) -> bool:
+        # allow_to_sell = (minutes > 30)
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+
+        force = self.pairs[pair]['force_sell']
+        allow_to_sell = True #(last_candle['percent'] < 0) #or force
+
+        minutes = int(round((current_time - trade.date_last_filled_utc).total_seconds() / 60, 0))
+
+        if allow_to_sell:
+            self.trades = list()
+            self.pairs[pair]['last_count_of_buys'] = trade.nr_of_successful_entries  # self.pairs[pair]['count_of_buys']
+            self.pairs[pair]['last_sell'] = rate
+            self.pairs[pair]['last_trade'] = trade
+            self.pairs[pair]['last_candle'] = last_candle
+            self.trades = list()
+            dispo = round(self.wallets.get_available_stake_amount())
+            print(f"Sell {pair} {current_time} {exit_reason}  dispo={dispo}  amount={amount} rate={rate} open_rate={trade.open_rate}")
+            self.log_trade(
+                last_candle=last_candle,
+                date=current_time,
+                action="🟥Sell " + str(minutes),
+                pair=pair,
+                trade_type=exit_reason,
+                rate=last_candle['close'],
+                dispo=dispo,
+                profit=round(trade.calc_profit(rate, amount), 2)
+            )
+            self.pairs[pair]['max_profit'] = 0
+            self.pairs[pair]['force_sell'] = False
+            self.pairs[pair]['has_gain'] = 0
+            self.pairs[pair]['current_profit'] = 0
+            self.pairs[pair]['total_amount'] = 0
+            self.pairs[pair]['count_of_buys'] = 0
+            self.pairs[pair]['max_touch'] = 0
+            self.pairs[pair]['last_buy'] = 0
+            self.pairs[pair]['last_date'] = current_time
+            self.pairs[pair]['last_palier_index'] = -1
+            self.pairs[pair]['last_trade'] = trade
+            self.pairs[pair]['current_trade'] = None
+
+        return (allow_to_sell) | (exit_reason == 'force_exit')
+
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, time_in_force: str,
+                            current_time: datetime, entry_tag: Optional[str], **kwargs) -> bool:
+
+        minutes = 0
+        if self.pairs[pair]['last_date'] != 0:
+            minutes = round(int((current_time - self.pairs[pair]['last_date']).total_seconds() / 60))
+
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+        last_candle_2 = dataframe.iloc[-2].squeeze()
+        last_candle_3 = dataframe.iloc[-3].squeeze()
+        # val = self.getProbaHausse144(last_candle)
+
+        # allow_to_buy = True #(not self.stop_all) #& (not self.all_down)
+        allow_to_buy = not self.pairs[pair]['stop']  # and val > self.buy_val.value #not last_candle['tendency'] in ('B-', 'B--')  # (rate <= float(limit)) | (entry_tag == 'force_entry')
+
+        # force = self.pairs[pair]['force_buy']
+        # if self.pairs[pair]['force_buy']:
+        #     self.pairs[pair]['force_buy'] = False
+        #     allow_to_buy = True
+        # else:
+        #     if not self.should_enter_trade(pair, last_candle, current_time):
+        #         allow_to_buy = False
+
+        if allow_to_buy:
+            self.trades = list()
+            self.pairs[pair]['first_buy'] = rate
+            self.pairs[pair]['last_buy'] = rate
+            self.pairs[pair]['max_touch'] = last_candle['close']
+            self.pairs[pair]['last_candle'] = last_candle
+            self.pairs[pair]['count_of_buys'] = 1
+            self.pairs[pair]['current_profit'] = 0
+            self.pairs[pair]['last_palier_index'] = -1
+            self.pairs[pair]['last_max'] = max(last_candle['close'], self.pairs[pair]['last_max'])
+            self.pairs[pair]['last_min'] = min(last_candle['close'], self.pairs[pair]['last_min'])
+
+            dispo = round(self.wallets.get_available_stake_amount())
+            self.printLineLog()
+
+            stake_amount = self.adjust_stake_amount(pair, last_candle)
+
+            self.pairs[pair]['total_amount'] = stake_amount
+
+            self.log_trade(
+                last_candle=last_candle,
+                date=current_time,
+                action=("🟩Buy" if allow_to_buy else "Canceled") + " " + str(minutes),
+                pair=pair,
+                rate=rate,
+                dispo=dispo,
+                profit=0,
+                trade_type=entry_tag,
+                buys=1,
+                stake=round(stake_amount, 2)
+            )
+
+        return allow_to_buy
+
+    def custom_exit(self, pair: str, trade: Trade, current_time, current_rate, current_profit, **kwargs) -> Optional[str]:
+        df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = df.iloc[-1].squeeze()
+
+        self.pairs[pair]['last_max'] = max(last_candle['close'], self.pairs[pair]['last_max'])
+        self.pairs[pair]['last_min'] = min(last_candle['close'], self.pairs[pair]['last_min'])
+        self.pairs[pair]['current_trade'] = trade
+        count_of_buys = trade.nr_of_successful_entries
+
+        profit = round(current_profit * trade.stake_amount, 1)
+        self.pairs[pair]['max_profit'] = max(self.pairs[pair]['max_profit'], profit)
+        max_profit = self.pairs[pair]['max_profit']
+        baisse = 0
+        if profit > 0:
+            baisse = 100 * abs(max_profit - profit) / max_profit
+        mx = max_profit / 5
+        self.pairs[pair]['count_of_buys'] = count_of_buys
+        self.pairs[pair]['current_profit'] = profit
+
+        dispo = round(self.wallets.get_available_stake_amount())
+        hours_since_first_buy = (current_time - trade.open_date_utc).seconds / 3600.0
+        days_since_first_buy = (current_time - trade.open_date_utc).days
+        hours = (current_time - trade.date_last_filled_utc).total_seconds() / 3600.0
+
+        if hours % 4 == 0:
+            self.log_trade(
+                last_candle=last_candle,
+                date=current_time,
+                action="🔴 CURRENT" if self.pairs[pair]['stop'] else "🟢 CURRENT",
+                dispo=dispo,
+                pair=pair,
+                rate=last_candle['close'],
+                trade_type='',
+                profit=profit,
+                buys='',
+                stake=0
+            )
+
+        z1 = last_candle.get('z_d1_smooth', None)
+        if z1 is None:
+            return None
+
+        if z1 >= 0:
+            return None
+
+        if current_profit is None:
+            return None
+
+        # highest close since entry
+        highest_since_entry = self.pairs[trade.pair]['max_touch']
+        # try:
+        #     if hasattr(trade, 'open_date_utc') and trade.open_date_utc:
+        #         entry_time = pd.to_datetime(trade.open_date_utc)
+        #         mask = df.index >= entry_time
+        #         if mask.any():
+        #             highest_since_entry = df.loc[mask, 'close'].max()
+        # except Exception as e:
+        #     logger.debug(f"Couldn't compute highest_since_entry: {e}")
+        #
+        # if highest_since_entry is None:
+        #     highest_since_entry = df['close'].max() if not df['close'].empty else current_rate
+
+        if highest_since_entry and highest_since_entry > 0:
+            retrace = 1.0 - (current_rate / highest_since_entry)
+        else:
+            retrace = 0.0
+        z1 = last_candle.get('z_d1_smooth', None)
+        z2 = last_candle.get('z_d2_smooth', None)
+
+        if (current_profit > 0) and (current_profit >= self.trailing_stop_pct) and last_candle['sma5_deriv1'] < -0.002:
+            return str(count_of_buys) + '_' + "zscore"
+
+        self.pairs[pair]['max_touch'] = max(last_candle['close'], self.pairs[pair]['max_touch'])
+
+        return None
+
+    def adjust_stake_amount(self, pair: str, last_candle: DataFrame):
+        # Calculer le minimum des 14 derniers jours
+        return self.config.get('stake_amount')
+
+    def adjust_trade_position(self, trade: Trade, current_time: datetime,
+                              current_rate: float, current_profit: float, min_stake: float,
+                              max_stake: float, **kwargs):
+        """
+        DCA intelligent (mode C - 'large'):
+        - Only add if:
+            * DCA is enabled
+            * number of adds done so far < dca_max_adds
+            * retracement since highest_since_entry is between dca_pullback_min and dca_pullback_max
+            * momentum still positive (z_d1_smooth, z_d2_smooth) if required
+            * current_profit >= min_profit_to_add (avoid averaging down into large loss)
+        - Returns a dict describing the desired order for Freqtrade to place (common format).
