Refine overview ratios and shell

10 files changed, 712 insertions, 98 deletions

diff --git a/backend/app/schemas.py b/backend/app/schemas.py
index db0076d..2ee6dac 100644
--- a/backend/app/schemas.py
+++ b/backend/app/schemas.py
@@ -39,6 +39,23 @@ class OverviewStats(BaseModel):
     beta: float | None = None
 
 
+class OverviewRatios(BaseModel):
+    price_to_book: float | None = None
+    price_to_sales: float | None = None
+    ev_to_sales: float | None = None
+    ev_to_ebitda: float | None = None
+    gross_margin_ttm: float | None = None
+    operating_margin_ttm: float | None = None
+    net_margin_ttm: float | None = None
+    roe_ttm: float | None = None
+    roa_ttm: float | None = None
+    roic_ttm: float | None = None
+    debt_to_equity: float | None = None
+    current_ratio: float | None = None
+    dividend_yield_ttm: float | None = None
+    dividend_payout_ratio_ttm: float | None = None
+
+
 class Range52Week(BaseModel):
     low: float | None = None
     high: float | None = None
@@ -75,6 +92,7 @@ class TickerOverview(BaseModel):
     quote: Quote
     signals: list[Signal] = Field(default_factory=list)
     stats: OverviewStats
+    ratios: OverviewRatios
     range_52w: Range52Week
     short_interest: ShortInterest
     meta: OverviewMeta
diff --git a/backend/app/services/data_service.py b/backend/app/services/data_service.py
index ae078cd..6f8587f 100644
--- a/backend/app/services/data_service.py
+++ b/backend/app/services/data_service.py
@@ -18,10 +18,18 @@ PRICE_CACHE = TTLCache(maxsize=256, ttl=300)
 HISTORY_CACHE = TTLCache(maxsize=256, ttl=300)
 INTRADAY_CACHE = TTLCache(maxsize=128, ttl=60)
 MARKET_CACHE = TTLCache(maxsize=8, ttl=300)
+STATEMENT_CACHE = TTLCache(maxsize=256, ttl=3600)
+SHARES_CACHE = TTLCache(maxsize=256, ttl=3600)
+RATIO_CACHE = TTLCache(maxsize=256, ttl=3600)
 
 PERIODS = {"1m", "3m", "6m", "1y", "5y"}
 YF_PERIOD_MAP = {"1m": "1mo", "3m": "3mo", "6m": "6mo", "1y": "1y", "5y": "5y"}
 _XMAP = {"NYQ": "NYSE", "NMS": "NASDAQ", "NGM": "NASDAQ", "NCM": "NASDAQ", "ASE": "AMEX"}
+_SHARE_LABELS = (
+    "Ordinary Shares Number",
+    "Share Issued",
+    "Common Stock Shares Outstanding",
+)
 
 
 def normalize_symbol(symbol: str) -> str:
@@ -55,6 +63,46 @@ def _json_value(value: Any) -> Any:
     return value
 
 
+def _cap_ratio(value: float | None, lower: float, upper: float) -> float | None:
+    if value is None or value <= lower or value >= upper:
+        return None
+    return value
+
+
+def _balance_value(frame: pd.DataFrame, *labels: str) -> float | None:
+    if frame is None or frame.empty:
+        return None
+    for label in labels:
+        if label not in frame.index:
+            continue
+        series = pd.to_numeric(frame.loc[label], errors="coerce").dropna()
+        if series.empty:
+            continue
+        value = _safe_float(series.iloc[0])
+        if value is not None:
+            return value
+    return None
+
+
+def _statement_ttm(frame: pd.DataFrame, *labels: str) -> float | None:
+    if frame is None or frame.empty:
+        return None
+    for label in labels:
+        if label not in frame.index:
+            continue
+        series = pd.to_numeric(frame.loc[label].iloc[:4], errors="coerce").dropna()
+        if len(series) == 4:
+            value = _safe_float(series.sum())
+            if value is not None:
+                return value
+    return None
+
+
+def _latest_share_count(balance_sheet: pd.DataFrame) -> float | None:
+    shares = _balance_value(balance_sheet, *_SHARE_LABELS)
+    return shares if shares is not None and shares > 0 else None
+
+
 def _pick_search_match(symbol: str) -> dict[str, Any]:
     sym = normalize_symbol(symbol)
     results = search_tickers(sym)
@@ -97,8 +145,7 @@ def get_company_info(symbol: str) -> dict[str, Any]:
         info = yf.Ticker(sym).info or {}
         if not isinstance(info, dict):
             return {}
-        cleaned = {str(k): _json_value(v) for k, v in info.items()}
-        return cleaned
+        return {str(k): _json_value(v) for k, v in info.items()}
     except Exception:
         return {}
 
