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src/calibration/strategies_inspector.py

@@ -21,27 +21,11 @@ from src.risk.sizing.percent_risk import PercentRiskSizer
 # --------------------------------------------------
 # Strategy registry (con metadata de parámetros)
 # --------------------------------------------------
+from src.strategies.registry import STRATEGY_REGISTRY
 from src.strategies.moving_average import MovingAverageCrossover
 from src.strategies.rsi_strategy import RSIStrategy
 from src.strategies.buy_and_hold import BuyAndHold
 
-
-STRATEGY_REGISTRY = {
-    "moving_average": {
-        "class": MovingAverageCrossover,
-        "params": ["fast_period", "slow_period"],
-    },
-    "rsi": {
-        "class": RSIStrategy,
-        "params": ["rsi_period", "overbought", "oversold"],
-    },
-    "buy_and_hold": {
-        "class": BuyAndHold,
-        "params": [],
-    },
-}
-
-
 # --------------------------------------------------
 # Helpers
 # --------------------------------------------------
@@ -49,15 +33,24 @@ STRATEGY_REGISTRY = {
 def list_available_strategies() -> List[Dict[str, Any]]:
     """
     Devuelve metadata completa para UI.
+    Usa parameters_schema() como fuente de verdad.
     """
-    out = []
 
-    for sid, entry in STRATEGY_REGISTRY.items():
+    out: List[Dict[str, Any]] = []
+
+    for strategy_id, strategy_class in STRATEGY_REGISTRY.items():
+
+        if not hasattr(strategy_class, "parameters_schema"):
+            continue
+
+        schema = strategy_class.parameters_schema()
+
         out.append({
-            "strategy_id": sid,
+            "strategy_id": strategy_id,
-            "name": entry["class"].__name__,
+            "name": strategy_class.__name__,
-            "params": entry["params"],
+            "params": list(schema.keys()),
-            "tags": [],  # puedes rellenar más adelante
+            "parameters_schema": schema,  # 🔥 ahora enviamos schema completo
+            "tags": [],
         })
 
     return out
@@ -67,7 +60,7 @@ def _build_stop_loss(stop_schema) -> object | None:
     if stop_schema.type == "fixed":
         return FixedStop(stop_fraction=float(stop_schema.stop_fraction))
     if stop_schema.type == "trailing":
-        return TrailingStop(stop_fraction=float(stop_schema.stop_fraction))
+        return TrailingStop(trailing_fraction=float(stop_schema.stop_fraction))
     if stop_schema.type == "atr":
         return ATRStop(
             atr_period=int(stop_schema.atr_period),
@@ -94,27 +87,6 @@ def _accumulate_equity(initial: float, returns_pct: List[float]) -> List[float]:
     return eq
 
 
-def _build_param_values(min_v: float, max_v: float, step: float) -> List[float]:
-    min_v = float(min_v)
-    max_v = float(max_v)
-    step = float(step)
-
-    # Valor único si min == max
-    if min_v == max_v:
-        return [min_v]
-
-    # Valor único si step <= 1
-    if step <= 1:
-        return [min_v]
-
-    values = []
-    v = min_v
-    while v <= max_v:
-        values.append(v)
-        v += step
-
-    return values
-
 # --------------------------------------------------
 # Main
 # --------------------------------------------------
@@ -162,14 +134,21 @@ def inspect_strategies_config(
     step_td = pd.Timedelta(days=int(payload.wf.step_days or payload.wf.test_days))
 
     overall_status = "ok"
+    
+    log.info(f"🔥 Strategies received: {len(payload.strategies)}")
+
     results: List[Dict[str, Any]] = []
     series: Dict[str, Any] = {"strategies": {}} if include_series else {}
 
+    log.info(f"🔥 Strategies received: {len(payload.strategies)}")
+
     for sel in payload.strategies:
 
         sid = sel.strategy_id
         entry = STRATEGY_REGISTRY.get(sid)
 
+        log.info(f"🧠 Step3 | Processing strategy: {sid}")
+
         if entry is None:
             results.append({
                 "strategy_id": sid,
@@ -183,10 +162,13 @@ def inspect_strategies_config(
                 "windows": [],
             })
             overall_status = "fail"
+            log.error(f"❌ Strategy not found in registry: {sid}")
             continue
 
-        strategy_class = entry["class"]
+        strategy_class = STRATEGY_REGISTRY[sid]
-        valid_params = set(entry["params"])
+
+        schema = strategy_class.parameters_schema()
+        valid_params = set(schema.keys())
         range_params = set(sel.parameters.keys())
 