+          Example returned dict: {'type': 'market', 'amount': 0.01}
+        """
+        if not self.dca_enabled:
+            return None
+        pair = trade.pair
+
+        # Basic guards
+        if current_profit is None:
+            current_profit = 0.0
+
+        # Do not add if we're already deeply in loss
+        if current_profit < self.min_profit_to_add:
+            return None
+
+        df, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
+        last_candle = df.iloc[-1].squeeze()
+
+        # Compute highest close since entry
+        highest_since_entry = self.pairs[trade.pair]['last_buy']
+
+        last = df.iloc[-1]
+        z1 = last.get('z_d1_smooth', None)
+        z2 = last.get('z_d2_smooth', None)
+
+        # Count how many adds have been done for this trade.
+        # Trade.extra might contain meta; otherwise try trade.tags or use trade.open_rate/amount heuristics.
+        adds_done = trade.nr_of_successful_entries
+        # Calculate retracement since the highest
+        retrace = 0.0
+        if highest_since_entry and highest_since_entry > 0:
+            retrace = (last['close'] - highest_since_entry) / highest_since_entry
+
+        # logger.info(f"{pair} {current_rate} {current_time} {highest_since_entry} add: retrace={retrace:.4f}, adds_done={adds_done} z1={z1} z2={z2}")
+
+        # Enforce momentum requirements if requested
+        if self.dca_require_z1_positive and (z1 is None or z1 <= 0):
+            return None
+        if self.dca_require_z2_positive and (z2 is None or z2 <= 0):
+            return None
+
+        #
+        # try:
+        #     meta = getattr(trade, 'meta', None) or {}
+        #     adds_done = int(meta.get('adds_done', 0))
+        # except Exception:
+        #     adds_done = 0
+
+        if adds_done >= self.dca_max_adds:
+            return None
+
+        # try:
+        #     if hasattr(trade, 'open_date_utc') and trade.open_date_utc:
+        #         entry_time = pd.to_datetime(trade.open_date_utc)
+        #         mask = df.index >= entry_time
+        #         if mask.any():
+        #             highest_since_entry = df.loc[mask, 'close'].max()
+        # except Exception as e:
+        #     logger.debug(f"adjust_trade_position: couldn't compute highest_since_entry: {e}")
+        #
+        # if highest_since_entry is None:
+        #     highest_since_entry = df['close'].max() if not df['close'].empty else current_rate
+
+        # Check if retrace is inside the allowed DCA window (large)
+        if ((retrace >= self.dca_pullback_min) and (retrace <= self.dca_pullback_max)):
+            # Determine amount to add: a fraction of the original trade amount
+            # Try to get trade.amount (base asset amount). If not available, fall back to stake percentage
+            add_amount = None
+            try:
+                base_amount = self.config.get('stake_amount')
+                if base_amount:
+                    add_amount = base_amount * self.dca_add_ratio
+                else:
+                    # Fallback: attempt to compute amount from trade.open_rate and desired quote stake
+                    # We'll propose to use a fraction of current rate worth (this is best-effort)
+                    add_amount = None
+            except Exception:
+                add_amount = None
+
+            # If we couldn't compute an absolute amount, propose a relative size via a suggested stake (user must map)
+            if add_amount is None:
+                # Return a suggested instruction; adapt according to your freqtrade version.
+                suggested = {
+                    'type': 'market',
+                    'amount': None,  # caller should compute actual amount from stake management
+                    'note': f'suggest_add_ratio={self.dca_add_ratio}'
+                }
+                # logger.info(f"{pair} {current_rate} DCA suggestion (no absolute amount): retrace={retrace:.4f}, adds_done={adds_done}")
+                return None
+
+            dispo = round(self.wallets.get_available_stake_amount())
+            trade_type = last_candle['enter_tag'] if last_candle['enter_long'] == 1 else 'pct48'
+            self.pairs[trade.pair]['count_of_buys'] += 1
+            self.pairs[pair]['total_amount'] += add_amount
+            self.log_trade(
+                last_candle=last_candle,
+                date=current_time,
+                action="🟧 Loss -",
+                dispo=dispo,
+                pair=trade.pair,
+                rate=current_rate,
+                trade_type=trade_type,
+                profit=round(current_profit * trade.stake_amount, 1),
+                buys=trade.nr_of_successful_entries + 1,
+                stake=round(add_amount, 2)
+            )
+
+            self.pairs[trade.pair]['last_buy'] = current_rate
+            self.pairs[trade.pair]['max_touch'] = last_candle['close']
+            self.pairs[trade.pair]['last_candle'] = last_candle
+
+            # All checks passed -> create market order instruction
+            # logger.info(f"{pair} {current_rate} {current_time} {highest_since_entry} add: retrace={retrace:.4f}, adds_done={adds_done}, add_amount={add_amount:.8f}")
+            return add_amount
+
+        # Not in allowed retrace window -> no action
+        return None
+
+    def getPctFirstBuy(self, pair, last_candle):
+        return round((last_candle['close'] - self.pairs[pair]['first_buy']) / self.pairs[pair]['first_buy'], 3)
+
+    def getPctLastBuy(self, pair, last_candle):
+        return round((last_candle['close'] - self.pairs[pair]['last_buy']) / self.pairs[pair]['last_buy'], 4)
+
+    def getPct60D(self, pair, last_candle):
+        return round((last_candle['max60'] - last_candle['min60']) / last_candle['max60'], 4)
+
+    def getPctClose60D(self, pair, last_candle):
+        if last_candle['close'] > last_candle['max12']:
+            return 1
+        if last_candle['close'] < last_candle['min12']:
+            return 0
+        return round(
+            (last_candle['close'] - last_candle['min12']) / (last_candle['max12'] - last_candle['min12']), 4)
+
+
+    def printLineLog(self):
+        self.printLog(
+            f"+{'-' * 18}+{'-' * 12}+{'-' * 5}+{'-' * 20}+{'-' * 9}+{'-' * 8}+{'-' * 12}+{'-' * 8}+{'-' * 13}+{'-' * 14}+{'-' * 9}{'-' * 9}+{'-' * 5}+{'-' * 7}+"
+            f"{'-' * 3}"
+            # "+{'-' * 3}+{'-' * 3}
+            f"+{'-' * 6}+{'-' * 7}+{'-' * 5}+{'-' * 5}+{'-' * 5}+{'-' * 5}+{'-' * 5}+{'-' * 5}+"
+        )
+
+    def printLog(self, str):
+        if self.config.get('runmode') == 'hyperopt' or self.dp.runmode.value in ('hyperopt'):
+            return
+        if not self.dp.runmode.value in ('backtest', 'hyperopt', 'lookahead-analysis'):
+            logger.info(str)
+        else:
+            if not self.dp.runmode.value in ('hyperopt'):
+                print(str)
+
+    def log_trade(self, action, pair, date, trade_type=None, rate=None, dispo=None, profit=None, buys=None,
+                  stake=None,
+                  last_candle=None):
+        # Couleurs ANSI de base
+        RED = "\033[31m"
+        GREEN = "\033[32m"
+        YELLOW = "\033[33m"
+        BLUE = "\033[34m"
+        MAGENTA = "\033[35m"
+        CYAN = "\033[36m"
+        RESET = "\033[0m"
+
+        # Afficher les colonnes une seule fois
+        if self.config.get('runmode') == 'hyperopt' or self.dp.runmode.value in ('hyperopt'):
+            return
+        if self.columns_logged % 10 == 0:
+            self.printLog(
+                f"| {'Date':<16} | {'Action':<10} |{'Pair':<5}| {'Trade Type':<18} |{'Rate':>8} | {'Dispo':>6} | {'Profit':>8} | {'Pct':>6} | {'max_touch':>11} | {'last_lost':>12} | {'last_max':>7}| {'last_max':>7}|{'Buys':>5}| {'Stake':>5} |"
+                f"Tdc|{'val':>6}|  RSI  |s201d|s5_1d|s5_2d|s51h|s52h"
+            )
