{signal_icon}
{signal_text}
Price: {latest['close']:.2f} | RSI: {rsi_val:.1f} | ATR%: {atr_val:.4f}%
""", unsafe_allow_html=True)
else:
st.error(f"Could not load data for {pair}.")
st.markdown("---")
# โโโ Equity Curve โโโ
st.subheader("๐ฐ Equity Curve")
if data is not None:
df = data.copy()
df["returns"] = df["close"].pct_change()
df["strategy_returns"] = df["position"].shift(1) * df["returns"]
df["equity"] = 10000 * (1 + df["strategy_returns"]).cumprod()
df["buy_hold"] = 10000 * (1 + df["returns"]).cumprod()
fig = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.05, row_heights=[0.7, 0.3])
fig.add_trace(go.Scatter(x=df["time"], y=df["equity"], line=dict(color=COLORS["green"], width=2), name="Strategy"), row=1, col=1)
fig.add_trace(go.Scatter(x=df["time"], y=df["buy_hold"], line=dict(color="#9E9E9E", width=1, dash="dash"), name="Buy & Hold"), row=1, col=1)
peak = df["equity"].expanding().max()
dd = (df["equity"] - peak) / peak * 100
fig.add_trace(go.Scatter(x=df["time"], y=dd, fill="tozeroy", line=dict(color=COLORS["red"], width=1), name="Drawdown"), row=2, col=1)
fig.update_layout(height=350, template="plotly_dark", hovermode="x unified",
margin=dict(l=0, r=0, t=10, b=0), legend=dict(orientation="h", y=1.02, x=0))
st.plotly_chart(fig, width="stretch")
st.markdown("---")
# โโโ Recent Signals โโโ
st.subheader("๐ Recent Activity")
if data is not None:
col1, col2 = st.columns(2)
with col1:
sig_cols = ["time", "close", "rsi", "atr_pct", "signal"]
if is_gold:
sig_cols += ["sl_price", "tp_price", "exit_reason"]
else:
sig_cols += ["position"]
recent = data[sig_cols].tail(30).copy()
recent["signal"] = recent["signal"].map({1: "๐ข BUY", -1: "๐ด SELL", 0: "โช"})
if is_gold and "exit_reason" in recent.columns:
recent["exit_reason"] = recent["exit_reason"].replace("", "-")
recent = recent.rename(columns={"time": "Time", "close": "Price", "rsi": "RSI",
"atr_pct": "ATR%", "signal": "Signal",
"sl_price": "SL", "tp_price": "TP", "exit_reason": "Exit"})
recent["Time"] = recent["Time"].dt.strftime("%H:%M")
recent["Price"] = recent["Price"].round(2)
recent["SL"] = recent["SL"].round(2)
recent["TP"] = recent["TP"].round(2)
display_cols = ["Time", "Price", "RSI", "Signal", "SL", "TP", "Exit"]
else:
recent = recent.rename(columns={"time": "Time", "close": "Price", "rsi": "RSI",
"atr_pct": "ATR%", "signal": "Signal"})
recent["Time"] = recent["Time"].dt.strftime("%H:%M" if tf in ("1m","5m","15m","30m") else "%m/%d %H:%M")
recent["Price"] = recent["Price"].round(5) if not is_gold else recent["Price"]
display_cols = ["Time", "Price", "RSI", "ATR%", "Signal"]
st.markdown("**Recent candles & signals**")
st.dataframe(recent[display_cols], width="stretch", hide_index=True)
with col2:
if is_gold and not data[data["signal"] != 0].empty:
signals = data[data["signal"] != 0].tail(20).copy()
st.markdown("**Trade exits breakdown**")
exit_data = signals[signals["exit_reason"] != ""].copy()
if not exit_data.empty:
exit_data["hold_bars"] = 0
for i in range(len(exit_data)):
idx = exit_data.index[i]
prev_sig = signals[signals.index < idx]
if not prev_sig.empty:
entry_idx = prev_sig.index[-1]
exit_data.loc[idx, "hold_bars"] = signals.index.get_loc(idx) - signals.index.get_loc(entry_idx)
exit_data["entry_time"] = ""
for i in range(len(exit_data)):
idx = exit_data.index[i]
prev = signals[signals.index < idx]
if not prev.empty:
exit_data.loc[idx, "entry_time"] = prev.iloc[-1]["time"]
exit_display = exit_data[["time", "close", "exit_reason"]].tail(10).copy()
exit_display["time"] = exit_display["time"].dt.strftime("%H:%M")
exit_display = exit_display.rename(columns={"time": "Time", "close": "Price", "exit_reason": "Exit"})
st.dataframe(exit_display, width="stretch", hide_index=True)
else:
st.info("No exits yet in recent data.")
else:
st.markdown("**Strategy metrics**")
if perf:
cols_left, cols_right = st.columns(2)
perf_items = [(k, v) for k, v in perf.items() if not isinstance(v, dict)]
mid = len(perf_items) // 2
with cols_left:
for k, v in perf_items[:mid]:
st.metric(k.replace("_", " ").title(), v)
with cols_right:
for k, v in perf_items[mid:]:
st.metric(k.replace("_", " ").title(), v)
# Footer
st.markdown("---")
st.caption("""
**XAU Scalp Monitor** โ Data: Yahoo Finance | Strategy: Gold Scalping (5-15 min holds)
Deployed on Streamlit Community Cloud ยท Fully automated ยท Free forever
""")