 
@@ -209,17 +191,13 @@ def inspect_strategies_config(
             continue
         
         # --------------------------------------------------
-        # Convert ranges -> param_grid real
+        # Build fixed_params (VALIDATION MODE)
         # --------------------------------------------------
-        param_grid = {}
+        fixed_params = {}
+
+        for pname, pvalue in sel.parameters.items():
+            fixed_params[pname] = pvalue
 
-        for pname, prange in sel.parameters.items():
-            values = _build_param_values(
-                min_v=prange.min,
-                max_v=prange.max,
-                step=prange.step,
-            )
-            param_grid[pname] = values
 
         # Wrapper sizer
         class _CappedSizer(type(base_sizer)):
@@ -248,7 +226,8 @@ def inspect_strategies_config(
         try:
             wf = WalkForwardValidator(
                 strategy_class=strategy_class,
-                param_grid=param_grid,
+                param_grid=None,
+                fixed_params=fixed_params,
                 data=df,
                 train_window=train_td,
                 test_window=test_td,
@@ -256,49 +235,60 @@ def inspect_strategies_config(
                 initial_capital=float(payload.account_equity),
                 commission=float(payload.commission),
                 slippage=float(payload.slippage),
-                optimizer_metric=str(payload.optimization.optimizer_metric),
                 position_sizer=capped_sizer,
                 stop_loss=stop_loss,
-                max_combinations=int(payload.optimization.max_combinations),
                 progress_callback=progress_callback,
             )
 
             wf_res = wf.run()
             win_df: pd.DataFrame = wf_res["windows"]
 
+            oos_returns = []
+            oos_dd = []
+            warnings_list = []
+            n_windows = 0
+
             if win_df is None or win_df.empty:
-                status = "fail"
+                status = "warning"
-                msg = "WF produced no valid windows"
+                msg = "No closed trades in OOS"
-                overall_status = "fail"
+                warnings_list.append("Walk-forward produced no closed trades.")
-                windows_out = []
-                oos_returns = []
             else:
-                trades = win_df["trades"].astype(int).tolist()
+                oos_returns = win_df["return_pct"].tolist()
-                too_few = sum(t < int(payload.optimization.min_trades_test) for t in trades)
+                oos_dd = win_df["max_dd_pct"].tolist()
+                n_windows = len(win_df)
 
-                if too_few > 0:
+            trades = win_df["trades"].astype(int).tolist()
-                    status = "warning"
+            too_few = sum(t < int(payload.wf.min_trades_test) for t in trades)
-                    msg = f"{too_few} windows below min_trades_test"
-                    if overall_status == "ok":
-                        overall_status = "warning"
-                else:
-                    status = "ok"
-                    msg = "WF OK"
 
-                windows_out = []
+            if too_few > 0:
-                for _, r in win_df.iterrows():
+                warnings_list.append(
-                    windows_out.append({
+                    f"{too_few} test windows have fewer than {payload.wf.min_trades_test} trades"
-                        "window": int(r["window"]),
+                )
-                        "train_start": str(r["train_start"]),
+
-                        "train_end": str(r["train_end"]),
+            windows_out = []
-                        "test_start": str(r["test_start"]),
+
-                        "test_end": str(r["test_end"]),
+            if warnings_list:
-                        "return_pct": float(r["return_pct"]),
+                status = "warning"
-                        "sharpe": float(r["sharpe"]),
+                msg = "Validation completed with warnings"
-                        "max_dd_pct": float(r["max_dd_pct"]),
+                if overall_status == "ok":
-                        "trades": int(r["trades"]),
+                    overall_status = "warning"
-                        "params": dict(r["params"]) if isinstance(r["params"], dict) else r["params"],
+            else:
-                    })
+                status = "ok"
+                msg = "WF OK"
+
+            for _, r in win_df.iterrows():
+                windows_out.append({
+                    "window": int(r["window"]),
+                    "train_start": str(r["train_start"]),
+                    "train_end": str(r["train_end"]),
+                    "test_start": str(r["test_start"]),
+                    "test_end": str(r["test_end"]),
+                    "return_pct": float(r["return_pct"]),
+                    "sharpe": float(r["sharpe"]),
+                    "max_dd_pct": float(r["max_dd_pct"]),
+                    "trades": int(r["trades"]),
+                    "params": dict(r["params"]) if isinstance(r["params"], dict) else r["params"],
+                })
 
                 oos_returns = win_df["return_pct"].astype(float).tolist()
 