+            self.printLineLog()
+            df = pd.DataFrame.from_dict(self.pairs, orient='index')
+            colonnes_a_exclure = ['last_candle', 'last_trade', 'last_palier_index',
+                                  'trade_info', 'last_date', 'expected_profit', 'last_count_of_buys',
+                                  'base_stake_amount', 'stop_buy']
+            df_filtered = df[df['count_of_buys'] > 0].drop(columns=colonnes_a_exclure)
+            # df_filtered = df_filtered["first_buy", "last_max", "max_touch", "last_sell","last_buy", 'count_of_buys', 'current_profit']
+
+            print(df_filtered)
+
+        self.columns_logged += 1
+        date = str(date)[:16] if date else "-"
+        limit = None
+        # if buys is not None:
+        #     limit = round(last_rate * (1 - self.fibo[buys] / 100), 4)
+
+        rsi = ''
+        rsi_pct = ''
+        sma5_1d = ''
+        sma5_1h = ''
+
+        sma5 = str(sma5_1d) + ' ' + str(sma5_1h)
+
+        last_lost = '' #self.getLastLost(last_candle, pair)
+
+        if buys is None:
+            buys = ''
+
+        max_touch = ''  # round(last_candle['max12'], 1) #round(self.pairs[pair]['max_touch'], 1)
+        pct_max = '' #self.getPctFirstBuy(pair, last_candle)
+
+        total_counts = str(buys) + '/' + str(
+            sum(pair_data['count_of_buys'] for pair_data in self.pairs.values()))
+
+        dist_max = '' #self.getDistMax(last_candle, pair)
+        val = 0 #self.getProbaHausseSma5d(last_candle)
+
+        pct60 = 0 #round(100 * self.getPct60D(pair, last_candle), 2)
+
+        color = GREEN if profit > 0 else RED
+        # color_sma20 = GREEN if last_candle['sma20_deriv1'] > 0 else RED
+        # color_sma5 = GREEN if last_candle['mid_smooth_5_deriv1'] > 0 else RED
+        # color_sma5_2 = GREEN if last_candle['mid_smooth_5_deriv2'] > 0 else RED
+        # color_sma5_1h = GREEN if last_candle['sma5_deriveriv1'] > 0 else RED
+        # color_sma5_2h = GREEN if last_candle['sma5_deriveriv2'] > 0 else RED
+
+        last_max = int(self.pairs[pair]['last_max']) if self.pairs[pair]['last_max'] > 1 else round(
+            self.pairs[pair]['last_max'], 3)
+        last_min = int(self.pairs[pair]['last_min']) if self.pairs[pair]['last_min'] > 1 else round(
+            self.pairs[pair]['last_min'], 3)
+
+        profit = str(profit) + '/' + str(round(self.pairs[pair]['max_profit'], 2))
+
+        #     🟢 Dérivée 1 > 0 et dérivée 2 > 0: tendance haussière qui s’accélère.
+        #     🟡 Dérivée 1 > 0 et dérivée 2 < 0: tendance haussière qui ralentit → essoufflement potentiel.
+        #     🔴 Dérivée 1 < 0 et dérivée 2 < 0: tendance baissière qui s’accélère.
+        #     🟠 Dérivée 1 < 0 et dérivée 2 > 0: tendance baissière qui ralentit → possible bottom.
+
+        # tdc last_candle['tendency_12']
+        self.printLog(
+            f"| {date:<16} |{action:<10} | {pair[0:3]:<3} | {trade_type or '-':<18} |{rate or '-':>9}| {dispo or '-':>6} "
+            f"|{color}{profit or '-':>10}{RESET}| {pct_max or '-':>6} | {round(self.pairs[pair]['max_touch'], 2) or '-':>11} | {last_lost or '-':>12} "
+            f"| {last_max or '-':>7} | {last_min or '-':>7} |{total_counts or '-':>5}|{stake or '-':>7}"
+            f"|{'-':>3}|"
+            f"{round(val, 1) or '-' :>6}|"
+            # f"{round(last_candle['rsi'], 0):>7}|{color_sma20}{round(last_candle['sma20_deriv1'], 2):>5}{RESET}"
+            # f"|{color_sma5}{round(last_candle['mid_smooth_5_deriv1'], 2):>5}{RESET}|{color_sma5_2}{round(last_candle['mid_smooth_5_deriv2'], 2):>5}{RESET}"
+            # f"|{color_sma5_1h}{round(last_candle['sma5_deriveriv1'], 2):>5}{RESET}|{color_sma5_2h}{round(last_candle['sma5_deriveriv2'], 2):>5}{RESET}"
+            # f"|{last_candle['min60']}|{last_candle['max60']}"
+        )

Zeus_8_1d_Bilan.txt

@@ -0,0 +1,376 @@
+                                                BACKTESTING REPORT
+┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
+┃      Pair ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃      Avg Duration ┃  Win  Draw  Loss  Win% ┃
+┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
+│ DOGE/USDT │     20 │         6.58 │         234.716 │         7.82 │ 12 days, 21:54:00 │   20     0     0   100 │
+│  XRP/USDT │     29 │         4.96 │         198.511 │         6.62 │  8 days, 17:43:00 │   28     0     1  96.6 │
+│  SOL/USDT │     23 │         4.96 │         159.580 │         5.32 │  11 days, 1:29:00 │   22     0     1  95.7 │
+│  ETH/USDT │     26 │         4.12 │         155.679 │         5.19 │  9 days, 20:48:00 │   26     0     0   100 │
+│  BTC/USDT │     23 │         2.57 │          76.047 │         2.53 │ 10 days, 23:47:00 │   22     0     1  95.7 │
+│     TOTAL │    121 │         4.59 │         824.533 │        27.48 │ 10 days, 12:59:00 │  118     0     3  97.5 │
+└───────────┴────────┴──────────────┴─────────────────┴──────────────┴───────────────────┴────────────────────────┘
+                                             LEFT OPEN TRADES REPORT
+┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
+┃      Pair ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃     Avg Duration ┃  Win  Draw  Loss  Win% ┃
+┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
+│  ETH/USDT │      1 │         3.07 │           1.533 │         0.05 │  2 days, 6:00:00 │    1     0     0   100 │
+│ DOGE/USDT │      1 │         0.47 │           0.741 │         0.02 │  2 days, 5:00:00 │    1     0     0   100 │
+│  BTC/USDT │      1 │        -0.13 │          -0.065 │         -0.0 │  2 days, 7:00:00 │    0     0     1     0 │
+│  SOL/USDT │      1 │        -1.47 │          -0.917 │        -0.03 │         19:00:00 │    0     0     1     0 │
+│  XRP/USDT │      1 │        -4.64 │         -11.192 │        -0.37 │ 54 days, 8:00:00 │    0     0     1     0 │
+│     TOTAL │      5 │        -0.54 │          -9.899 │        -0.33 │ 12 days, 9:00:00 │    2     0     3  40.0 │
+└───────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┘
+                                                  ENTER TAG STATS
+┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
+┃ Enter Tag ┃ Entries ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃      Avg Duration ┃  Win  Draw  Loss  Win% ┃
+┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
+│   smth_12 │     121 │         4.59 │         824.533 │        27.48 │ 10 days, 12:59:00 │  118     0     3  97.5 │
+│     TOTAL │     121 │         4.59 │         824.533 │        27.48 │ 10 days, 12:59:00 │  118     0     3  97.5 │
+└───────────┴─────────┴──────────────┴─────────────────┴──────────────┴───────────────────┴────────────────────────┘
+                                                      EXIT REASON STATS
+┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
+┃         Exit Reason ┃ Exits ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃       Avg Duration ┃  Win  Draw  Loss  Win% ┃
+┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
+│   RSI_XRP_5_0_28.43 │     1 │        15.15 │          71.078 │         2.37 │   15 days, 4:00:00 │    1     0     0   100 │
+│  Drv3_ETH_8_0_34.72 │     1 │         6.36 │          53.262 │         1.78 │ 125 days, 19:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_6_0_46.32 │     1 │        10.45 │          52.528 │         1.75 │  47 days, 13:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_3_0_26.01 │     1 │        21.51 │          34.730 │         1.16 │    6 days, 1:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_3_0_39.61 │     1 │        14.32 │          34.062 │         1.14 │  11 days, 21:00:00 │    1     0     0   100 │
+│  Drv3_ETH_3_0_14.24 │     1 │        15.48 │          26.538 │         0.88 │  11 days, 17:00:00 │    1     0     0   100 │
+│   Drv3_SOL_2_0_9.03 │     1 │        17.25 │          26.223 │         0.87 │    8 days, 1:00:00 │    1     0     0   100 │
