🎨 Palette: Add Tooltips for Financial Parameters

.Jules/palette.md

@@ -0,0 +1,3 @@
+## 2024-05-24 - Clarifying Abstract Financial Inputs
+**Learning:** Inputs requiring niche domain knowledge (like basis points or ADV metrics) often confuse general users without concrete examples. Using `help=` with explicit mathematical conversions ("10 bps = 0.10%") significantly improves input comprehension.
+**Action:** Always include concrete numeric examples in tooltips when an input deals with domain-specific statistical or financial parameters.

src/dashboard.py

@@ -160,37 +160,58 @@ def get_cache_key(*args) -> str:
     st.subheader("3. Signal Parameters")
     if mode == "Single-Asset":
         sma_window = st.slider(
-            "Trend SMA Window", 10, 200, DEFAULT_SMA_WINDOW, 10,
-            help="Lookback days for Simple Moving Average trend signal."
+            "Trend SMA Window",
+            10,
+            200,
+            DEFAULT_SMA_WINDOW,
+            10,
+            help="Lookback days for Simple Moving Average trend signal.",
         )
         mom_window = st.slider(
-            "Momentum Lookback (Months)", 1, 24, DEFAULT_MOMENTUM_WINDOW, 1,
-            help="Lookback months for Momentum signal."
+            "Momentum Lookback (Months)",
+            1,
+            24,
+            DEFAULT_MOMENTUM_WINDOW,
+            1,
+            help="Lookback months for Momentum signal.",
         )
     else:
         factor_window = st.slider("Factor Beta Window (days)", 20, 252, 63, 7)
         vol_window = st.slider("Regime Vol Window (days)", 10, 60, 21, 5)
-        adv_pct = st.slider("ADV Participation %", 0.01, 0.30, float(DEFAULT_ADV_PCT), 0.01)
+        adv_pct = st.slider(
+            "ADV Participation %",
+            0.01,
+            0.30,
+            float(DEFAULT_ADV_PCT),
+            0.01,
+            help="Max percentage of Average Daily Volume to trade. e.g., 0.05 = 5% of daily volume.",
+        )
 
     st.markdown("---")
     st.subheader("4. Research Rigor")
     use_oos = st.toggle(
         "Out-of-Sample Mode",
         value=False,
-        help="Uses expanding-window quantiles for regime classification to avoid look-ahead bias. Enable for rigorous backtesting."
+        help="Uses expanding-window quantiles for regime classification to avoid look-ahead bias. Enable for rigorous backtesting.",
     )
     if use_oos:
         st.success("✓ Look-ahead bias removed")
     else:
         st.info("Using full-sample quantiles (exploratory mode)")
 
-    vol_q_high = st.slider(
-        "High Volatility Quantile", 0.5, 0.95, DEFAULT_VOL_QUANTILE_HIGH, 0.05
-    )
+    vol_q_high = st.slider("High Volatility Quantile", 0.5, 0.95, DEFAULT_VOL_QUANTILE_HIGH, 0.05)
 
     if mode == "Single-Asset":
         st.subheader("5. Backtest Settings")
-        bt_cost = st.number_input("Transaction Cost (bps)", value=DEFAULT_COST_BPS, step=1) / 10000
+        bt_cost = (
+            st.number_input(
+                "Transaction Cost (bps)",
+                value=DEFAULT_COST_BPS,
+                step=1,
+                help="10 bps = 0.10%. Represents slippage and execution costs per trade.",
+            )
+            / 10000
+        )
         allow_short = st.checkbox("Allow Short Selling?", value=False)
     else:
         st.subheader("5. Alert Thresholds")