@@ -187,6 +234,76 @@ def get_intraday_history(symbol: str, period: str, interval: str) -> list[dict[s
         return []
 
 
+@cached(STATEMENT_CACHE)
+def get_income_statement(symbol: str, quarterly: bool = False) -> pd.DataFrame:
+    try:
+        ticker = yf.Ticker(normalize_symbol(symbol))
+        frame = ticker.quarterly_income_stmt if quarterly else ticker.income_stmt
+        return frame if isinstance(frame, pd.DataFrame) else pd.DataFrame()
+    except Exception:
+        return pd.DataFrame()
+
+
+@cached(STATEMENT_CACHE)
+def get_balance_sheet(symbol: str, quarterly: bool = False) -> pd.DataFrame:
+    try:
+        ticker = yf.Ticker(normalize_symbol(symbol))
+        frame = ticker.quarterly_balance_sheet if quarterly else ticker.balance_sheet
+        return frame if isinstance(frame, pd.DataFrame) else pd.DataFrame()
+    except Exception:
+        return pd.DataFrame()
+
+
+@cached(STATEMENT_CACHE)
+def get_cash_flow(symbol: str, quarterly: bool = False) -> pd.DataFrame:
+    try:
+        ticker = yf.Ticker(normalize_symbol(symbol))
+        frame = ticker.quarterly_cashflow if quarterly else ticker.cashflow
+        return frame if isinstance(frame, pd.DataFrame) else pd.DataFrame()
+    except Exception:
+        return pd.DataFrame()
+
+
+@cached(SHARES_CACHE)
+def get_shares_outstanding(symbol: str) -> float | None:
+    sym = normalize_symbol(symbol)
+    info = get_company_info(sym)
+    for key in ("sharesOutstanding", "impliedSharesOutstanding"):
+        shares = _safe_float(info.get(key))
+        if shares is not None and shares > 0:
+            return shares
+
+    fast_info = get_fast_info(sym)
+    shares = _safe_float(fast_info.get("shares"))
+    if shares is not None and shares > 0:
+        return shares
+
+    balance_sheet = get_balance_sheet(sym, quarterly=True)
+    shares = _latest_share_count(balance_sheet)
+    if shares is not None:
+        return shares
+
+    try:
+        history = yf.Ticker(sym).get_shares_full(start="2000-01-01")
+        if isinstance(history, pd.Series):
+            values = pd.to_numeric(history, errors="coerce").dropna()
+            if not values.empty:
+                latest = _safe_float(values.iloc[-1])
+                if latest is not None and latest > 0:
+                    return latest
+    except Exception:
+        pass
+    return None
+
+
+def get_market_cap_computed(symbol: str, price: float | None = None, shares: float | None = None) -> float | None:
+    latest_price = price if price is not None else get_latest_price(symbol)
+    share_count = shares if shares is not None else get_shares_outstanding(symbol)
+    if latest_price is not None and latest_price > 0 and share_count is not None and share_count > 0:
+        return latest_price * share_count
+    return None
+
+
 def _history_rows(df: pd.DataFrame, include_time: bool) -> list[dict[str, Any]]:
     rows: list[dict[str, Any]] = []
     for idx, row in df.iterrows():
@@ -246,9 +363,11 @@ def build_quote(info: dict[str, Any], symbol: str) -> dict[str, Any]:
     return {"price": price, "prev_close": prev_close, "change": change, "change_pct": change_pct}
 
