Harden valuation edge cases

1 files changed, 168 insertions, 38 deletions

diff --git a/components/valuation.py b/components/valuation.py
index a72d177..72c8001 100644
--- a/components/valuation.py
+++ b/components/valuation.py
@@ -146,35 +146,138 @@ def _render_ratios(ticker: str):
         st.info("Ratio data unavailable.")
         return
 
-    def r(key, fmt=fmt_ratio):
+    def _normalized_label(label: str) -> str:
+        return " ".join(str(label).replace("/", " ").replace("-", " ").split()).strip().lower()
+
+    def _display_value(key: str, fmt=fmt_ratio):
         val = ratios.get(key) if ratios else None
         return fmt(val) if val is not None else "—"
 
+    def _company_context() -> dict:
+        return info or {}
+
+    def _display_reasoned_metric(key: str, fmt=fmt_ratio) -> str:
+        val = ratios.get(key) if ratios else None
+        if val is not None:
+            return fmt(val)
+
+        ctx = _company_context()
+
+        if key == "peRatioTTM":
+            trailing_pe = ctx.get("trailingPE")
+            if trailing_pe is not None:
+                return fmt_ratio(trailing_pe)
+            if ratios and ratios.get("netProfitMarginTTM") is not None and ratios.get("netProfitMarginTTM") < 0:
+                return "N/M (neg. TTM earnings)"
+            trailing_eps = ctx.get("trailingEps")
+            if trailing_eps is not None:
+                try:
+                    if float(trailing_eps) <= 0:
+                        return "N/M (neg. TTM earnings)"
+                except (TypeError, ValueError):
+                    pass
+            return "—"
+
+        if key == "priceToBookRatioTTM":
+            book_value = ctx.get("bookValue")
+            if book_value is not None:
+                try:
+                    if float(book_value) <= 0:
+                        return "N/M (neg. equity)"
+                except (TypeError, ValueError):
+                    pass
+            return "—"
+
+        if key == "enterpriseValueMultipleTTM":
+            ebitda = ratios.get("ebitdaTTM") if ratios else None
+            if ebitda is not None:
+                try:
+                    if float(ebitda) <= 0:
+                        return "N/M (neg. EBITDA)"
+                except (TypeError, ValueError):
+                    pass
+            return "—"
+
+        if key == "dividendPayoutRatioTTM":
+            payout_ratio = ctx.get("payoutRatio")
+            if payout_ratio is not None:
+                try:
+                    if float(payout_ratio) <= 0:
+                        return "—"
+                except (TypeError, ValueError):
+                    pass
+            if ratios and ratios.get("netProfitMarginTTM") is not None and ratios.get("netProfitMarginTTM") < 0:
+                return "N/M (neg. earnings)"
+            return "—"
+
+        if key == "returnOnEquityTTM":
+            book_value = ctx.get("bookValue")
+            if book_value is not None:
+                try:
+                    if float(book_value) <= 0:
+                        return "N/M (neg. equity)"
+                except (TypeError, ValueError):
+                    pass
+            return "—"
+
+        if key == "debtToEquityRatioTTM":
+            book_value = ctx.get("bookValue")
+            if book_value is not None:
+                try:
+                    if float(book_value) <= 0:
+                        return "N/M (neg. equity)"
+                except (TypeError, ValueError):
+                    pass
+            return "—"
+
+        if key == "interestCoverageRatioTTM":
+            operating_margins = ctx.get("operatingMargins")
+            if operating_margins is not None:
+                try:
+                    if float(operating_margins) <= 0:
+                        return "N/M (neg. EBIT)"
+                except (TypeError, ValueError):
+                    pass
+            return "—"
+
+        return "—"
+
+    def _dedupe_metrics(metrics: list[tuple[str, str]]) -> list[tuple[str, str]]:
+        deduped: list[tuple[str, str]] = []
+        seen_labels: set[str] = set()
+        for label, val in metrics:
+            norm = _normalized_label(label)
+            if norm in seen_labels:
+                continue
+            seen_labels.add(norm)
+            deduped.append((label, val))
+        return deduped
+
     rows = [
-        ("Valuation", [
-            ("P/E (TTM)", r("peRatioTTM")),
-            ("Forward P/E", r("forwardPE")),
-            ("P/S (TTM)", r("priceToSalesRatioTTM")),
-            ("P/B", r("priceToBookRatioTTM")),
-            ("EV/EBITDA", r("enterpriseValueMultipleTTM")),
-            ("EV/Revenue", r("evToSalesTTM")),
-        ]),
-        ("Profitability", [
-            ("Gross Margin", r("grossProfitMarginTTM", fmt=fmt_pct)),
-            ("Operating Margin", r("operatingProfitMarginTTM", fmt=fmt_pct)),
-            ("Net Margin", r("netProfitMarginTTM", fmt=fmt_pct)),
-            ("ROE", r("returnOnEquityTTM", fmt=fmt_pct)),
-            ("ROA", r("returnOnAssetsTTM", fmt=fmt_pct)),
-            ("ROIC", r("returnOnInvestedCapitalTTM", fmt=fmt_pct)),
-        ]),
-        ("Leverage & Liquidity", [
-            ("Debt/Equity", r("debtToEquityRatioTTM")),
-            ("Current Ratio", r("currentRatioTTM")),
-            ("Quick Ratio", r("quickRatioTTM")),
-            ("Interest Coverage", r("interestCoverageRatioTTM")),
-            ("Dividend Yield", r("dividendYieldTTM", fmt=fmt_pct)),
-            ("Payout Ratio", r("dividendPayoutRatioTTM", fmt=fmt_pct)),
-        ]),
+        ("Valuation", _dedupe_metrics([
+            ("P/E (TTM)", _display_reasoned_metric("peRatioTTM")),
+            ("Forward P/E", _display_value("forwardPE")),
+            ("P/S (TTM)", _display_value("priceToSalesRatioTTM")),
+            ("P/B", _display_reasoned_metric("priceToBookRatioTTM")),
+            ("EV/EBITDA", _display_reasoned_metric("enterpriseValueMultipleTTM")),
+            ("EV/Revenue", _display_value("evToSalesTTM")),
+        ])),
+        ("Profitability", _dedupe_metrics([
+            ("Gross Margin", _display_value("grossProfitMarginTTM", fmt=fmt_pct)),
+            ("Operating Margin", _display_value("operatingProfitMarginTTM", fmt=fmt_pct)),
+            ("Net Margin", _display_value("netProfitMarginTTM", fmt=fmt_pct)),
+            ("ROE", _display_reasoned_metric("returnOnEquityTTM", fmt=fmt_pct)),
+            ("ROA", _display_value("returnOnAssetsTTM", fmt=fmt_pct)),
+            ("ROIC", _display_value("returnOnInvestedCapitalTTM", fmt=fmt_pct)),
+        ])),
+        ("Leverage & Liquidity", _dedupe_metrics([
+            ("Debt/Equity", _display_reasoned_metric("debtToEquityRatioTTM")),
+            ("Current Ratio", _display_value("currentRatioTTM")),
+            ("Quick Ratio", _display_value("quickRatioTTM")),
+            ("Interest Coverage", _display_reasoned_metric("interestCoverageRatioTTM")),
+            ("Dividend Yield", _display_value("dividendYieldTTM", fmt=fmt_pct)),
+            ("Payout Ratio", _display_reasoned_metric("dividendPayoutRatioTTM", fmt=fmt_pct)),
+        ])),
     ]
 
