Harden valuation edge cases

3 files changed, 94 insertions, 20 deletions

diff --git a/services/data_service.py b/services/data_service.py
index 412ca94..c278a2f 100644
--- a/services/data_service.py
+++ b/services/data_service.py
@@ -298,10 +298,14 @@ def compute_ttm_ratios(ticker: str) -> dict:
                 ratios["netProfitMarginTTM"] = net_income / revenue
 
         if equity and equity > 0 and net_income is not None:
-            ratios["returnOnEquityTTM"] = net_income / equity
+            roe = net_income / equity
+            if abs(roe) < 10:
+                ratios["returnOnEquityTTM"] = roe
 
         if total_assets and total_assets > 0 and net_income is not None:
-            ratios["returnOnAssetsTTM"] = net_income / total_assets
+            roa = net_income / total_assets
+            if abs(roa) < 10:
+                ratios["returnOnAssetsTTM"] = roa
 
         # ROIC = NOPAT / Invested Capital
         if ebit is not None and pretax_income and pretax_income != 0:
@@ -309,27 +313,39 @@ def compute_ttm_ratios(ticker: str) -> dict:
             nopat = ebit * (1 - effective_tax_rate)
             invested_capital = (equity or 0) + (total_debt or 0) - cash
             if invested_capital > 0:
-                ratios["returnOnInvestedCapitalTTM"] = nopat / invested_capital
+                roic = nopat / invested_capital
+                if abs(roic) < 10:
+                    ratios["returnOnInvestedCapitalTTM"] = roic
 
         # ── Valuation multiples ───────────────────────────────────────────────
         if market_cap and market_cap > 0:
             if net_income and net_income > 0:
                 ratios["peRatioTTM"] = market_cap / net_income
             if revenue and revenue > 0:
-                ratios["priceToSalesRatioTTM"] = market_cap / revenue
+                ps = market_cap / revenue
+                if 0 < ps < 100:
+                    ratios["priceToSalesRatioTTM"] = ps
             if equity and equity > 0:
-                ratios["priceToBookRatioTTM"] = market_cap / equity
+                pb = market_cap / equity
+                if 0 < pb < 100:
+                    ratios["priceToBookRatioTTM"] = pb
 
         if market_cap and market_cap > 0:
             ev = market_cap + (total_debt or 0.0) - cash
             if revenue and revenue > 0:
-                ratios["evToSalesTTM"] = ev / revenue
-            if ebitda and ebitda > 0:
-                ratios["enterpriseValueMultipleTTM"] = ev / ebitda
+                ev_sales = ev / revenue
+                if 0 < ev_sales < 100:
+                    ratios["evToSalesTTM"] = ev_sales
+            if ebitda and ebitda > 1e6:
+                ev_ebitda = ev / ebitda
+                if 0 < ev_ebitda < 500:
+                    ratios["enterpriseValueMultipleTTM"] = ev_ebitda
 
         # ── Leverage & Liquidity ──────────────────────────────────────────────
         if equity and equity > 0 and total_debt is not None:
-            ratios["debtToEquityRatioTTM"] = total_debt / equity
+            de = total_debt / equity
+            if 0 <= de < 100:
+                ratios["debtToEquityRatioTTM"] = de
 
         if current_liabilities and current_liabilities > 0 and current_assets is not None:
             ratios["currentRatioTTM"] = current_assets / current_liabilities
@@ -338,8 +354,10 @@ def compute_ttm_ratios(ticker: str) -> dict:
 
         if ebit is not None and interest_expense:
             ie = abs(interest_expense)
-            if ie > 0:
-                ratios["interestCoverageRatioTTM"] = ebit / ie
+            if ie > 0 and ebit > 0:
+                coverage = ebit / ie
+                if 0 < coverage < 1000:
+                    ratios["interestCoverageRatioTTM"] = coverage
 
         # ── Dividends (from cash flow statement) ─────────────────────────────
         dividends_paid = None
@@ -351,9 +369,13 @@ def compute_ttm_ratios(ticker: str) -> dict:
 
         if dividends_paid and dividends_paid > 0:
             if market_cap and market_cap > 0:
-                ratios["dividendYieldTTM"] = dividends_paid / market_cap
+                div_yield = dividends_paid / market_cap
+                if 0 <= div_yield < 1:
+                    ratios["dividendYieldTTM"] = div_yield
             if net_income and net_income > 0:
-                ratios["dividendPayoutRatioTTM"] = dividends_paid / net_income
+                payout = dividends_paid / net_income
+                if 0 <= payout < 10:
+                    ratios["dividendPayoutRatioTTM"] = payout
 