 
-def build_signals(info: dict[str, Any]) -> list[dict[str, str]]:
+def build_signals(info: dict[str, Any], ratios: dict[str, Any]) -> list[dict[str, str]]:
     signals: list[dict[str, str]] = []
     pe = _safe_float(info.get("trailingPE"))
+    if pe is None:
+        pe = _safe_float(ratios.get("trailing_pe"))
     if pe is not None and pe > 0:
         if pe < 15:
             signals.append({"key": "Valuation", "state": "pos", "value": f"P/E {pe:.1f}x", "description": "Attractive multiple"})
@@ -260,18 +379,25 @@ def build_signals(info: dict[str, Any]) -> list[dict[str, str]]:
         signals.append({"key": "Valuation", "state": "neu", "value": "P/E unavailable", "description": "No trailing earnings"})
 
     _ratio_signal(signals, "Growth", info.get("revenueGrowth"), 0.10, 0.0, "Strong top-line growth", "Low but positive growth", "Contracting revenue")
-    _ratio_signal(signals, "Profit", info.get("profitMargins"), 0.15, 0.05, "High net margin", "Moderate net margin", "Thin or negative margin")
+
+    profit = _safe_float(info.get("profitMargins"))
+    if profit is None:
+        profit = _safe_float(ratios.get("net_margin_ttm"))
+    _ratio_signal(signals, "Profit", profit, 0.15, 0.05, "High net margin", "Moderate net margin", "Thin or negative margin")
 
     debt_to_equity = _safe_float(info.get("debtToEquity"))
     if debt_to_equity is not None:
-        de_x = debt_to_equity / 100.0
-        if de_x < 0.5:
+        debt_to_equity = debt_to_equity / 100.0
+    else:
+        debt_to_equity = _safe_float(ratios.get("debt_to_equity"))
+    if debt_to_equity is not None:
+        if debt_to_equity < 0.5:
             state, desc = "pos", "Low leverage"
-        elif de_x < 2.0:
+        elif debt_to_equity < 2.0:
             state, desc = "warn", "Moderate leverage"
         else:
             state, desc = "neg", "High leverage"
-        signals.append({"key": "Leverage", "state": state, "value": f"D/E {de_x:.2f}x", "description": desc})
+        signals.append({"key": "Leverage", "state": state, "value": f"D/E {debt_to_equity:.2f}x", "description": desc})
 
     return signals
 
@@ -295,7 +421,8 @@ def _ratio_signal(
         state, desc = "warn", warn_desc
     else:
         state, desc = "neg", negative_desc
-    signals.append({"key": key, "state": state, "value": f"{ratio * 100:+.0f}%" if key == "Growth" else f"{ratio * 100:.0f}%", "description": desc})
+    formatted = f"{ratio * 100:+.0f}%" if key == "Growth" else f"{ratio * 100:.0f}%"
+    signals.append({"key": key, "state": state, "value": formatted, "description": desc})
 
 
 def _field(source_map: dict[str, dict[str, Any]], field_sources: dict[str, str], name: str, *candidates: tuple[str, str]) -> Any:
@@ -412,11 +539,111 @@ def _build_profile(sym: str, info: dict[str, Any], fast_info: dict[str, Any], se
     }
 