@@ -311,6 +301,7 @@ def inspect_strategies_config(
                 "strategy_id": sid,
                 "status": status,
                 "message": msg,
+                "warnings": warnings_list if status == "warning" else [],
                 "n_windows": int(len(windows_out)),
                 "oos_final_equity": oos_final,
                 "oos_total_return_pct": float(oos_total_return),
@@ -323,6 +314,7 @@ def inspect_strategies_config(
                 series["strategies"][sid] = {
                     "window_returns_pct": oos_returns,
                     "window_equity": eq_curve,
+                    "window_trades": win_df["trades"].tolist(),
                 }
 
         except Exception as e:

src/core/walk_forward.py

@@ -1,6 +1,6 @@
-# src/backtest/walk_forward.py
+# src/core/walk_forward.py
 import pandas as pd
-from typing import List, Dict, Optional
+from typing import List, Dict, Optional, Callable, Any
 from src.core.optimizer import ParameterOptimizer
 from src.core.engine import Engine
 from src.risk.sizing.base import PositionSizer
@@ -19,7 +19,7 @@ class WalkForwardValidator:
     def __init__(
         self,
         strategy_class,
-        param_grid: dict,
+        param_grid: Optional[dict],
         data: pd.DataFrame,
         train_window: pd.Timedelta,
         test_window: pd.Timedelta,
@@ -34,9 +34,12 @@ class WalkForwardValidator:
         stop_loss: Optional[StopLoss] = None,
         max_combinations: Optional[int] = None,
         progress_callback: Optional[callable] = None,
+        fixed_params: Optional[dict] = None,
     ):
         self.strategy_class = strategy_class
         self.param_grid = param_grid
+        self.fixed_params = fixed_params
+
         self.data = data.sort_index()
 
         self.train_window = train_window
@@ -62,6 +65,13 @@ class WalkForwardValidator:
         if not self.data.index.is_monotonic_increasing:
             raise ValueError("data.index debe estar ordenado cronológicamente")
         
+        # ✅ Validación de modo (NUEVO, mínimo y claro)
+        if self.param_grid is not None and self.fixed_params is not None:
+            raise ValueError("WalkForwardValidator: usa param_grid (optimization) o fixed_params (validation), no ambos.")
+
+        if self.param_grid is None and self.fixed_params is None:
+            raise ValueError("WalkForwardValidator: debes pasar param_grid o fixed_params.")
+
     # ------------------------------------------------------------------
     # 🔹 GENERACIÓN DE VENTANAS TEMPORALES
     # ------------------------------------------------------------------
@@ -186,26 +196,33 @@ class WalkForwardValidator:
                 continue
 
             # 1️⃣ Optimización TRAIN
-            optimizer = ParameterOptimizer(
+            best_train_metric = None
-                strategy_class=self.strategy_class,
-                data=train_data,
-                initial_capital=self.initial_capital,
-                commission=self.commission,
-                slippage=self.slippage,
-                position_size=self.position_size,
-                position_sizer=self.position_sizer,
-                stop_loss=self.stop_loss,
-                max_combinations=self.max_combinations,
-            )
 
-            opt_df = optimizer.optimize(self.param_grid)
+            if self.fixed_params is not None:
+                # ✅ VALIDATION MODE: sin optimización
+                best_params = self.fixed_params
+            else:
+                # ✅ OPTIMIZATION MODE
+                optimizer = ParameterOptimizer(
+                    strategy_class=self.strategy_class,
+                    data=train_data,
+                    initial_capital=self.initial_capital,
+                    commission=self.commission,
+                    slippage=self.slippage,
+                    position_size=self.position_size,
+                    position_sizer=self.position_sizer,
+                    stop_loss=self.stop_loss,
+                    max_combinations=self.max_combinations,
+                )
 
-            if opt_df.empty:
+                opt_df = optimizer.optimize(self.param_grid)
-                log.warning(f"WF #{wid} sin resultados de optimización")
-                continue
 
-            best_params = optimizer.get_best_params(metric=self.optimizer_metric)
+                if opt_df.empty:
-            best_train_metric = opt_df[self.optimizer_metric].max()
+                    log.warning(f"WF #{wid} sin resultados de optimización")
+                    continue
+
+                best_params = optimizer.get_best_params(metric=self.optimizer_metric)
+                best_train_metric = opt_df[self.optimizer_metric].max()
 
