mirror of
https://github.com/shawnkim1997/All-in-one-Financial-Analysis.git
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91 lines
4.5 KiB
Python
91 lines
4.5 KiB
Python
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"""
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UI helper functions for rendering analyst consensus, sensitivity tables, etc.
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"""
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import pandas as pd
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import streamlit as st
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from utils.dcf import excel_style_dcf
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def _render_analyst_consensus(ticker: str):
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"""Render analyst consensus rating with visual badge and target prices."""
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from data.valuation import get_analyst_consensus
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consensus = get_analyst_consensus(ticker)
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if not consensus:
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st.caption("Analyst consensus data not available.")
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return
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rec = (consensus.get("recommendationKey") or "N/A").upper()
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target_mean = consensus.get("targetMeanPrice")
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target_high = consensus.get("targetHighPrice")
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target_low = consensus.get("targetLowPrice")
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num_analysts = consensus.get("numberOfAnalystOpinions", "N/A")
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current = consensus.get("currentPrice")
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# Rating badge colors
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if rec in ("BUY", "STRONG_BUY", "STRONG BUY"):
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badge_bg = "rgba(52, 211, 153, 0.15)"
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badge_border = "rgba(52, 211, 153, 0.4)"
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badge_color = "#34D399"
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elif rec in ("SELL", "STRONG_SELL", "STRONG SELL"):
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badge_bg = "rgba(248, 113, 113, 0.15)"
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badge_border = "rgba(248, 113, 113, 0.4)"
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badge_color = "#F87171"
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else:
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badge_bg = "rgba(251, 191, 36, 0.15)"
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badge_border = "rgba(251, 191, 36, 0.4)"
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badge_color = "#FBBF24"
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rec_display = rec.replace("_", " ")
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upside = ""
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if target_mean and current and current > 0:
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upside_pct = (target_mean - current) / current * 100
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upside_color = "#34D399" if upside_pct > 0 else "#F87171"
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upside = f'<span style="color: {upside_color}; font-family: JetBrains Mono, monospace; font-weight: 600; margin-left: 12px;">{upside_pct:+.1f}% implied</span>'
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if target_mean:
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st.markdown(f"""
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<div style="display: flex; align-items: center; gap: 16px; padding: 16px; background: rgba(255,255,255,0.03); border: 1px solid rgba(255,255,255,0.06); border-radius: 10px; margin-bottom: 12px;">
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<div>
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<div style="color: #6B7280; font-size: 0.65rem; font-weight: 600; letter-spacing: 1px; text-transform: uppercase;">ANALYST RATING</div>
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<span style="display: inline-block; padding: 4px 14px; border-radius: 6px; font-weight: 700; font-family: JetBrains Mono, monospace; background: {badge_bg}; border: 1px solid {badge_border}; color: {badge_color}; font-size: 1.1rem; margin-top: 4px;">{rec_display}</span>
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{upside}
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</div>
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<div style="margin-left: auto; display: flex; gap: 24px;">
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<div style="text-align: center;">
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<div style="color: #6B7280; font-size: 0.6rem; letter-spacing: 1px;">TARGET (MEAN)</div>
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<div style="color: #F3F4F6; font-size: 1.1rem; font-family: JetBrains Mono, monospace; font-weight: 700;">${target_mean:,.2f}</div>
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</div>
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<div style="text-align: center;">
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<div style="color: #6B7280; font-size: 0.6rem; letter-spacing: 1px;">HIGH</div>
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<div style="color: #34D399; font-size: 0.95rem; font-family: JetBrains Mono, monospace;">${target_high:,.2f}</div>
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</div>
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<div style="text-align: center;">
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<div style="color: #6B7280; font-size: 0.6rem; letter-spacing: 1px;">LOW</div>
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<div style="color: #F87171; font-size: 0.95rem; font-family: JetBrains Mono, monospace;">${target_low:,.2f}</div>
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</div>
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<div style="text-align: center;">
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<div style="color: #6B7280; font-size: 0.6rem; letter-spacing: 1px;">ANALYSTS</div>
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<div style="color: #D1D5DB; font-size: 0.95rem; font-family: JetBrains Mono, monospace;">{num_analysts}</div>
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</div>
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</div>
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</div>
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""", unsafe_allow_html=True)
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else:
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st.caption("Analyst targets not available.")
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def _render_sensitivity_table(fcf: float, total_debt: float, cash: float, shares: float):
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"""Render DCF sensitivity table: WACC vs Terminal Growth Rate."""
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wacc_range = [0.065, 0.070, 0.075, 0.080, 0.085, 0.090, 0.095, 0.100]
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tgr_range = [0.020, 0.025, 0.030, 0.035, 0.040]
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rows = []
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for tgr in tgr_range:
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row = {"TGR": f"{tgr*100:.1f}%"}
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for w in wacc_range:
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res = excel_style_dcf(fcf, w, tgr, 0.10, total_debt, cash, shares)
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val = res.get("value_per_share", 0)
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row[f"{w*100:.1f}%"] = f"${val:,.0f}" if val and val > 0 else "N/A"
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rows.append(row)
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return pd.DataFrame(rows).set_index("TGR")
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