 
+@cached(RATIO_CACHE)
+def compute_ttm_ratios(symbol: str) -> dict[str, Any]:
+    sym = normalize_symbol(symbol)
+    info = get_company_info(sym)
+    price = _safe_float(info.get("currentPrice") or info.get("regularMarketPrice")) or get_latest_price(sym)
+    shares = get_shares_outstanding(sym)
+    income = get_income_statement(sym, quarterly=True)
+    balance = get_balance_sheet(sym, quarterly=True)
+    cash_flow = get_cash_flow(sym, quarterly=True)
+
+    if income is None or income.empty:
+        return {}
+
+    revenue = _statement_ttm(income, "Total Revenue")
+    gross_profit = _statement_ttm(income, "Gross Profit")
+    operating_income = _statement_ttm(income, "Operating Income")
+    net_income = _statement_ttm(income, "Net Income")
+    ebit = _statement_ttm(income, "EBIT")
+    ebitda = _statement_ttm(income, "EBITDA", "Normalized EBITDA")
+    tax_provision = _statement_ttm(income, "Tax Provision")
+    pretax_income = _statement_ttm(income, "Pretax Income")
+
+    equity = _balance_value(balance, "Stockholders Equity", "Common Stock Equity")
+    total_assets = _balance_value(balance, "Total Assets")
+    total_debt = _balance_value(balance, "Total Debt", "Long Term Debt And Capital Lease Obligation")
+    current_assets = _balance_value(balance, "Current Assets")
+    current_liabilities = _balance_value(balance, "Current Liabilities")
+    cash = _balance_value(balance, "Cash And Cash Equivalents", "Cash Cash Equivalents And Short Term Investments") or 0.0
+
+    market_cap = get_market_cap_computed(sym, price=price, shares=shares)
+    trailing_eps = None
+    if shares is not None and shares > 0 and net_income is not None:
+        trailing_eps = net_income / shares
+
+    ratios: dict[str, Any] = {}
+    ratios["market_cap"] = market_cap
+    ratios["trailing_eps"] = trailing_eps
+
+    if revenue and revenue > 0:
+        if gross_profit is not None:
+            ratios["gross_margin_ttm"] = gross_profit / revenue
+        if operating_income is not None:
+            ratios["operating_margin_ttm"] = operating_income / revenue
+        if net_income is not None:
+            ratios["net_margin_ttm"] = net_income / revenue
+
+    if equity and equity > 0 and net_income is not None:
+        roe = net_income / equity
+        if abs(roe) < 10:
+            ratios["roe_ttm"] = roe
+
+    if total_assets and total_assets > 0 and net_income is not None:
+        roa = net_income / total_assets
+        if abs(roa) < 10:
+            ratios["roa_ttm"] = roa
+
+    if ebit is not None and pretax_income not in (None, 0):
+        effective_tax_rate = max(0.0, (tax_provision or 0.0) / pretax_income)
+        invested_capital = (equity or 0.0) + (total_debt or 0.0) - cash
+        if invested_capital > 0:
+            roic = (ebit * (1 - effective_tax_rate)) / invested_capital
+            if abs(roic) < 10:
+                ratios["roic_ttm"] = roic
+
+    if market_cap and market_cap > 0:
+        if net_income and net_income > 0:
+            ratios["trailing_pe"] = market_cap / net_income
+        if revenue and revenue > 0:
+            ratios["price_to_sales"] = _cap_ratio(market_cap / revenue, 0, 100)
+        if equity and equity > 0:
+            ratios["price_to_book"] = _cap_ratio(market_cap / equity, 0, 100)
+
+        enterprise_value = market_cap + (total_debt or 0.0) - cash
+        if revenue and revenue > 0:
+            ratios["ev_to_sales"] = _cap_ratio(enterprise_value / revenue, 0, 100)
+        if ebitda and ebitda > 1e6:
+            ratios["ev_to_ebitda"] = _cap_ratio(enterprise_value / ebitda, 0, 500)
+
+    if equity and equity > 0 and total_debt is not None:
+        ratios["debt_to_equity"] = _cap_ratio(total_debt / equity, -1, 100)
+
+    if current_liabilities and current_liabilities > 0 and current_assets is not None:
+        ratios["current_ratio"] = current_assets / current_liabilities
+
+    dividends_paid = _statement_ttm(cash_flow, "Cash Dividends Paid", "Common Stock Dividend Paid")
+    if dividends_paid is not None:
+        dividends_paid = abs(dividends_paid)
+        if market_cap and market_cap > 0:
+            div_yield = dividends_paid / market_cap
+            if 0 <= div_yield < 1:
+                ratios["dividend_yield_ttm"] = div_yield
+        if net_income and net_income > 0:
+            payout = dividends_paid / net_income
+            if 0 <= payout < 10:
+                ratios["dividend_payout_ratio_ttm"] = payout
+
+    return {key: value for key, value in ratios.items() if value is not None}
+
+
 def _build_quote_and_stats(
     info: dict[str, Any],
     fast_info: dict[str, Any],
     month_history: list[dict[str, Any]],
     year_history: list[dict[str, Any]],
+    computed: dict[str, Any],
     field_sources: dict[str, str],
 ) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any]]:
     month_snapshot = _history_snapshot(month_history)
@@ -426,6 +653,7 @@ def _build_quote_and_stats(
         "fast_info": fast_info,
         "history_recent": month_snapshot,
         "history_year": year_snapshot,
+        "computed": computed,
     }
 