             # 2️⃣ Backtest TEST (OOS)
             strategy = self.strategy_class(**best_params)
@@ -261,6 +278,7 @@ class WalkForwardValidator:
                 "n_windows": len(rows),
                 "data_start": self.data.index.min(),
                 "data_end": self.data.index.max(),
+                "mode": "validation" if self.fixed_params is not None else "optimization"
             },
             "windows": pd.DataFrame(rows),
             "raw_results": raw_results,

src/strategies/moving_average.py

@@ -10,7 +10,12 @@ class MovingAverageCrossover(Strategy):
     """
     Estrategia de cruce de medias móviles
 
-    Señales:
+    Señales:@classmethod
+    def default_parameters(cls) -> dict:
+        return {
+            "fast_period": 10,
+            "slow_period": 30,
+        }
     - BUY: Cruce alcista de medias + (ADX >= threshold si está activado)
     - SELL: Cruce bajista de medias
     - HOLD: En cualquier otro caso
@@ -28,6 +33,8 @@ class MovingAverageCrossover(Strategy):
         Sin ADX todavía → primero evaluamos la señal “pura”
     """
 
+    strategy_id = "moving_average"
+
     def __init__(
         self,
         fast_period: int = 20,
@@ -55,7 +62,38 @@ class MovingAverageCrossover(Strategy):
         if self.ma_type not in ['sma', 'ema']:
             raise ValueError("ma_type debe ser 'sma' o 'ema'")
 
-    # ------------------------------------------------------------------
+    @classmethod
+    def parameters_schema(cls) -> dict:
+        return {
+            "fast_period": {
+                "type": "int",
+                "min": 1,
+                "max": 500,
+                "default": 20,
+            },
+            "slow_period": {
+                "type": "int",
+                "min": 1,
+                "max": 500,
+                "default": 50,
+            },
+            "ma_type": {
+                "type": "enum",
+                "choices": ["sma", "ema"],
+                "default": "ema",
+            },
+            "use_adx": {
+                "type": "bool",
+                "default": False,
+            },
+            "adx_threshold": {
+                "type": "float",
+                "min": 1,
+                "max": 100,
+                "default": 20.0,
+            },
+        }
+
 
     def init_indicators(self, data: pd.DataFrame) -> pd.DataFrame:
         """

src/strategies/registry.py

@@ -0,0 +1,16 @@
+# src/strategies/registry.py
+from .moving_average import MovingAverageCrossover
+from .rsi_strategy import RSIStrategy
+from .buy_and_hold import BuyAndHold
+
+
+ALL_STRATEGIES = [
+    MovingAverageCrossover,
+    RSIStrategy,
+]
+
+
+STRATEGY_REGISTRY = {
+    cls.strategy_id: cls
+    for cls in ALL_STRATEGIES
+}

src/strategies/rsi_strategy.py

@@ -20,6 +20,8 @@ class RSIStrategy(Strategy):
         overbought_threshold: Umbral de sobrecompra (default: 70)
     """
     
+    strategy_id = "rsi"
+    
     def __init__(self, rsi_period: int = 14, oversold_threshold: float = 30, overbought_threshold: float = 70):
         
         params = {
@@ -34,6 +36,30 @@ class RSIStrategy(Strategy):
         self.oversold = oversold_threshold
         self.overbought = overbought_threshold
 
+    @classmethod
+    def parameters_schema(cls) -> dict:
+        return {
+            "rsi_period": {
+                "type": "int",
+                "min": 1,
+                "max": 200,
+                "default": 14,
+            },
+            "oversold": {
+                "type": "float",
+                "min": 0,
+                "max": 100,
+                "default": 30,
+            },
+            "overbought": {
+                "type": "float",
+                "min": 0,
+                "max": 100,
+                "default": 70,
+            },
+        }
+
+
     def init_indicators(self, data: pd.DataFrame) -> pd.DataFrame:
         """
         Calcula el RSI

src/web/api/v2/routers/calibration_strategies.py

@@ -10,6 +10,7 @@ from fastapi import APIRouter, Depends, HTTPException, Request
 from fastapi.responses import JSONResponse, HTMLResponse
 
 from src.data.storage import StorageManager
+from src.strategies.registry import STRATEGY_REGISTRY
 from src.calibration.strategies_inspector import (
     inspect_strategies_config,
     list_available_strategies,
@@ -37,22 +38,40 @@ def get_storage() -> StorageManager:
 
 @router.get("/catalog")
 def strategy_catalog():
+
     strategies = list_available_strategies()
 
