diff --git a/pairs.txt b/pairs.txt
new file mode 100644
index 0000000..dd9e748
--- /dev/null
+++ b/pairs.txt
@@ -0,0 +1,6 @@
+BTC_USDT
+ETH_USDT
+DOGE_USDT
+XRP_USDT
+SOL_USDT
+
diff --git a/tools/create_params_tree.sh b/tools/create_params_tree.sh
new file mode 100755
index 0000000..6c9b6b8
--- /dev/null
+++ b/tools/create_params_tree.sh
@@ -0,0 +1,18 @@
+#!/usr/bin/env bash
+
+# Usage: create_params_tree.sh <PAIR1> [PAIR2] ...
+
+if [ $# -lt 1 ]; then
+    echo "Usage: $0 <PAIR1> [PAIR2] ..." >&2
+    exit 1
+fi
+
+for PAIR in "$@"; do
+    DIR="params/$PAIR"
+    mkdir -p "$DIR"
+    echo "Created: $DIR"
+    for REGIME in bull bear range; do
+        mkdir -p "$DIR/$REGIME"
+        echo "  -> $DIR/$REGIME"
+    done
+done
diff --git a/tools/detect_regime.py b/tools/detect_regime.py
new file mode 100755
index 0000000..966a9d3
--- /dev/null
+++ b/tools/detect_regime.py
@@ -0,0 +1,114 @@
+#!/usr/bin/env python3
+"""
+Detect bull/bear/range regimes from historical CSV data (SMA50/SMA200 crossovers)
+Usage: python3 detect_regime.py <PAIR> <CSV_FILE>
+CSV must contain at least columns: timestamp, close
+"""
+
+# python3 user_data/strategies/tools/detect_regime.py BTC /home/jerome/Perso/freqtradeDocker/user_data/data/binance/BTC_USDT-1d.feather
+
+import sys
+import pandas as pd
+import ta
+import talib.abstract as talib
+
+if len(sys.argv) < 3:
+    print("Usage: detect_regime.py <PAIR> <FEATHER_FILE>")
+    sys.exit(1)
+
+pair = sys.argv[1]
+file = sys.argv[2]
+
+# lecture du fichier feather
+df = pd.read_feather(file)
+# ne garder que timestamp et close pour detect_regime.py
+df[['date', 'close']].rename(columns={'date':'timestamp'}).to_csv(
+    f"user_data/data/{pair}-usdt-1d.csv", index=False
+)
+
+df = pd.read_csv(f"user_data/data/{pair}-usdt-1d.csv")
+
+if 'close' not in df.columns or 'timestamp' not in df.columns:
+    print("CSV must contain 'timestamp' and 'close' columns")
+    sys.exit(1)
+
+# --- paramètres ---
+SMOOTH_WIN = 5   # EMA pour lisser la pente
+NUM_TOP = 3      # nombre de segments à garder par classe
+
+# --- charger les données ---
+df['timestamp'] = pd.to_datetime(df['timestamp'], errors='coerce')
+
+# --- calcul SMA14 ---
+df['sma14'] = ta.trend.sma_indicator(df['close'], 14)
+
+# --- pente brute ---
+df['slope'] = df['sma14'].diff()
+
+# --- lissage EMA ---
+df['slope_smooth'] = df['slope'].ewm(span=SMOOTH_WIN, adjust=False).mean()
+
+# --- normalisation relative ---
+df['slope_norm'] = df['slope_smooth'] / df['close']
+df['slope_norm'].fillna(0, inplace=True)
+
+# --- classification dynamique via quantiles ---
+q = df['slope_norm'].quantile([0.07, 0.21, 0.35, 0.65, 0.79, 0.93]).values
+q1, q2, q3, q4, q5, q6 = q
+
+def classify(v):
+    if v <= q1:
+        return 'BR3'
+    elif v <= q2:
+        return 'BR2'
+    elif v <= q3:
+        return 'BR1'
+    elif v <= q4:
+        return 'RG'
+    elif v <= q5:
+        return 'BU1'
+    elif v <= q6:
+        return 'BU2'
+    else:
+        return 'BU3'
+
+df['trend_class'] = df['slope_norm'].apply(classify)
+
+# --- boucle pour détecter les segments ---
+segments = []
+trend = None
+start_idx = None
+
+for i in range(len(df)):
+    new_trend = df['trend_class'].iloc[i]
+
+    if trend is None:
+        trend = new_trend
+        start_idx = i
+    elif new_trend != trend:
+        start_ts = df['timestamp'].iloc[start_idx]
+        end_ts = df['timestamp'].iloc[i]
+        segments.append((trend, start_ts, end_ts))
+        trend = new_trend
+        start_idx = i
+
+# fermer le dernier segment
+if trend is not None and start_idx is not None:
+    start_ts = df['timestamp'].iloc[start_idx]
+    end_ts = df['timestamp'].iloc[len(df)-1]
+    segments.append((trend, start_ts, end_ts))
+
+# --- extraire les 5 plus longs segments par classe ---
+top_segments_by_class = {}
+for cls in ['BR3','BR2','BR1','RG','BU1','BU2','BU3']:
+    cls_segments = [(t,s,e) for t,s,e in segments if t==cls]
+    # calcul de la durée
