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3 changes: 3 additions & 0 deletions .Jules/palette.md
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## 2024-03-07 - Accessible Statistical/Financial Input Tooltips
**Learning:** This application involves highly technical inputs (e.g., basis points, daily volume percentiles, rolling quantiles) that are obscure to less experienced users. Providing concrete, relatable examples inside the native Streamlit `help` parameter makes the interface significantly more intuitive and usable.
**Action:** Always include concrete numeric examples (e.g., "10 bps = 0.10%", "21 days = 1 month") when adding or modifying statistical or financial input parameters across the design system.
46 changes: 40 additions & 6 deletions src/dashboard.py
Original file line number Diff line number Diff line change
Expand Up @@ -168,29 +168,63 @@ def get_cache_key(*args) -> str:
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)
factor_window = st.slider(
"Factor Beta Window (days)",
20,
252,
63,
7,
help="Rolling window for calculating beta to risk factors (e.g., 63 days = 3 months).",
)
vol_window = st.slider(
"Regime Vol Window (days)",
10,
60,
21,
5,
help="Rolling window for calculating realized volatility (e.g., 21 days = 1 month).",
)
adv_pct = st.slider(
"ADV Participation %",
0.01,
0.30,
float(DEFAULT_ADV_PCT),
0.01,
help="Target percentage of Average Daily Volume for trading (e.g., 0.10 = 10% 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("βœ“ 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
"High Volatility Quantile",
0.5,
0.95,
DEFAULT_VOL_QUANTILE_HIGH,
0.05,
help="Threshold for defining 'High' volatility regime (e.g., 0.75 = top 25% of historical volatility).",
)

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="Cost per trade in basis points (e.g., 10 bps = 0.10%).",
)
/ 10000
)
allow_short = st.checkbox("Allow Short Selling?", value=False)
else:
st.subheader("5. Alert Thresholds")
Expand Down
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