-    # Añadimos defaults sugeridos
+    enriched = []
-    for s in strategies:
+
-        s["parameters_meta"] = [
+    for s in strategies:
-            {
+
-                "name": p,
+        strategy_id = s["strategy_id"]
-                "type": "int",
+        strategy_class = STRATEGY_REGISTRY[strategy_id]
-                "default_min": 10,
+
-                "default_max": 50,
+        schema = strategy_class.parameters_schema()
-                "default_step": 10,
+
-            }
+        parameters_meta = []
-            for p in s["params"]
+
-        ]
+        for name, meta in schema.items():
+
+            parameters_meta.append({
+                "name": name,
+                "type": meta.get("type"),
+                "default_value": meta.get("default"),
+                "choices": meta.get("choices"),
+                "min": meta.get("min"),
+                "max": meta.get("max"),
+            })
+
+        enriched.append({
+            "strategy_id": strategy_id,
+            "name": s["name"],
+            "params": list(schema.keys()),
+            "parameters_meta": parameters_meta,
+        })
+
+    return {"strategies": enriched}
 
-    return {"strategies": strategies}
 
 @router.post("/inspect", response_model=CalibrationStrategiesInspectResponse)
 def inspect_strategies(
@@ -147,9 +166,9 @@ def report_strategies(
             "WF train_days": payload.wf.train_days,
             "WF test_days": payload.wf.test_days,
             "WF step_days": payload.wf.step_days or payload.wf.test_days,
-            "Optimizer metric": payload.optimization.optimizer_metric,
+            "Min trades per window (test)": payload.wf.min_trades_test,
-            "Max combinations": payload.optimization.max_combinations,
         },
+
         results=result,
     )
 

src/web/api/v2/schemas/calibration_strategies.py

@@ -1,33 +1,24 @@
 # src/web/api/v2/schemas/calibration_strategies.py
 
-from typing import Any, Dict, List, Literal, Optional
+from typing import Any, Dict, List, Literal, Optional, Union
 from pydantic import BaseModel, Field
 
 from .calibration_risk import StopConfigSchema, RiskConfigSchema, GlobalRiskRulesSchema
 
 
+ParameterValue = Union[int, float, bool, str]
+
+
 class WalkForwardConfigSchema(BaseModel):
     train_days: int = Field(..., gt=0)
     test_days: int = Field(..., gt=0)
-    step_days: Optional[int] = Field(None, gt=0)  # if None => step = test_days
+    step_days: Optional[int] = Field(None, gt=0)
-
-
-class OptimizationConfigSchema(BaseModel):
-    optimizer_metric: str = Field("sharpe_ratio")
-    max_combinations: int = Field(500, gt=0)
-    min_trades_train: int = Field(30, ge=0)
     min_trades_test: int = Field(10, ge=0)
 
 
-class ParameterRangeSchema(BaseModel):
-    min: float
-    max: float
-    step: float
-
-
 class StrategySelectionSchema(BaseModel):
     strategy_id: str
-    parameters: Dict[str, ParameterRangeSchema]
+    parameters: Dict[str, ParameterValue]
 
 
 class CalibrationStrategiesInspectRequest(BaseModel):
@@ -42,7 +33,6 @@ class CalibrationStrategiesInspectRequest(BaseModel):
 
     strategies: List[StrategySelectionSchema]
     wf: WalkForwardConfigSchema
-    optimization: OptimizationConfigSchema
 
     commission: float = Field(0.001, ge=0)
     slippage: float = Field(0.0005, ge=0)

src/web/ui/v2/templates/pages/calibration/calibration_strategies.html

@@ -187,7 +187,7 @@
   <!-- ========================= -->
   <div class="card mb-4">
     <div class="card-header">
-      <h3 class="card-title">Walk-Forward & Optimization</h3>
+      <h3 class="card-title">Walk-Forward Validation (OOS)</h3>
     </div>
     <div class="card-body">
       <div class="row g-3">
@@ -203,26 +203,10 @@
           <label class="form-label">Step days (optional)</label>
           <input id="wf_step_days" class="form-control" type="number" step="1" value="">
         </div>
-        <div class="col-md-3">
-          <label class="form-label">Metric</label>
-          <select id="opt_metric" class="form-select">
-            <option value="sharpe_ratio">sharpe_ratio</option>
-            <option value="total_return">total_return</option>
-            <option value="max_drawdown">max_drawdown</option>
-          </select>
-        </div>
 
         <div class="col-md-3">
-          <label class="form-label">Max combinations</label>
+          <label class="form-label">Min trades per window (test)</label>
-          <input id="opt_max_combinations" class="form-control" type="number" step="1" value="300">
+          <input id="wf_min_trades_test" class="form-control" type="number" step="1" value="10">
-        </div>
-        <div class="col-md-3">
-          <label class="form-label">Min trades (train)</label>
-          <input id="opt_min_trades_train" class="form-control" type="number" step="1" value="30">
-        </div>
-        <div class="col-md-3">
-          <label class="form-label">Min trades (test)</label>
-          <input id="opt_min_trades_test" class="form-control" type="number" step="1" value="10">
         </div>
 