+    cls_segments = [(t,s,e,(e-s).total_seconds()) for t,s,e in cls_segments]
+    cls_segments.sort(key=lambda x: x[3], reverse=True)
+    top_segments_by_class[cls] = [(t,s,e) for t,s,e,d in cls_segments[:NUM_TOP]]
+
+# --- affichage ---
+for cls, segs in top_segments_by_class.items():
+    print(f"--- {cls} ---")
+    for t,s,e in segs:
+        print(f"{t} {s} {e}")
diff --git a/tools/run_hyperopt_batch.sh b/tools/run_hyperopt_batch.sh
new file mode 100755
index 0000000..df631d6
--- /dev/null
+++ b/tools/run_hyperopt_batch.sh
@@ -0,0 +1,80 @@
+#!/usr/bin/env bash
+
+# Usage: run_hyperopt_batch.sh <PAIR_LIST_FILE>
+# <PAIR_LIST_FILE> contains one pair per line, e.g., BTC-USDT\nETH-USDT
+#
+# This script will read each pair, detect regimes (using detect_regime.py),
+# and run freqtrade hyperopt for each detected regime, saving user_data/strategies/params in user_data/strategies/params/PAIR/REGIME/
+
+# Lanement par docker exec -i freqtrade user_data/strategies/tools/run_hyperopt_batch.sh user_data/strategies/pairs.txt
+# user_data/strategies/tools/run_hyperopt_batch.sh user_data/strategies/pairs.txt
+
+STRATEGIE="Zeus_8_3_2_B_4_2"
+
+if [ $# -ne 1 ]; then
+    echo "Usage: $0 <PAIR_LIST_FILE>" >&2
+    exit 1
+fi
+
+PAIR_LIST_FILE="$1"
+
+if [ ! -f "$PAIR_LIST_FILE" ]; then
+    echo "File not found: $PAIR_LIST_FILE" >&2
+    exit 1
+fi
+echo "ici $PAIR_LIST_FILE"
+
+while read -r PAIR; do
+    echo $PAIR
+    [ -z "$PAIR" ] && continue
+    echo "\nProcessing pair: $PAIR"
+
+    DATA_FEATHER="user_data/data/binance/$(echo $PAIR | tr '[:upper:]' '[:upper:]')-1d.feather"
+    if [ ! -f "$DATA_FEATHER" ]; then
+        echo "Data file not found for $PAIR: $DATA_FEATHER" >&2
+        continue
+    fi
+    echo "Work with data file $PAIR: $DATA_FEATHER" >&2
+
+    # Detect regimes using Python script
+    REGIMES=$(python3 user_data/strategies/tools/detect_regime.py "$PAIR" "$DATA_FEATHER") # | awk '{print tolower($1) " " $2 " " $4}')
+
+    while read -r REGIME START st END et; do
+        echo "Work with dates $REGIME : $START - $END" >&2
+
+        if [ -z "$START" ] || [ -z "$END" ]; then
+            echo "Skipping $PAIR $REGIME : cannot determine timerange" >&2
+            continue
+        fi
+
+        if [[ "$START" < "2024-09-01" ]]; then
+            echo "TOO OLD $START"
+            continue
+        fi
+
+        TIMERANGE="${START//-/}-${END//-/}"
+        echo "Running hyperopt for $PAIR $REGIME with timerange $TIMERANGE"
+
+        OUTPUT_JSON="user_data/strategies/params/$PAIR/$REGIME/$START-$END-hyperopt_result.json"
+        OUTPUT_TXT="user_data/strategies/params/$PAIR/$REGIME/$START-$END-hyperopt_result.txt"
+        mkdir -p "user_data/strategies/params/$PAIR/$REGIME"
+
+        converted="${PAIR/_//}"
+
+#        COLUMNS=200 LINES=40 script -q -c "
+
+        freqtrade hyperopt --strategy $STRATEGIE --config user_data/config.json --hyperopt-loss OnlyProfitHyperOptLoss --timerange $TIMERANGE --timeframe 5m --spaces sell buy protection --pair $converted -e 80 -j7
+
+        echo "Saved hyperopt output to $OUTPUT_JSON"
+
+        cp user_data/strategies/$STRATEGIE.json $OUTPUT_JSON
+
+        # COLUMNS=120 LINES=40 script -q -c "
+#        docker exec -i freqtrade
+        freqtrade hyperopt-list  --profitable --no-details > $OUTPUT_TXT
+
+        sleep 1
+
+    done <<< "$REGIMES"
+
+done < "$PAIR_LIST_FILE"
\ No newline at end of file
diff --git a/tools/save_params.sh b/tools/save_params.sh
new file mode 100755
index 0000000..69b64fc
--- /dev/null
+++ b/tools/save_params.sh
@@ -0,0 +1,21 @@
+#!/usr/bin/env bash
+
+# Usage: save_params.sh <pair> <regime> <sourcefile> <destname>
+
+set -e
+
+if [ $# -ne 4 ]; then
+  echo "Usage: $0 <pair> <bull|bear> <sourcefile> <destname>" >&2
+  exit 1
+fi
+
+PAIR="$1"
+REGIME="$2"
+SRC="$3"
+DESTNAME="$4"
+
+mkdir -p "params/${PAIR}/${REGIME}"
+
+DEST="params/${PAIR}/${REGIME}/${DESTNAME}.json"
+cp "$SRC" "$DEST"
+echo "Saved: $DEST"
\ No newline at end of file