+│  Drv3_XRP_4_0_19.78 │     1 │         9.64 │          21.919 │         0.73 │   9 days, 10:00:00 │    1     0     0   100 │
+│  Drv3_SOL_3_0_31.46 │     1 │        10.39 │          20.674 │         0.69 │   8 days, 13:00:00 │    1     0     0   100 │
+│  Drv3_SOL_4_0_24.35 │     1 │         6.46 │          20.553 │         0.69 │   13 days, 8:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_4_0_29.59 │     1 │         6.68 │          18.794 │         0.63 │  16 days, 21:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_2_0_23.33 │     1 │        17.89 │          18.435 │         0.61 │   3 days, 20:00:00 │    1     0     0   100 │
+│  Drv3_XRP_4_0_34.21 │     1 │         7.03 │          17.503 │         0.58 │   12 days, 1:00:00 │    1     0     0   100 │
+│  Drv3_ETH_3_0_18.45 │     1 │        10.19 │          16.852 │         0.56 │    7 days, 0:00:00 │    1     0     0   100 │
+│  Drv3_BTC_8_0_37.83 │     1 │         3.12 │          16.616 │         0.55 │  79 days, 11:00:00 │    1     0     0   100 │
+│  Drv3_BTC_4_0_12.14 │     1 │         6.86 │          15.212 │         0.51 │  16 days, 15:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_1_0_19.08 │     1 │        18.77 │          14.063 │         0.47 │   4 days, 11:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_20.83 │     1 │        26.55 │          13.279 │         0.44 │   3 days, 16:00:00 │    1     0     0   100 │
+│  Drv3_ETH_3_0_19.63 │     1 │         7.04 │          13.133 │         0.44 │   14 days, 0:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_3_0_25.43 │     1 │         6.43 │          12.901 │         0.43 │  12 days, 17:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_1_0_27.27 │     1 │        12.06 │          12.054 │          0.4 │    2 days, 6:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_67.31 │     1 │        11.51 │          11.807 │         0.39 │   3 days, 13:00:00 │    1     0     0   100 │
+│  Drv3_XRP_3_0_43.54 │     1 │         5.33 │          11.803 │         0.39 │  46 days, 10:00:00 │    1     0     0   100 │
+│  Drv3_SOL_1_0_11.11 │     1 │        12.28 │          11.253 │         0.38 │   3 days, 16:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_4_0_54.81 │     1 │         4.36 │          10.812 │         0.36 │  13 days, 15:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_34.78 │     1 │        16.81 │          10.484 │         0.35 │   2 days, 20:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_3_0_26.24 │     1 │          6.2 │          10.401 │         0.35 │   7 days, 23:00:00 │    1     0     0   100 │
+│    RSI_ETH_1_0_8.93 │     1 │        20.52 │          10.253 │         0.34 │   4 days, 22:00:00 │    1     0     0   100 │
+│  Drv3_XRP_3_0_32.89 │     1 │         6.37 │          10.247 │         0.34 │   6 days, 18:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_28.89 │     1 │         9.34 │           9.561 │         0.32 │   5 days, 14:00:00 │    1     0     0   100 │
+│   RSI_SOL_4_0_40.62 │     1 │         2.98 │           9.471 │         0.32 │  10 days, 23:00:00 │    1     0     0   100 │
+│  Drv3_XRP_3_0_69.84 │     1 │         2.64 │           9.241 │         0.31 │   3 days, 14:00:00 │    1     0     0   100 │
+│  Drv3_SOL_3_0_60.36 │     1 │         4.38 │           8.823 │         0.29 │   7 days, 10:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_47.83 │     1 │         8.04 │           8.420 │         0.28 │   3 days, 23:00:00 │    1     0     0   100 │
+│    RSI_XRP_1_0_9.78 │     1 │        13.26 │           8.291 │         0.28 │    1 day, 10:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_33.33 │     1 │        15.27 │           7.630 │         0.25 │   3 days, 20:00:00 │    1     0     0   100 │
+│  Drv3_ETH_1_0_12.35 │     1 │        14.27 │           7.136 │         0.24 │   3 days, 22:00:00 │    1     0     0   100 │
+│  Drv3_SOL_1_0_39.42 │     1 │        10.17 │           6.354 │         0.21 │   3 days, 15:00:00 │    1     0     0   100 │
+│  Drv3_BTC_4_0_17.57 │     1 │         2.59 │           6.081 │          0.2 │  15 days, 18:00:00 │    1     0     0   100 │
+│  Drv3_BTC_2_0_18.06 │     1 │         5.89 │           5.956 │          0.2 │   9 days, 11:00:00 │    1     0     0   100 │
+│  Drv3_BTC_1_0_17.14 │     1 │         9.45 │           5.834 │         0.19 │    8 days, 2:00:00 │    1     0     0   100 │
+│  Drv3_SOL_8_0_81.16 │     1 │         0.73 │           5.508 │         0.18 │ 107 days, 19:00:00 │    1     0     0   100 │
+│   RSI_BTC_5_0_31.25 │     1 │         1.93 │           5.464 │         0.18 │  17 days, 20:00:00 │    1     0     0   100 │
+│  Drv3_BTC_6_0_30.26 │     1 │         1.51 │           5.343 │         0.18 │  31 days, 22:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_4_0_83.45 │     1 │         1.65 │           4.730 │         0.16 │   11 days, 6:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_26.98 │     1 │          9.3 │           4.588 │         0.15 │   4 days, 12:00:00 │    1     0     0   100 │
+│   Drv3_SOL_1_0_25.0 │     1 │         7.26 │           4.538 │         0.15 │    3 days, 7:00:00 │    1     0     0   100 │
+│   Drv3_BTC_1_0_20.0 │     1 │         8.86 │           4.432 │         0.15 │   5 days, 22:00:00 │    1     0     0   100 │
+│  Drv3_XRP_5_0_68.35 │     1 │         1.23 │           4.368 │         0.15 │  55 days, 19:00:00 │    1     0     0   100 │
+│  Drv3_BTC_1_0_10.64 │     1 │         8.42 │           4.189 │         0.14 │   6 days, 23:00:00 │    1     0     0   100 │
+│  Drv3_ETH_3_0_60.19 │     1 │         2.61 │           4.110 │         0.14 │    4 days, 3:00:00 │    1     0     0   100 │
+│   RSI_ETH_3_0_38.98 │     1 │          2.1 │           3.591 │         0.12 │   12 days, 8:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_1_0_27.66 │     1 │         5.48 │           3.425 │         0.11 │   2 days, 16:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_43.86 │     1 │         2.49 │           3.220 │         0.11 │    4 days, 1:00:00 │    1     0     0   100 │
+│  Drv3_ETH_1_0_40.74 │     1 │         5.16 │           3.215 │         0.11 │    2 days, 2:00:00 │    1     0     0   100 │
+│  Drv3_SOL_1_0_50.77 │     1 │         5.12 │           3.201 │         0.11 │   2 days, 12:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_7_0_96.68 │     1 │         0.29 │           3.008 │          0.1 │  110 days, 6:00:00 │    1     0     0   100 │
+│  Drv3_SOL_5_0_82.93 │     1 │         0.66 │           2.808 │         0.09 │  38 days, 21:00:00 │    1     0     0   100 │
+│  Drv3_XRP_3_0_74.07 │     1 │         1.13 │           2.788 │         0.09 │   6 days, 14:00:00 │    1     0     0   100 │
+│   Drv3_XRP_3_0_77.5 │     1 │         1.35 │           2.745 │         0.09 │   2 days, 16:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_57.63 │     1 │         2.33 │           2.489 │         0.08 │    5 days, 9:00:00 │    1     0     0   100 │
+│  Drv3_XRP_3_0_46.67 │     1 │         1.18 │           2.404 │         0.08 │   4 days, 10:00:00 │    1     0     0   100 │
+│   Drv3_XRP_1_0_54.0 │     1 │         4.34 │           2.338 │         0.08 │    3 days, 3:00:00 │    1     0     0   100 │
+│  Drv3_SOL_4_0_76.04 │     1 │         0.96 │           2.254 │         0.08 │  13 days, 17:00:00 │    1     0     0   100 │
+│   Drv3_BTC_1_0_56.0 │     1 │         3.55 │           2.217 │         0.07 │   6 days, 15:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_45.95 │     1 │         3.99 │           1.993 │         0.07 │     1 day, 5:00:00 │    1     0     0   100 │
+│   RSI_ETH_1_0_16.67 │     1 │         3.97 │           1.977 │         0.07 │           14:00:00 │    1     0     0   100 │