         <div class="col-md-3">
@@ -262,7 +246,7 @@
         </small>
       </div>
       <div class="mt-3 text-secondary">
-        Cada estrategia incluye un <b>param_grid</b> en JSON.
+        Cada estrategia utiliza parámetros fijos (validación OOS sin grid).
       </div>
     </div>
   </div>

src/web/ui/v2/templates/pages/calibration/calibration_strategies.txt

@@ -0,0 +1,366 @@
+{% extends "layout.html" %}
+
+{% block content %}
+<div class="container-xl">
+
+  <!-- ========================= -->
+  <!-- Wizard header -->
+  <!-- ========================= -->
+  <div class="d-flex align-items-center mb-4">
+
+    <!-- Back arrow -->
+    <div class="me-3">
+      <a href="/calibration/risk" class="btn btn-outline-secondary btn-icon">
+        <svg xmlns="http://www.w3.org/2000/svg"
+            class="icon icon-tabler icon-tabler-arrow-left"
+            width="24" height="24" viewBox="0 0 24 24"
+            stroke-width="2" stroke="currentColor"
+            fill="none" stroke-linecap="round" stroke-linejoin="round">
+          <path stroke="none" d="M0 0h24v24H0z"/>
+          <path d="M15 6l-6 6l6 6"/>
+        </svg>
+      </a>
+    </div>
+
+    <div class="flex-grow-1 text-center">
+      <h2 class="mb-0">Calibración · Paso 3 · Strategies</h2>
+      <div class="text-secondary">Optimización + Walk Forward (OOS)</div>
+    </div>
+
+    <!-- Forward arrow (disabled until OK) -->
+    <div class="ms-3">
+      <a
+        id="next-step-btn"
+        href="#"
+        class="btn btn-outline-secondary btn-icon"
+        aria-disabled="true"
+        title="Next step not implemented yet"
+      >
+        <svg xmlns="http://www.w3.org/2000/svg"
+            class="icon icon-tabler icon-tabler-arrow-right"
+            width="24" height="24" viewBox="0 0 24 24"
+            stroke-width="2" stroke="currentColor"
+            fill="none" stroke-linecap="round" stroke-linejoin="round">
+          <path stroke="none" d="M0 0h24v24H0z"/>
+          <path d="M9 6l6 6l-6 6"/>
+        </svg>
+      </a>
+    </div>
+
+  </div>
+
+  <!-- ========================= -->
+  <!-- Context -->
+  <!-- ========================= -->
+  <div class="card mb-4">
+    <div class="card-header">
+      <h3 class="card-title">Context</h3>
+    </div>
+    <div class="card-body">
+      <div class="row g-3">
+        <div class="col-md-4">
+          <label class="form-label">Symbol</label>
+          <input id="symbol" class="form-control" placeholder="BTC/USDT">
+        </div>
+        <div class="col-md-4">
+          <label class="form-label">Timeframe</label>
+          <input id="timeframe" class="form-control" placeholder="1h">
+        </div>
+        <div class="col-md-4">
+          <label class="form-label">Account equity</label>
+          <input id="account_equity" class="form-control" type="number" step="0.01" value="10000">
+        </div>
+      </div>
+      <div class="mt-3 text-secondary">
+        Tip: Symbol y timeframe se cargan desde Step 1 (localStorage). Si no aparecen, rellénalos manualmente.
+      </div>
+    </div>
+  </div>
+
+  <!-- ========================= -->
+  <!-- Risk & Stops -->
+  <!-- ========================= -->
+  <div class="card mb-4">
+    <div class="card-header d-flex justify-content-between align-items-center">
+      <h3 class="card-title mb-0">Risk & Stops(Step 2)</h3>
+
+      <div class="form-check form-switch m-0">
+        <input class="form-check-input" type="checkbox" id="lock_inherited" checked>
+        <label class="form-check-label" for="lock_inherited">
+          Bloquear parámetros heredados
+        </label>
+      </div>
+    </div>
+
+  <div class="card-body">
+
+    <!-- ================= -->
+    <!-- Risk Configuration -->
+    <!-- ================= -->
+    <h4 class="mb-3">Risk Configuration</h4>
+
+    <div class="row g-3 mb-4">
+      <div class="col-md-4">
+        <label class="form-label">Risk per Trade (%)</label>
+        <input id="risk_fraction" class="form-control inherited-field" type="number" step="0.01">
+      </div>
+
+      <div class="col-md-4">
+        <label class="form-label">Max Position Size (%)</label>
+        <input id="max_position_fraction" class="form-control inherited-field" type="number" step="0.1">
+      </div>
+    </div>
+
+    <!-- ================= -->
