/ with color: var(--brass-ink) to override Streamlit's fg-2 default Co-Authored-By: Claude Sonnet 4.6 --- components/valuation.py | 748 +++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 714 insertions(+), 34 deletions(-) (limited to 'components') diff --git a/components/valuation.py b/components/valuation.py index e2e4338..53be09c 100644 --- a/components/valuation.py +++ b/components/valuation.py @@ -460,18 +460,27 @@ def _build_model_context(ticker: str) -> dict: def _render_model_availability(ctx: dict): - st.markdown("**Applicable models**") - cols = st.columns(4) - cards = [ - ("DCF", ctx["dcf_available"], ctx["dcf_reason"]), - ("EV/EBITDA", ctx["ev_available"], ctx["ev_reason"]), - ("EV/Revenue", ctx["ev_revenue_available"], ctx["ev_revenue_reason"]), - ("P/B", ctx["pb_available"], ctx["pb_reason"]), - ] - for col, (label, available, reason) in zip(cols, cards): - col.markdown(f"**{label}**") - col.caption("Available" if available else "Not suitable") - col.write(reason) + dcf_ok = ctx["dcf_available"] + ev_ok = ctx["ev_available"] + rev_ok = ctx["ev_revenue_available"] + pb_ok = ctx["pb_available"] + pb_limited = pb_ok and not ctx["is_financial"] + pb_color = "#C49545" if pb_limited else ("#4F8C5E" if pb_ok else "#5E5849") + pb_glyph = "◐" if pb_limited else "●" + dcf_c = "#4F8C5E" if dcf_ok else "#5E5849" + ev_c = "#4F8C5E" if ev_ok else "#5E5849" + rev_c = "#4F8C5E" if rev_ok else "#5E5849" + st.markdown( + f'

+ +

+ Multiples +

Three relative-valuation lenses — implied per-share

Subject multiple × normalized TTM metric, bridged to equity per share. Compare across columns to see which lens the market is leaning on.

+ EV / EBITDA + {_fs(eb_per0)} + {_ds_span(eb_per0, 'id="sum-eb-d"')} +

+ EV / Revenue + {_fs(rv_per0)} + {_ds_span(rv_per0, 'id="sum-rv-d"')} +

+ P / Book + {_fs(pb_per0)} + {_ds_span(pb_per0, 'id="sum-pb-d"')} +

+ Market · last + {_fs(market) if has_market else "—"} + {ticker} · {exchange} +

+ +

Method comparison

+ USD · TTM metrics · balance-sheet bridge +

+ +

Method

EV / EBITDA

Strong fit

Enterprise value normalized by operating cash profit. Strips depreciation and capital structure so different capex profiles compare cleanly.

EV / Revenue

Strong fit

Topline multiple — useful when margins are volatile or the business is reinvesting through profitability. Less sensitive to one-off charges.

III

P / Book

{pb_fit_lbl}

Equity multiple — works for balance-sheet-heavy businesses (banks, insurers, REITs). Limited signal for asset-light software & services.

+ +

Subject multipledrag to flex the lens

{_fx(eb_init)}sector {_fx(eb_sector)}

+ + +

+ +

8×typical 14×–26×32×

{_fx(rv_init)}sector {_fx(rv_sector)}

+ + +

+ +

4×typical 6×–13×20×

{_fx(pb_init)}sector {_fx(pb_sector)}

+ + +

+ +

4×typical 8×–14×60×

+ +

× Normalized metricfrom TTM filings

{_fb(ebitda) if eb_ok else "—"}EBITDA · TTM

{_fb(revenue) if rv_ok else "—"}Revenue · TTM

{_fs(book_ps) if pb_ok else "—"}Book value · /share

+ +

= Enterprise value

{_fb(eb_ev0)}multiple × metric

{_fb(rv_ev0)}multiple × metric

—P/B is an equity multiple — no EV step

+ +

− Net debt

{_fb(net_debt)}total {_fb(total_debt)} − cash {_fb(cash)}

—

+ +

= Equity value

{_fb(eb_eq0)}EV − net debt

{_fb(rv_eq0)}EV − net debt

—

+ +

÷ Shares outstanding

{shares_str}diluted

—

+ +

= Implied per share

+ {_fs(eb_per0)} + {_d_span(eb_per0, 'id="eb-per-d"')} +

+ {_fs(rv_per0)} + {_d_span(rv_per0, 'id="rv-per-d"')} +

+ {_fs(pb_per0)} + {_d_span(pb_per0, 'id="pb-per-d"')} +

+ +

If the lens shifted to sector

+ Same metrics, subject multiple replaced by sector median +

+ +

+ EV / EBITDA +

+ At subject {_fx(eb_init)} + {_fs(eb_per0)} + {_ds_span(eb_per0, 'id="sens-eb-subj-d"')} +

+ → +

+ At sector {_fx(eb_sector)} + {_fs(sec_eb)} + {_ds_span(sec_eb)} +

+ Re-rating Δ {_rr(eb_per0, sec_eb)} per share if the subject converged to peers +

+ +

+ EV / Revenue +

+ At subject {_fx(rv_init)} + {_fs(rv_per0)} + {_ds_span(rv_per0, 'id="sens-rv-subj-d"')} +

+ → +

+ At sector {_fx(rv_sector)} + {_fs(sec_rv)} + {_ds_span(sec_rv)} +

+ Re-rating Δ {_rr(rv_per0, sec_rv)} per share if the subject converged to peers +

+ +

+ P / Book +

+ At subject {_fx(pb_init)} + {_fs(pb_per0)} + {_ds_span(pb_per0, 'id="sens-pb-subj-d"')} +

+ → +

+ At sector {_fx(pb_sector)} + {_fs(sec_pb)} + {_ds_span(sec_pb)} +

+ Re-rating Δ {_rr(pb_per0, sec_pb)} per share if the subject converged to peers +

+ +

Cross-check against DCF

+ DCF intrinsic from the firm-value model on the previous tab +

+ DCF · firm value + {dcf_val_str} + {dcf_delta_html} + {dcf_meta_str} +

+ EV / EBITDA + {_fs(eb_per0)} + {_d_span(eb_per0, 'id="cx-eb-d"')} + Subject {_fx(eb_init)} · sector {_fx(eb_sector)} +

+ EV / Revenue + {_fs(rv_per0)} + {_d_span(rv_per0, 'id="cx-rv-d"')} + Subject {_fx(rv_init)} · sector {_fx(rv_sector)} +

+ P / Book + {_fs(pb_per0)} + {_d_span(pb_per0, 'id="cx-pb-d"')} + Subject {_fx(pb_init)} · sector {_fx(pb_sector)} · low-signal +

+ +

+ Multiples · TTM metrics, balance sheet. Net-debt adjustment applies to EV-based methods only; P/B reads directly off book equity per share. Sector medians from peer group analysis. + Methodology & sources ↗ +

+ +