     price = _safe_float(
@@ -478,9 +706,11 @@ def _build_quote_and_stats(
             ("history_recent", "averageVolume"),
         )
     )
-    market_cap = _safe_float(_field(source_map, field_sources, "stats.market_cap", ("info", "marketCap"), ("fast_info", "marketCap")))
-    trailing_pe = _safe_float(_field(source_map, field_sources, "stats.trailing_pe", ("info", "trailingPE")))
-    trailing_eps = _safe_float(_field(source_map, field_sources, "stats.trailing_eps", ("info", "trailingEps")))
+    market_cap = _safe_float(
+        _field(source_map, field_sources, "stats.market_cap", ("info", "marketCap"), ("fast_info", "marketCap"), ("computed", "market_cap"))
+    )
+    trailing_pe = _safe_float(_field(source_map, field_sources, "stats.trailing_pe", ("info", "trailingPE"), ("computed", "trailing_pe")))
+    trailing_eps = _safe_float(_field(source_map, field_sources, "stats.trailing_eps", ("info", "trailingEps"), ("computed", "trailing_eps")))
     beta = _safe_float(_field(source_map, field_sources, "stats.beta", ("info", "beta")))
     range_low = _safe_float(
         _field(
@@ -513,23 +743,46 @@ def _build_quote_and_stats(
             "average_volume": average_volume,
             "beta": beta,
         },
-        {
-            "low": range_low,
-            "high": range_high,
-            "price": price,
-        },
+        {"low": range_low, "high": range_high, "price": price},
     )
 
 
+def _build_ratios(computed: dict[str, Any], field_sources: dict[str, str]) -> dict[str, Any]:
+    ratios: dict[str, Any] = {}
+    keys = (
+        "price_to_book",
+        "price_to_sales",
+        "ev_to_sales",
+        "ev_to_ebitda",
+        "gross_margin_ttm",
+        "operating_margin_ttm",
+        "net_margin_ttm",
+        "roe_ttm",
+        "roa_ttm",
+        "roic_ttm",
+        "debt_to_equity",
+        "current_ratio",
+        "dividend_yield_ttm",
+        "dividend_payout_ratio_ttm",
+    )
+    for key in keys:
+        value = _safe_float(computed.get(key))
+        ratios[key] = value
+        if value is not None:
+            field_sources[f"ratios.{key}"] = "computed"
+    return ratios
+
+
 def _has_any_overview_data(
     profile: dict[str, Any],
     quote: dict[str, Any],
     stats: dict[str, Any],
+    ratios: dict[str, Any],
     range_52w: dict[str, Any],
     short_interest: dict[str, Any],
     field_sources: dict[str, str],
 ) -> bool:
-    for bucket in (profile, quote, stats, range_52w, short_interest):
+    for bucket in (profile, quote, stats, ratios, range_52w, short_interest):
         for key, value in bucket.items():
             if key == "symbol":
                 continue
@@ -549,10 +802,13 @@ def get_ticker_overview(symbol: str) -> dict[str, Any] | None:
     fast_info = get_fast_info(sym)
     month_history = get_price_history(sym, period="1m")
     year_history = get_price_history(sym, period="1y")
+    computed = compute_ttm_ratios(sym)
     field_sources: dict[str, str] = {}
 
     profile = _build_profile(sym, info, fast_info, search_match, field_sources)
-    quote, stats, range_52w = _build_quote_and_stats(info, fast_info, month_history, year_history, field_sources)
+    quote, stats, range_52w = _build_quote_and_stats(info, fast_info, month_history, year_history, computed, field_sources)
+    ratios = _build_ratios(computed, field_sources)
+
     short = _safe_int(info.get("sharesShort"))
     short_prior = _safe_int(info.get("sharesShortPriorMonth"))
     short_delta = None
@@ -566,7 +822,7 @@ def get_ticker_overview(symbol: str) -> dict[str, Any] | None:
         "shares_short_delta_pct": short_delta,
     }
 