+│  Drv3_ETH_1_0_26.09 │     1 │          2.8 │           1.746 │         0.06 │   2 days, 10:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_71.93 │     1 │         1.52 │           1.583 │         0.05 │   2 days, 11:00:00 │    1     0     0   100 │
+│  Drv3_ETH_1_0_11.11 │     1 │         3.14 │           1.565 │         0.05 │    2 days, 8:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_3_0_27.27 │     1 │         0.85 │           1.557 │         0.05 │           12:00:00 │    1     0     0   100 │
+│  Drv3_ETH_4_0_79.73 │     1 │         0.65 │           1.509 │         0.05 │   6 days, 20:00:00 │    1     0     0   100 │
+│  Drv3_ETH_2_0_76.56 │     1 │         1.15 │           1.466 │         0.05 │    3 days, 6:00:00 │    1     0     0   100 │
+│   Drv3_ETH_1_0_75.0 │     1 │         1.75 │           1.314 │         0.04 │   3 days, 14:00:00 │    1     0     0   100 │
+│  Drv3_ETH_3_0_73.47 │     1 │         0.76 │           1.289 │         0.04 │   20 days, 8:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_27.78 │     1 │         1.27 │           1.268 │         0.04 │            6:00:00 │    1     0     0   100 │
+│  Drv3_XRP_2_0_33.33 │     1 │         0.95 │           1.203 │         0.04 │     1 day, 1:00:00 │    1     0     0   100 │
+│  Drv3_XRP_2_0_83.58 │     1 │         1.12 │           1.148 │         0.04 │    1 day, 16:00:00 │    1     0     0   100 │
+│  Drv3_ETH_1_0_54.17 │     1 │         2.19 │           1.097 │         0.04 │    1 day, 15:00:00 │    1     0     0   100 │
+│  Drv3_BTC_2_0_44.44 │     1 │         0.79 │           1.033 │         0.03 │    9 days, 6:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_1_0_77.78 │     1 │          2.0 │           0.999 │         0.03 │    1 day, 16:00:00 │    1     0     0   100 │
+│  Drv3_BTC_1_0_41.18 │     1 │         1.93 │           0.964 │         0.03 │    5 days, 6:00:00 │    1     0     0   100 │
+│  Drv3_ETH_3_0_85.94 │     1 │         0.48 │           0.944 │         0.03 │  14 days, 16:00:00 │    1     0     0   100 │
+│   Drv3_XRP_3_0_12.5 │     1 │         0.45 │           0.712 │         0.02 │     1 day, 1:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_81.58 │     1 │         1.12 │           0.697 │         0.02 │    2 days, 7:00:00 │    1     0     0   100 │
+│  Drv3_DOGE_1_0_30.0 │     1 │          1.1 │           0.688 │         0.02 │           10:00:00 │    1     0     0   100 │
+│   Drv3_ETH_3_0_30.0 │     1 │         0.42 │           0.669 │         0.02 │     1 day, 6:00:00 │    1     0     0   100 │
+│    Drv3_ETH_1_0_0.0 │     1 │         1.07 │           0.666 │         0.02 │            4:00:00 │    1     0     0   100 │
+│  Drv3_ETH_2_0_72.73 │     1 │         0.62 │           0.631 │         0.02 │    1 day, 20:00:00 │    1     0     0   100 │
+│   Drv3_XRP_2_0_25.0 │     1 │          0.6 │           0.614 │         0.02 │           13:00:00 │    1     0     0   100 │
+│  Drv3_ETH_2_0_66.67 │     1 │         0.59 │           0.607 │         0.02 │   4 days, 22:00:00 │    1     0     0   100 │
+│ Drv3_DOGE_1_0_57.14 │     2 │         0.38 │           0.590 │         0.02 │            8:00:00 │    2     0     0   100 │
+│  Drv3_SOL_2_0_64.71 │     1 │         0.57 │           0.588 │         0.02 │    1 day, 12:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_94.95 │     1 │         0.36 │           0.548 │         0.02 │    2 days, 5:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_28.57 │     1 │         0.87 │           0.545 │         0.02 │            3:00:00 │    1     0     0   100 │
+│  Drv3_SOL_2_0_28.57 │     1 │         0.49 │           0.506 │         0.02 │     1 day, 5:00:00 │    1     0     0   100 │
+│   Drv3_BTC_2_0_37.5 │     1 │         0.45 │           0.489 │         0.02 │    3 days, 2:00:00 │    1     0     0   100 │
+│  Drv3_BTC_1_0_73.68 │     1 │         0.94 │           0.466 │         0.02 │   2 days, 18:00:00 │    1     0     0   100 │
+│  Drv3_BTC_2_0_76.47 │     1 │         0.38 │           0.397 │         0.01 │   15 days, 3:00:00 │    1     0     0   100 │
+│  Drv3_BTC_1_0_72.73 │     1 │          0.7 │           0.347 │         0.01 │    1 day, 23:00:00 │    1     0     0   100 │
+│  Drv3_BTC_1_0_57.14 │     1 │         0.64 │           0.318 │         0.01 │    1 day, 14:00:00 │    1     0     0   100 │
+│   Drv3_XRP_1_0_85.0 │     1 │         0.48 │           0.298 │         0.01 │    2 days, 7:00:00 │    1     0     0   100 │
+│  Drv3_ETH_1_0_76.92 │     1 │         0.58 │           0.290 │         0.01 │    2 days, 1:00:00 │    1     0     0   100 │
+│   Drv3_BTC_1_0_75.0 │     1 │         0.45 │           0.223 │         0.01 │    1 day, 15:00:00 │    1     0     0   100 │
+│  Drv3_DOGE_1_0_87.5 │     1 │         0.32 │           0.198 │         0.01 │    1 day, 11:00:00 │    1     0     0   100 │
+│   Drv3_XRP_1_0_80.0 │     1 │         0.32 │           0.196 │         0.01 │    1 day, 14:00:00 │    1     0     0   100 │
+│  Drv3_BTC_2_0_94.59 │     1 │         0.19 │           0.188 │         0.01 │   6 days, 10:00:00 │    1     0     0   100 │
+│   Drv3_XRP_1_0_92.0 │     1 │         0.35 │           0.173 │         0.01 │    3 days, 2:00:00 │    1     0     0   100 │
+│  Drv3_XRP_1_0_92.86 │     1 │         0.29 │           0.147 │          0.0 │    1 day, 18:00:00 │    1     0     0   100 │
+│  Drv3_ETH_2_0_97.62 │     1 │         0.14 │           0.145 │          0.0 │    1 day, 14:00:00 │    1     0     0   100 │
+│  Drv3_ETH_2_0_91.67 │     1 │         0.14 │           0.143 │          0.0 │     1 day, 0:00:00 │    1     0     0   100 │
+│  Drv3_BTC_1_0_85.71 │     1 │         0.27 │           0.133 │          0.0 │   2 days, 11:00:00 │    1     0     0   100 │
+│   Drv3_SOL_1_0_80.0 │     1 │         0.23 │           0.114 │          0.0 │    2 days, 0:00:00 │    1     0     0   100 │
+│  Drv3_BTC_2_0_66.67 │     1 │         0.11 │           0.107 │          0.0 │     1 day, 0:00:00 │    1     0     0   100 │
+│   Drv3_BTC_1_0_90.0 │     1 │         0.21 │           0.104 │          0.0 │     1 day, 9:00:00 │    1     0     0   100 │
+│          force_exit │     5 │        -0.54 │          -9.899 │        -0.33 │   12 days, 9:00:00 │    2     0     3  40.0 │
+│               TOTAL │   121 │         4.59 │         824.533 │        27.48 │  10 days, 12:59:00 │  118     0     3  97.5 │
+└─────────────────────┴───────┴──────────────┴─────────────────┴──────────────┴────────────────────┴────────────────────────┘
+                                                                      MIXED TAG STATS
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
+┃                          Enter Tag ┃ Exit Reason ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃       Avg Duration ┃  Win  Draw  Loss  Win% ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