     for section_name, metrics in rows:
@@ -463,14 +566,30 @@ def _render_comps(ticker: str):
     available = [c for c in ["symbol", "peRatioTTM", "priceToSalesRatioTTM", "priceToBookRatioTTM", "enterpriseValueMultipleTTM", "netProfitMarginTTM", "returnOnEquityTTM", "debtToEquityRatioTTM"] if c in df.columns]
     df = df[available].rename(columns=display_cols)
 
-    pct_cols = {"Net Margin", "ROE"}
+    def _format_comp_value(column: str, value):
+        if value is None:
+            return "—"
+        try:
+            v = float(value)
+        except (TypeError, ValueError):
+            return "—"
+
+        if column == "P/E":
+            return fmt_ratio(v) if v > 0 else "N/M (neg. earnings)"
+        if column == "P/B":
+            return fmt_ratio(v) if v > 0 else "N/M (neg. equity)"
+        if column == "EV/EBITDA":
+            return fmt_ratio(v) if v > 0 else "N/M (neg. EBITDA)"
+        if column == "D/E":
+            return fmt_ratio(v) if v >= 0 else "N/M (neg. equity)"
+        if column in {"Net Margin", "ROE"}:
+            return fmt_pct(v)
+        return fmt_ratio(v) if v > 0 else "—"
+
     for col in df.columns:
         if col == "Ticker":
             continue
-        if col in pct_cols:
-            df[col] = df[col].apply(lambda v: fmt_pct(v) if v is not None else "—")
-        else:
-            df[col] = df[col].apply(lambda v: fmt_ratio(v) if v is not None else "—")
+        df[col] = df[col].apply(lambda v, c=col: _format_comp_value(c, v))
 
     def highlight_subject(row):
         if row["Ticker"] == ticker.upper():
@@ -737,19 +856,30 @@ def _render_historical_ratios(ticker: str):
             primary, alt, fmt = _HIST_RATIO_OPTIONS[label]
             display_cols[label] = (primary, alt, fmt)
 
+        def _format_hist_value(label: str, value, fmt: str | None) -> str:
+            if value is None:
+                return "—"
+            try:
+                v = float(value)
+            except (TypeError, ValueError):
+                return "—"
+
+            if fmt == "pct":
+                return f"{v * 100:.2f}%"
+            if label == "P/E":
+                return f"{v:.2f}x" if v > 0 else "N/M (neg. earnings)"
+            if label == "EV/EBITDA":
+                return f"{v:.2f}x" if v > 0 else "N/M (neg. EBITDA)"
+            if label in {"P/B", "Debt/Equity"}:
+                return f"{v:.2f}x" if v > 0 else "N/M (neg. equity)"
+            return f"{v:.2f}x" if v > 0 else "—"
+
         table_rows = []
         for row in merged_rows:
             r: dict = {"Year": str(row.get("date", ""))[:4]}
             for label, (primary, alt, fmt) in display_cols.items():
                 val = row.get(primary) or (row.get(alt) if alt else None)
-                if val is not None:
-                    try:
-                        v = float(val)
-                        r[label] = f"{v * 100:.2f}%" if fmt == "pct" else f"{v:.2f}x"
-                    except (TypeError, ValueError):
-                        r[label] = "—"
-                else:
-                    r[label] = "—"
+                r[label] = _format_hist_value(label, val, fmt)
             table_rows.append(r)
 
         if table_rows: