diff --git a/.env b/.env
index 9abb4ae..2f7e309 100644
--- a/.env
+++ b/.env
@@ -63,7 +63,7 @@ TIME_SERIES_MIN_CANDLES=120
 TIME_SERIES_FORECAST_HORIZON=3
 TIME_SERIES_MIN_EDGE_PERCENT=0.10
 TIME_SERIES_MIN_PROBABILITY_UP=0.52
-TIME_SERIES_MIN_CONFIDENCE=0.72
+TIME_SERIES_MIN_CONFIDENCE=0.4
 TIME_SERIES_MAX_ADJUSTMENT=0.08
 TIME_SERIES_LSTM_ENABLED=true
 TIME_SERIES_LSTM_MODEL_PATH=runtime/lstm_forecaster.json
diff --git a/.env.example b/.env.example
index f8b8df0..8355f41 100644
--- a/.env.example
+++ b/.env.example
@@ -63,7 +63,7 @@ TIME_SERIES_MIN_CANDLES=120
 TIME_SERIES_FORECAST_HORIZON=3
 TIME_SERIES_MIN_EDGE_PERCENT=0.08
 TIME_SERIES_MIN_PROBABILITY_UP=0.58
-TIME_SERIES_MIN_CONFIDENCE=0.72
+TIME_SERIES_MIN_CONFIDENCE=0.4
 TIME_SERIES_MAX_ADJUSTMENT=0.08
 TIME_SERIES_LSTM_ENABLED=true
 TIME_SERIES_LSTM_MODEL_PATH=runtime/lstm_forecaster.json
diff --git a/README.md b/README.md
index 33d9582..a537717 100644
--- a/README.md
+++ b/README.md
@@ -161,7 +161,7 @@ TIME_SERIES_MIN_CANDLES=120
 TIME_SERIES_FORECAST_HORIZON=3
 TIME_SERIES_MIN_EDGE_PERCENT=0.08
 TIME_SERIES_MIN_PROBABILITY_UP=0.58
-TIME_SERIES_MIN_CONFIDENCE=0.72
+TIME_SERIES_MIN_CONFIDENCE=0.4
 TIME_SERIES_MAX_ADJUSTMENT=0.08
 TIME_SERIES_LSTM_ENABLED=true
 TIME_SERIES_LSTM_MODEL_PATH=runtime/lstm_forecaster.json
diff --git a/crypto_spot_bot/config.py b/crypto_spot_bot/config.py
index 695524f..a08894d 100644
--- a/crypto_spot_bot/config.py
+++ b/crypto_spot_bot/config.py
@@ -262,7 +262,7 @@ def load_settings(env_file: str | Path | None = None) -> Settings:
         time_series_forecast_horizon=_int_env("TIME_SERIES_FORECAST_HORIZON", 3),
         time_series_min_edge_percent=_float_env("TIME_SERIES_MIN_EDGE_PERCENT", 0.08),
         time_series_min_probability_up=_float_env("TIME_SERIES_MIN_PROBABILITY_UP", 0.58),
-        time_series_min_confidence=_float_env("TIME_SERIES_MIN_CONFIDENCE", 0.72),
+        time_series_min_confidence=_float_env("TIME_SERIES_MIN_CONFIDENCE", 0.4),
         time_series_max_adjustment=_float_env("TIME_SERIES_MAX_ADJUSTMENT", 0.08),
         time_series_lstm_enabled=_bool_env("TIME_SERIES_LSTM_ENABLED", True),
         time_series_lstm_model_path=Path(os.getenv("TIME_SERIES_LSTM_MODEL_PATH", "runtime/lstm_forecaster.json")),
diff --git a/crypto_spot_bot/dashboard.py b/crypto_spot_bot/dashboard.py
index 79a76ec..421d225 100644
--- a/crypto_spot_bot/dashboard.py
+++ b/crypto_spot_bot/dashboard.py
@@ -698,6 +698,8 @@ HTML = r"""
       const forecast = market.forecast || {};
       const quality = market.quality || {};
       const signal = latestSignals[symbol] || {};
+      const minEdge = state.data.config?.time_series_min_edge_percent ?? 0;
+      const minConfidence = state.data.config?.time_series_min_confidence ?? 0;
       const diagnostics = parseDiagnostics(signal);
       const failed = Object.entries(diagnostics.checks || {}).filter(([, ok]) => !ok).map(([key]) => key);
       return panel(
@@ -712,8 +714,9 @@ HTML = r"""
           ])}
           ${kvTable([
             ['Model', modelName(forecast.model)],
-            ['Expected', signed(forecast.expected_return_percent, 4) + '%'],
+            ['Edge', `${signed(forecast.expected_return_percent, 4)}% / min ${num(minEdge, 3)}%`],
             ['P(up)', num((forecast.probability_up || 0) * 100, 2) + '%'],
+            ['Confidence', `${num(signal.confidence, 4)} / min ${num(minConfidence, 2)}`],
             ['Q10/Q50/Q90', `${signed(forecast.quantile_10_percent, 2)} / ${signed(forecast.quantile_50_percent, 2)} / ${signed(forecast.quantile_90_percent, 2)}`],
             ['Blocked', forecast.block_entry ? 'yes' : 'no']
           ])}
diff --git a/tests/conftest.py b/tests/conftest.py
index 38a699a..300a356 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -79,7 +79,7 @@ def make_settings():
             time_series_forecast_horizon=3,
             time_series_min_edge_percent=0.08,
             time_series_min_probability_up=0.58,
-            time_series_min_confidence=0.72,
+            time_series_min_confidence=0.4,
             time_series_max_adjustment=0.08,
             time_series_lstm_enabled=True,
             time_series_lstm_model_path=tmp_path / "lstm_forecaster.json",