         # Expose raw EBITDA so callers (e.g. DCF EV/EBITDA section) use the
         # same TTM figure as the Key Ratios tab — single canonical source.
@@ -498,12 +520,18 @@ def get_historical_ratios_yfinance(ticker: str) -> list[dict]:
 
                 if equity and equity > 0:
                     if net_income is not None:
-                        row["returnOnEquity"] = net_income / equity
+                        roe = net_income / equity
+                        if abs(roe) < 10:
+                            row["returnOnEquity"] = roe
                     if total_debt is not None:
-                        row["debtEquityRatio"] = total_debt / equity
+                        de = total_debt / equity
+                        if 0 <= de < 100:
+                            row["debtEquityRatio"] = de
 
                 if total_assets and total_assets > 0 and net_income is not None:
-                    row["returnOnAssets"] = net_income / total_assets
+                    roa = net_income / total_assets
+                    if abs(roa) < 10:
+                        row["returnOnAssets"] = roa
 
             # Price-based ratios — average closing price in ±45-day window around year-end
             if shares and not hist.empty:
@@ -525,9 +553,13 @@ def get_historical_ratios_yfinance(ticker: str) -> list[dict]:
                         if net_income and net_income > 0:
                             row["peRatio"] = market_cap / net_income
                         if equity and equity > 0:
-                            row["priceToBookRatio"] = market_cap / equity
+                            pb = market_cap / equity
+                            if 0 < pb < 100:
+                                row["priceToBookRatio"] = pb
                         if total_rev and total_rev > 0:
-                            row["priceToSalesRatio"] = market_cap / total_rev
+                            ps = market_cap / total_rev
+                            if 0 < ps < 100:
+                                row["priceToSalesRatio"] = ps
 
                         # EV/EBITDA — approximate. Skip if EBITDA is too small to be meaningful,
                         # which otherwise creates absurd multiples for some software names.
diff --git a/services/fmp_service.py b/services/fmp_service.py
index 1e5ea42..82a9c4c 100644
--- a/services/fmp_service.py
+++ b/services/fmp_service.py
@@ -33,6 +33,11 @@ def get_key_ratios(ticker: str) -> dict:
 
     All ratios are self-computed via compute_ttm_ratios() — no FMP calls.
     Forward P/E and dividend fallbacks come from yfinance's info dict.
+
+    For edge cases, trailing P/E prefers the vendor-supplied value from the
+    info dict when the self-computed statement-based figure is missing or
+    materially inconsistent. This avoids obviously bad P/E outputs on tickers
+    with restatements, near-zero earnings, or statement mapping quirks.
     """
     ticker = ticker.upper()
     merged = {"symbol": ticker}
@@ -44,13 +49,43 @@ def get_key_ratios(ticker: str) -> dict:
     # Forward P/E requires analyst estimates — can't compute from statements
     info = get_company_info(ticker)
     if info:
+        trailing_pe_info = info.get("trailingPE")
+        trailing_pe_computed = merged.get("peRatioTTM")
+
+        if trailing_pe_info is not None:
+            try:
+                vendor_pe = float(trailing_pe_info)
+            except (TypeError, ValueError):
+                vendor_pe = None
+
+            try:
+                computed_pe = float(trailing_pe_computed) if trailing_pe_computed is not None else None
+            except (TypeError, ValueError):
+                computed_pe = None
+
+            if vendor_pe is not None and vendor_pe > 0:
+                if computed_pe is None or computed_pe <= 0:
+                    merged["peRatioTTM"] = vendor_pe
+                else:
+                    # If the two values are wildly different, trust the vendor
+                    # trailing P/E. This prevents edge-case display bugs where a
+                    # malformed TTM net income makes P/E look duplicated/wrong.
+                    ratio_gap = max(vendor_pe, computed_pe) / max(min(vendor_pe, computed_pe), 1e-9)
+                    if ratio_gap > 2.0:
+                        merged["peRatioTTM"] = vendor_pe
+
         if info.get("forwardPE") is not None:
             merged["forwardPE"] = info["forwardPE"]
         # Fallback: dividends from info dict when cash-flow data is missing
         if merged.get("dividendYieldTTM") is None and info.get("dividendYield") is not None:
             merged["dividendYieldTTM"] = info["dividendYield"]
-        if merged.get("dividendPayoutRatioTTM") is None and info.get("payoutRatio") is not None:
-            merged["dividendPayoutRatioTTM"] = info["payoutRatio"]
+        payout_ratio_info = info.get("payoutRatio")
+        if (
+            merged.get("dividendPayoutRatioTTM") is None
+            and payout_ratio_info is not None
+            and float(payout_ratio_info) > 0
+        ):
+            merged["dividendPayoutRatioTTM"] = payout_ratio_info
 
     return merged if len(merged) > 1 else {}
 
diff --git a/services/valuation_service.py b/services/valuation_service.py
index 6db4053..8559842 100644
--- a/services/valuation_service.py
+++ b/services/valuation_service.py
@@ -79,6 +79,13 @@ def run_dcf(
         growth_rate = historical_growth if historical_growth is not None else 0.05
 
     base_fcf = float(historical[-1])
+    if base_fcf <= 0:
+        return {
+            "error": (
+                "DCF is not meaningful with zero or negative base free cash flow. "
+                "Use comps, EV/EBITDA, or adjust the model only after underwriting a credible FCF turnaround."
+            )
+        }
 
     projected_fcfs = []
     for year in range(1, projection_years + 1):