+│   ('smth_12', 'RSI_XRP_5_0_28.43') │             │      1 │        15.15 │          71.078 │         2.37 │   15 days, 4:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_8_0_34.72') │             │      1 │         6.36 │          53.262 │         1.78 │ 125 days, 19:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_6_0_46.32') │             │      1 │        10.45 │          52.528 │         1.75 │  47 days, 13:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_3_0_26.01') │             │      1 │        21.51 │          34.730 │         1.16 │    6 days, 1:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_3_0_39.61') │             │      1 │        14.32 │          34.062 │         1.14 │  11 days, 21:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_3_0_14.24') │             │      1 │        15.48 │          26.538 │         0.88 │  11 days, 17:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_SOL_2_0_9.03') │             │      1 │        17.25 │          26.223 │         0.87 │    8 days, 1:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_4_0_19.78') │             │      1 │         9.64 │          21.919 │         0.73 │   9 days, 10:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_3_0_31.46') │             │      1 │        10.39 │          20.674 │         0.69 │   8 days, 13:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_4_0_24.35') │             │      1 │         6.46 │          20.553 │         0.69 │   13 days, 8:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_4_0_29.59') │             │      1 │         6.68 │          18.794 │         0.63 │  16 days, 21:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_2_0_23.33') │             │      1 │        17.89 │          18.435 │         0.61 │   3 days, 20:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_4_0_34.21') │             │      1 │         7.03 │          17.503 │         0.58 │   12 days, 1:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_3_0_18.45') │             │      1 │        10.19 │          16.852 │         0.56 │    7 days, 0:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_8_0_37.83') │             │      1 │         3.12 │          16.616 │         0.55 │  79 days, 11:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_4_0_12.14') │             │      1 │         6.86 │          15.212 │         0.51 │  16 days, 15:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_1_0_19.08') │             │      1 │        18.77 │          14.063 │         0.47 │   4 days, 11:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_20.83') │             │      1 │        26.55 │          13.279 │         0.44 │   3 days, 16:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_3_0_19.63') │             │      1 │         7.04 │          13.133 │         0.44 │   14 days, 0:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_3_0_25.43') │             │      1 │         6.43 │          12.901 │         0.43 │  12 days, 17:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_1_0_27.27') │             │      1 │        12.06 │          12.054 │          0.4 │    2 days, 6:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_67.31') │             │      1 │        11.51 │          11.807 │         0.39 │   3 days, 13:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_3_0_43.54') │             │      1 │         5.33 │          11.803 │         0.39 │  46 days, 10:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_1_0_11.11') │             │      1 │        12.28 │          11.253 │         0.38 │   3 days, 16:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_4_0_54.81') │             │      1 │         4.36 │          10.812 │         0.36 │  13 days, 15:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_34.78') │             │      1 │        16.81 │          10.484 │         0.35 │   2 days, 20:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_3_0_26.24') │             │      1 │          6.2 │          10.401 │         0.35 │   7 days, 23:00:00 │    1     0     0   100 │
+│    ('smth_12', 'RSI_ETH_1_0_8.93') │             │      1 │        20.52 │          10.253 │         0.34 │   4 days, 22:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_3_0_32.89') │             │      1 │         6.37 │          10.247 │         0.34 │   6 days, 18:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_28.89') │             │      1 │         9.34 │           9.561 │         0.32 │   5 days, 14:00:00 │    1     0     0   100 │
+│   ('smth_12', 'RSI_SOL_4_0_40.62') │             │      1 │         2.98 │           9.471 │         0.32 │  10 days, 23:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_3_0_69.84') │             │      1 │         2.64 │           9.241 │         0.31 │   3 days, 14:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_3_0_60.36') │             │      1 │         4.38 │           8.823 │         0.29 │   7 days, 10:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_47.83') │             │      1 │         8.04 │           8.420 │         0.28 │   3 days, 23:00:00 │    1     0     0   100 │
+│    ('smth_12', 'RSI_XRP_1_0_9.78') │             │      1 │        13.26 │           8.291 │         0.28 │    1 day, 10:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_33.33') │             │      1 │        15.27 │           7.630 │         0.25 │   3 days, 20:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_1_0_12.35') │             │      1 │        14.27 │           7.136 │         0.24 │   3 days, 22:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_1_0_39.42') │             │      1 │        10.17 │           6.354 │         0.21 │   3 days, 15:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_4_0_17.57') │             │      1 │         2.59 │           6.081 │          0.2 │  15 days, 18:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_2_0_18.06') │             │      1 │         5.89 │           5.956 │          0.2 │   9 days, 11:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_1_0_17.14') │             │      1 │         9.45 │           5.834 │         0.19 │    8 days, 2:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_8_0_81.16') │             │      1 │         0.73 │           5.508 │         0.18 │ 107 days, 19:00:00 │    1     0     0   100 │
+│   ('smth_12', 'RSI_BTC_5_0_31.25') │             │      1 │         1.93 │           5.464 │         0.18 │  17 days, 20:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_6_0_30.26') │             │      1 │         1.51 │           5.343 │         0.18 │  31 days, 22:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_4_0_83.45') │             │      1 │         1.65 │           4.730 │         0.16 │   11 days, 6:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_26.98') │             │      1 │          9.3 │           4.588 │         0.15 │   4 days, 12:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_SOL_1_0_25.0') │             │      1 │         7.26 │           4.538 │         0.15 │    3 days, 7:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_BTC_1_0_20.0') │             │      1 │         8.86 │           4.432 │         0.15 │   5 days, 22:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_5_0_68.35') │             │      1 │         1.23 │           4.368 │         0.15 │  55 days, 19:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_1_0_10.64') │             │      1 │         8.42 │           4.189 │         0.14 │   6 days, 23:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_3_0_60.19') │             │      1 │         2.61 │           4.110 │         0.14 │    4 days, 3:00:00 │    1     0     0   100 │
+│   ('smth_12', 'RSI_ETH_3_0_38.98') │             │      1 │          2.1 │           3.591 │         0.12 │   12 days, 8:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_1_0_27.66') │             │      1 │         5.48 │           3.425 │         0.11 │   2 days, 16:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_43.86') │             │      1 │         2.49 │           3.220 │         0.11 │    4 days, 1:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_1_0_40.74') │             │      1 │         5.16 │           3.215 │         0.11 │    2 days, 2:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_1_0_50.77') │             │      1 │         5.12 │           3.201 │         0.11 │   2 days, 12:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_7_0_96.68') │             │      1 │         0.29 │           3.008 │          0.1 │  110 days, 6:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_5_0_82.93') │             │      1 │         0.66 │           2.808 │         0.09 │  38 days, 21:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_3_0_74.07') │             │      1 │         1.13 │           2.788 │         0.09 │   6 days, 14:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_XRP_3_0_77.5') │             │      1 │         1.35 │           2.745 │         0.09 │   2 days, 16:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_57.63') │             │      1 │         2.33 │           2.489 │         0.08 │    5 days, 9:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_3_0_46.67') │             │      1 │         1.18 │           2.404 │         0.08 │   4 days, 10:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_XRP_1_0_54.0') │             │      1 │         4.34 │           2.338 │         0.08 │    3 days, 3:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_4_0_76.04') │             │      1 │         0.96 │           2.254 │         0.08 │  13 days, 17:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_BTC_1_0_56.0') │             │      1 │         3.55 │           2.217 │         0.07 │   6 days, 15:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_45.95') │             │      1 │         3.99 │           1.993 │         0.07 │     1 day, 5:00:00 │    1     0     0   100 │
+│   ('smth_12', 'RSI_ETH_1_0_16.67') │             │      1 │         3.97 │           1.977 │         0.07 │           14:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_1_0_26.09') │             │      1 │          2.8 │           1.746 │         0.06 │   2 days, 10:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_71.93') │             │      1 │         1.52 │           1.583 │         0.05 │   2 days, 11:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_1_0_11.11') │             │      1 │         3.14 │           1.565 │         0.05 │    2 days, 8:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_3_0_27.27') │             │      1 │         0.85 │           1.557 │         0.05 │           12:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_4_0_79.73') │             │      1 │         0.65 │           1.509 │         0.05 │   6 days, 20:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_2_0_76.56') │             │      1 │         1.15 │           1.466 │         0.05 │    3 days, 6:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_ETH_1_0_75.0') │             │      1 │         1.75 │           1.314 │         0.04 │   3 days, 14:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_3_0_73.47') │             │      1 │         0.76 │           1.289 │         0.04 │   20 days, 8:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_27.78') │             │      1 │         1.27 │           1.268 │         0.04 │            6:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_2_0_33.33') │             │      1 │         0.95 │           1.203 │         0.04 │     1 day, 1:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_2_0_83.58') │             │      1 │         1.12 │           1.148 │         0.04 │    1 day, 16:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_1_0_54.17') │             │      1 │         2.19 │           1.097 │         0.04 │    1 day, 15:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_2_0_44.44') │             │      1 │         0.79 │           1.033 │         0.03 │    9 days, 6:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_1_0_77.78') │             │      1 │          2.0 │           0.999 │         0.03 │    1 day, 16:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_1_0_41.18') │             │      1 │         1.93 │           0.964 │         0.03 │    5 days, 6:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_3_0_85.94') │             │      1 │         0.48 │           0.944 │         0.03 │  14 days, 16:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_XRP_3_0_12.5') │             │      1 │         0.45 │           0.712 │         0.02 │     1 day, 1:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_81.58') │             │      1 │         1.12 │           0.697 │         0.02 │    2 days, 7:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_DOGE_1_0_30.0') │             │      1 │          1.1 │           0.688 │         0.02 │           10:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_ETH_3_0_30.0') │             │      1 │         0.42 │           0.669 │         0.02 │     1 day, 6:00:00 │    1     0     0   100 │
+│    ('smth_12', 'Drv3_ETH_1_0_0.0') │             │      1 │         1.07 │           0.666 │         0.02 │            4:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_2_0_72.73') │             │      1 │         0.62 │           0.631 │         0.02 │    1 day, 20:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_XRP_2_0_25.0') │             │      1 │          0.6 │           0.614 │         0.02 │           13:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_2_0_66.67') │             │      1 │         0.59 │           0.607 │         0.02 │   4 days, 22:00:00 │    1     0     0   100 │
+│ ('smth_12', 'Drv3_DOGE_1_0_57.14') │             │      2 │         0.38 │           0.590 │         0.02 │            8:00:00 │    2     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_64.71') │             │      1 │         0.57 │           0.588 │         0.02 │    1 day, 12:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_94.95') │             │      1 │         0.36 │           0.548 │         0.02 │    2 days, 5:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_28.57') │             │      1 │         0.87 │           0.545 │         0.02 │            3:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_SOL_2_0_28.57') │             │      1 │         0.49 │           0.506 │         0.02 │     1 day, 5:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_BTC_2_0_37.5') │             │      1 │         0.45 │           0.489 │         0.02 │    3 days, 2:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_1_0_73.68') │             │      1 │         0.94 │           0.466 │         0.02 │   2 days, 18:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_2_0_76.47') │             │      1 │         0.38 │           0.397 │         0.01 │   15 days, 3:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_1_0_72.73') │             │      1 │          0.7 │           0.347 │         0.01 │    1 day, 23:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_1_0_57.14') │             │      1 │         0.64 │           0.318 │         0.01 │    1 day, 14:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_XRP_1_0_85.0') │             │      1 │         0.48 │           0.298 │         0.01 │    2 days, 7:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_1_0_76.92') │             │      1 │         0.58 │           0.290 │         0.01 │    2 days, 1:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_BTC_1_0_75.0') │             │      1 │         0.45 │           0.223 │         0.01 │    1 day, 15:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_DOGE_1_0_87.5') │             │      1 │         0.32 │           0.198 │         0.01 │    1 day, 11:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_XRP_1_0_80.0') │             │      1 │         0.32 │           0.196 │         0.01 │    1 day, 14:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_2_0_94.59') │             │      1 │         0.19 │           0.188 │         0.01 │   6 days, 10:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_XRP_1_0_92.0') │             │      1 │         0.35 │           0.173 │         0.01 │    3 days, 2:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_XRP_1_0_92.86') │             │      1 │         0.29 │           0.147 │          0.0 │    1 day, 18:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_2_0_97.62') │             │      1 │         0.14 │           0.145 │          0.0 │    1 day, 14:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_ETH_2_0_91.67') │             │      1 │         0.14 │           0.143 │          0.0 │     1 day, 0:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_1_0_85.71') │             │      1 │         0.27 │           0.133 │          0.0 │   2 days, 11:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_SOL_1_0_80.0') │             │      1 │         0.23 │           0.114 │          0.0 │    2 days, 0:00:00 │    1     0     0   100 │