+    <!-- Stop Configuration -->
+    <!-- ================= -->
+    <h4 class="mb-3">Stop Configuration</h4>
+
+    <div class="row g-3 mb-4">
+
+      <div class="col-md-4">
+        <label class="form-label">Stop Type</label>
+        <select id="stop_type" class="form-select inherited-field">
+          <option value="fixed">fixed</option>
+          <option value="trailing">trailing</option>
+          <option value="atr">atr</option>
+        </select>
+      </div>
+
+      <div id="stop_fraction_group" class="col-md-4">
+        <label class="form-label">Stop fraction (%)</label>
+        <input id="stop_fraction" class="form-control inherited-field" type="number" step="0.01">
+      </div>
+
+      <div id="atr_group" class="col-md-4 d-none">
+        <label class="form-label">ATR period</label>
+        <input id="atr_period" class="form-control inherited-field" type="number">
+      </div>
+
+      <div id="atr_multiplier_group" class="col-md-4 d-none">
+        <label class="form-label">ATR multiplier</label>
+        <input id="atr_multiplier" class="form-control inherited-field" type="number" step="0.1">
+      </div>
+
+    </div>
+
+
+    <!-- ================= -->
+    <!-- Global Rules -->
+    <!-- ================= -->
+    <h4 class="mb-3">Global Rules</h4>
+
+    <div class="row g-3 mb-4">
+      <div class="col-md-4">
+        <label class="form-label">Max Drawdown (%)</label>
+        <input id="max_drawdown_pct" class="form-control inherited-field" type="number" step="0.1">
+      </div>
+    </div>
+
+    <!-- ================= -->
+    <!-- Optional Parameters -->
+    <!-- ================= -->
+    <h4 class="mb-3">Optional Parameters</h4>
+
+    <div class="row g-3">
+      <div class="col-md-4">
+        <label class="form-label">Daily loss limit (%)</label>
+        <input id="daily_loss_limit_pct" class="form-control optional-field" type="number" step="0.1">
+      </div>
+
+      <div class="col-md-4">
+        <label class="form-label">Max consecutive losses</label>
+        <input id="max_consecutive_losses" class="form-control optional-field" type="number">
+      </div>
+
+      <div class="col-md-4">
+        <label class="form-label">Cooldown bars</label>
+        <input id="cooldown_bars" class="form-control optional-field" type="number">
+      </div>
+    </div>
+
+  </div>
+</div>
+
+  <!-- ========================= -->
+  <!-- WF + Optimizer config -->
+  <!-- ========================= -->
+  <div class="card mb-4">
+    <div class="card-header">
+      <h3 class="card-title">Walk-Forward & Optimization</h3>
+    </div>
+    <div class="card-body">
+      <div class="row g-3">
+        <div class="col-md-3">
+          <label class="form-label">Train days</label>
+          <input id="wf_train_days" class="form-control" type="number" step="1" value="120">
+        </div>
+        <div class="col-md-3">
+          <label class="form-label">Test days</label>
+          <input id="wf_test_days" class="form-control" type="number" step="1" value="30">
+        </div>
+        <div class="col-md-3">
+          <label class="form-label">Step days (optional)</label>
+          <input id="wf_step_days" class="form-control" type="number" step="1" value="">
+        </div>
+        <div class="col-md-3">
+          <label class="form-label">Metric</label>
+          <select id="opt_metric" class="form-select">
+            <option value="sharpe_ratio">sharpe_ratio</option>
+            <option value="total_return">total_return</option>
+            <option value="max_drawdown">max_drawdown</option>
+          </select>
+        </div>
+
+        <div class="col-md-3">
+          <label class="form-label">Max combinations</label>
+          <input id="opt_max_combinations" class="form-control" type="number" step="1" value="300">
+        </div>
+        <div class="col-md-3">
+          <label class="form-label">Min trades (train)</label>
+          <input id="opt_min_trades_train" class="form-control" type="number" step="1" value="30">
+        </div>
+        <div class="col-md-3">
+          <label class="form-label">Min trades (test)</label>
+          <input id="opt_min_trades_test" class="form-control" type="number" step="1" value="10">
+        </div>
+
+        <div class="col-md-3">
+          <label class="form-label">Commission</label>