+│  ('smth_12', 'Drv3_BTC_2_0_66.67') │             │      1 │         0.11 │           0.107 │          0.0 │     1 day, 0:00:00 │    1     0     0   100 │
+│   ('smth_12', 'Drv3_BTC_1_0_90.0') │             │      1 │         0.21 │           0.104 │          0.0 │     1 day, 9:00:00 │    1     0     0   100 │
+│          ('smth_12', 'force_exit') │             │      5 │        -0.54 │          -9.899 │        -0.33 │   12 days, 9:00:00 │    2     0     3  40.0 │
+│                              TOTAL │             │    121 │         4.59 │         824.533 │        27.48 │  10 days, 12:59:00 │  118     0     3  97.5 │
+└────────────────────────────────────┴─────────────┴────────┴──────────────┴─────────────────┴──────────────┴────────────────────┴────────────────────────┘
+                     WEEK BREAKDOWN
+┏━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━┳━━━━━━━┳━━━━━━━━┓
+┃       Week ┃ Tot Profit USDT ┃ Wins ┃ Draws ┃ Losses ┃
+┡━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━╇━━━━━━━╇━━━━━━━━┩
+│ 06/01/2025 │          37.217 │    6 │     0 │      0 │
+│ 13/01/2025 │          12.464 │    2 │     0 │      0 │
+│ 20/01/2025 │          76.722 │    7 │     0 │      0 │
+│ 27/01/2025 │           4.684 │    4 │     0 │      0 │
+│ 03/02/2025 │           3.577 │    4 │     0 │      0 │
+│ 10/02/2025 │               0 │    0 │     0 │      0 │
+│ 17/02/2025 │          17.503 │    1 │     0 │      0 │
+│ 24/02/2025 │               0 │    0 │     0 │      0 │
+│ 03/03/2025 │          71.078 │    1 │     0 │      0 │
+│ 10/03/2025 │           9.241 │    1 │     0 │      0 │
+│ 17/03/2025 │           4.588 │    1 │     0 │      0 │
+│ 24/03/2025 │           2.338 │    1 │     0 │      0 │
+│ 31/03/2025 │           0.147 │    1 │     0 │      0 │
+│ 07/04/2025 │               0 │    0 │     0 │      0 │
+│ 14/04/2025 │               0 │    0 │     0 │      0 │
+│ 21/04/2025 │               0 │    0 │     0 │      0 │
+│ 28/04/2025 │          16.839 │    2 │     0 │      0 │
+│ 05/05/2025 │           0.964 │    1 │     0 │      0 │
+│ 12/05/2025 │          78.013 │    5 │     0 │      0 │
+│ 19/05/2025 │           6.222 │    4 │     0 │      0 │
+│ 26/05/2025 │          19.509 │    3 │     0 │      0 │
+│ 02/06/2025 │           0.944 │    1 │     0 │      0 │
+│ 09/06/2025 │               0 │    0 │     0 │      0 │
+│ 16/06/2025 │             9.2 │    3 │     0 │      0 │
+│ 23/06/2025 │           2.131 │    2 │     0 │      0 │
+│ 30/06/2025 │           7.723 │    3 │     0 │      0 │
+│ 07/07/2025 │           5.149 │    5 │     0 │      0 │
+│ 14/07/2025 │          81.049 │    8 │     0 │      0 │
+│ 21/07/2025 │          66.176 │    5 │     0 │      0 │
+│ 28/07/2025 │          27.276 │   10 │     0 │      0 │
+│ 04/08/2025 │           0.788 │    2 │     0 │      0 │
+│ 11/08/2025 │          62.555 │    5 │     0 │      0 │
+│ 18/08/2025 │          15.647 │    6 │     0 │      0 │
+│ 25/08/2025 │          47.927 │    3 │     0 │      0 │
+│ 01/09/2025 │           3.201 │    1 │     0 │      0 │
+│ 08/09/2025 │            3.22 │    1 │     0 │      0 │
+│ 15/09/2025 │          70.772 │    6 │     0 │      0 │
+│ 22/09/2025 │           6.969 │    5 │     0 │      0 │
+│ 29/09/2025 │               0 │    0 │     0 │      0 │
+│ 06/10/2025 │          62.599 │    6 │     0 │      0 │
+│ 13/10/2025 │          -9.899 │    2 │     0 │      3 │
+└────────────┴─────────────────┴──────┴───────┴────────┘
+                   SUMMARY METRICS
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓
+┃ Metric                      ┃ Value               ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
+│ Backtesting from            │ 2025-01-01 00:00:00 │
+│ Backtesting to              │ 2025-10-07 10:00:00 │
+│ Trading Mode                │ Spot                │
+│ Max open trades             │ 5                   │
+│                             │                     │
+│ Total/Daily Avg Trades      │ 121 / 0.43          │
+│ Starting balance            │ 3000 USDT           │
+│ Final balance               │ 3824.533 USDT       │
+│ Absolute profit             │ 824.533 USDT        │
+│ Total profit %              │ 27.48%              │
+│ CAGR %                      │ 37.39%              │
+│ Sortino                     │ 11.17               │
+│ Sharpe                      │ 5.08                │
+│ Calmar                      │ 596.19              │
+│ SQN                         │ 6.71                │
+│ Profit factor               │ 68.73               │
+│ Expectancy (Ratio)          │ 6.81 (1.68)         │
+│ Avg. daily profit %         │ 0.10%               │
+│ Avg. stake amount           │ 155.858 USDT        │
+│ Total trade volume          │ 38619.369 USDT      │
+│                             │                     │
+│ Best Pair                   │ XRP/USDT 6.62%      │
+│ Worst Pair                  │ BTC/USDT 2.53%      │
+│ Best trade                  │ XRP/USDT 26.55%     │
+│ Worst trade                 │ XRP/USDT -4.64%     │
+│ Best day                    │ 76.022 USDT         │
+│ Worst day                   │ -9.899 USDT         │
+│ Days win/draw/lose          │ 75 / 203 / 1        │
+│ Avg. Duration Winners       │ 10 days, 7:44:00    │
+│ Avg. Duration Loser         │ 19 days, 3:20:00    │
+│ Max Consecutive Wins / Loss │ 116 / 2             │
+│ Rejected Entry signals      │ 0                   │
+│ Entry/Exit Timeouts         │ 0 / 0               │
+│                             │                     │
+│ Min balance                 │ 3008.291 USDT       │
+│ Max balance                 │ 3835.901 USDT       │
+│ Max % of account underwater │ 0.32%               │
+│ Absolute Drawdown (Account) │ 0.32%               │
+│ Absolute Drawdown           │ 12.109 USDT         │
+│ Drawdown high               │ 835.901 USDT        │
+│ Drawdown low                │ 823.792 USDT        │
+│ Drawdown Start              │ 2025-10-07 10:00:00 │
+│ Drawdown End                │ 2025-10-07 10:00:00 │
+│ Market change               │ 2.17%               │
+└─────────────────────────────┴─────────────────────┘
+
+Backtested 2025-01-01 00:00:00 -> 2025-10-07 10:00:00 | Max open trades : 5
+                                                            STRATEGY SUMMARY
+┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
+┃  Strategy ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃      Avg Duration ┃  Win  Draw  Loss  Win% ┃           Drawdown ┃
+┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
+│ Zeus_8_1d │    121 │         4.59 │         824.533 │        27.48 │ 10 days, 12:59:00 │  118     0     3  97.5 │ 12.109 USDT  0.32% │
+└───────────┴────────┴──────────────┴─────────────────┴──────────────┴───────────────────┴────────────────────────┴────────────────────┘

Zeus_8_3_2_B_4_2.json

@@ -17,16 +17,17 @@
       "max_open_trades": 80
     },
     "buy": {
-      "buy_horizon_predict_1h": 2
-    },
-    "sell": {
-      "sell_allow_decrease": 0.2
+      "buy_horizon_predict_1h": 2,
+      "mise_factor_buy": 0.06
     },
+    "sell": {},
     "protection": {
-      "protection_fibo": 9,
-      "protection_percent_buy_lost": 3
+      "sma5_deriv1_1d_restart_protection": 2.2,
+      "sma5_deriv1_1d_stop_protection": -3.9,
+      "sma5_deriv2_1d_restart_protection": 0.0,
+      "sma5_deriv2_1d_stop_protection": -4.8
     }
   },
   "ft_stratparam_v": 1,
-  "export_time": "2025-05-24 18:29:22.477903+00:00"
+  "export_time": "2025-09-28 13:58:28.838866+00:00"
 }