+          <input id="commission" class="form-control" type="number" step="0.0001" value="0.001">
+        </div>
+        <div class="col-md-3">
+          <label class="form-label">Slippage</label>
+          <input id="slippage" class="form-control" type="number" step="0.0001" value="0.0005">
+        </div>
+      </div>
+    </div>
+  </div>
+
+  <!-- ========================= -->
+  <!-- Strategy selection -->
+  <!-- ========================= -->
+  <div class="card mb-4">
+    <div class="card-header">
+      <h3 class="card-title">Strategies</h3>
+      <div class="card-actions">
+        <button id="refresh_strategies_btn" class="btn btn-sm btn-outline-secondary">Refresh</button>
+      </div>
+    </div>
+    <div class="card-body">
+      <div id="strategies_container" class="d-flex flex-column gap-4"></div>
+      <div class="card p-3">
+        <div class="d-flex justify-content-between">
+          <strong>Total combinations</strong>
+          <span id="combination_counter">0</span>
+        </div>
+      </div>
+      <div class="mt-2 text-end">
+        <small class="text-muted">
+          Estimated WF time:
+          <span id="wf_time_estimate">~ 0 sec</span>
+        </small>
+      </div>
+      <div class="mt-3 text-secondary">
+        Cada estrategia incluye un <b>param_grid</b> en JSON.
+      </div>
+    </div>
+  </div>
+
+  <!-- ========================= -->
+  <!-- Actions -->
+  <!-- ========================= -->
+  <div class="d-flex gap-2 mb-4">
+    <button id="validate_strategies_btn" class="btn btn-primary">
+      Validate (WF)
+    </button>
+    <button id="report_strategies_btn" class="btn btn-outline-primary">
+      Generate PDF report
+    </button>
+  </div>
+
+  <!-- ========================= -->
+  <!-- Prograss Bar -->
+  <!-- ========================= -->
+  <div id="wf_progress_card" class="card mb-4">
+    <div class="card-header">
+      <h3 class="card-title">Walk-Forward Progress</h3>
+    </div>
+    <div class="card-body">
+
+      <div class="progress mb-2">
+        <div
+          id="wfProgressBar"
+          class="progress-bar progress-bar-striped progress-bar-animated"
+          role="progressbar"
+          style="width: 0%"
+        >
+          0%
+        </div>
+      </div>
+
+      <div id="wf_progress_text" class="text-secondary small">
+        Waiting to start...
+      </div>
+
+    </div>
+  </div>
+
+  <!-- ========================= -->
+  <!-- Results -->
+  <!-- ========================= -->
+  <div class="card mb-4">
+    <div class="card-header">
+      <h3 class="card-title">Results</h3>
+      <div class="card-actions">
+        <span id="strategies_status_badge" class="badge bg-secondary">—</span>
+      </div>
+    </div>
+    <div class="card-body">
+      <div id="strategies_message" class="mb-3 text-secondary">Run validation to see results.</div>
+
+      <div class="row g-3">
+        <div class="col-md-4">
+          <label class="form-label">Strategy plot</label>
+          <select id="plot_strategy_select" class="form-select"></select>
+        </div>
+      </div>
+
+      <div class="mt-3">
+        <div id="plot_equity" style="height: 320px;"></div>
+      </div>
+      <div class="mt-3">
+        <div id="plot_returns" style="height: 320px;"></div>
+      </div>
+
+      <hr class="my-4">
+
+      <div id="strategies_table_wrap"></div>
+
+      <details class="mt-3">
+        <summary class="text-secondary">Debug JSON</summary>
+        <pre id="strategies_debug" class="mt-2" style="max-height: 300px; overflow:auto;"></pre>
+      </details>
+    </div>
+  </div>
+
+  <!-- ========================= -->
+  <!-- PDF Viewer -->
+  <!-- ========================= -->
+  <div id="pdf_viewer_section" class="card mb-4 d-none">
+    <div class="card-header">
+      <h3 class="card-title">Strategies Report (PDF)</h3>
+      <div class="card-actions">
+        <button id="close_pdf_btn" class="btn btn-sm btn-outline-secondary">Close</button>
+      </div>
+    </div>
+    <div class="card-body">
+      <iframe id="pdf_frame" style="width: 100%; height: 800px; border: none;"></iframe>
+    </div>
+  </div>
+
+</div>
+
+<script src="https://cdn.plot.ly/plotly-2.27.0.min.js"></script>
+<script src="/static/js/pages/calibration_strategies.js"></script>
+{% endblock %}