-    if not _has_any_overview_data(profile, quote, stats, range_52w, short_interest, field_sources):
+    if not _has_any_overview_data(profile, quote, stats, ratios, range_52w, short_interest, field_sources):
         return None
 
     field_availability = {
@@ -584,6 +840,20 @@ def get_ticker_overview(symbol: str) -> dict[str, Any] | None:
         "stats.volume": stats.get("volume") is not None,
         "stats.average_volume": stats.get("average_volume") is not None,
         "stats.beta": stats.get("beta") is not None,
+        "ratios.price_to_book": ratios.get("price_to_book") is not None,
+        "ratios.price_to_sales": ratios.get("price_to_sales") is not None,
+        "ratios.ev_to_sales": ratios.get("ev_to_sales") is not None,
+        "ratios.ev_to_ebitda": ratios.get("ev_to_ebitda") is not None,
+        "ratios.gross_margin_ttm": ratios.get("gross_margin_ttm") is not None,
+        "ratios.operating_margin_ttm": ratios.get("operating_margin_ttm") is not None,
+        "ratios.net_margin_ttm": ratios.get("net_margin_ttm") is not None,
+        "ratios.roe_ttm": ratios.get("roe_ttm") is not None,
+        "ratios.roa_ttm": ratios.get("roa_ttm") is not None,
+        "ratios.roic_ttm": ratios.get("roic_ttm") is not None,
+        "ratios.debt_to_equity": ratios.get("debt_to_equity") is not None,
+        "ratios.current_ratio": ratios.get("current_ratio") is not None,
+        "ratios.dividend_yield_ttm": ratios.get("dividend_yield_ttm") is not None,
+        "ratios.dividend_payout_ratio_ttm": ratios.get("dividend_payout_ratio_ttm") is not None,
         "range_52w.low": range_52w.get("low") is not None,
         "range_52w.high": range_52w.get("high") is not None,
     }
@@ -592,8 +862,9 @@ def get_ticker_overview(symbol: str) -> dict[str, Any] | None:
     return {
         "profile": profile,
         "quote": quote,
-        "signals": build_signals(info),
+        "signals": build_signals(info, computed),
         "stats": stats,
+        "ratios": ratios,
         "range_52w": range_52w,
         "short_interest": short_interest,
         "meta": {
diff --git a/backend/tests/test_api.py b/backend/tests/test_api.py
index 70b67a7..1c99cf9 100644
--- a/backend/tests/test_api.py
+++ b/backend/tests/test_api.py
@@ -6,6 +6,21 @@ from app import main
 from app.services import data_service
 
 
+def clear_service_caches() -> None:
+    data_service.INFO_CACHE.clear()
+    data_service.FAST_INFO_CACHE.clear()
+    data_service.PRICE_CACHE.clear()
+    data_service.HISTORY_CACHE.clear()
+    data_service.STATEMENT_CACHE.clear()
+    data_service.SHARES_CACHE.clear()
+    data_service.RATIO_CACHE.clear()
+
+
+def quarterly_frame(rows: dict[str, list[float]]) -> pd.DataFrame:
+    columns = pd.to_datetime(["2025-12-31", "2025-09-30", "2025-06-30", "2025-03-31"])
+    return pd.DataFrame(rows, index=columns).T
+
+
 def test_health() -> None:
     assert main.health() == {"status": "ok"}
 
@@ -31,6 +46,22 @@ def test_mocked_ticker_overview(monkeypatch) -> None:
             "quote": {"price": 100.0, "prev_close": 98.0, "change": 2.0, "change_pct": 0.0204},
             "signals": [],
             "stats": {"market_cap": None, "trailing_pe": None, "trailing_eps": None, "volume": None, "average_volume": None, "beta": None},
+            "ratios": {
+                "price_to_book": None,
+                "price_to_sales": None,
+                "ev_to_sales": None,
+                "ev_to_ebitda": None,
+                "gross_margin_ttm": None,
+                "operating_margin_ttm": None,
+                "net_margin_ttm": None,
+                "roe_ttm": None,
+                "roa_ttm": None,
+                "roic_ttm": None,
+                "debt_to_equity": None,
+                "current_ratio": None,
+                "dividend_yield_ttm": None,
+                "dividend_payout_ratio_ttm": None,
+            },
             "range_52w": {"low": None, "high": None, "price": 100.0},
             "short_interest": {"short_percent_of_float": None, "short_ratio": None, "shares_short": None, "shares_short_prior_month": None, "shares_short_delta_pct": None},
             "meta": {"status": "partial", "is_partial": True, "field_availability": {}, "sources": {}},
@@ -40,6 +71,7 @@ def test_mocked_ticker_overview(monkeypatch) -> None:
 
 
 def test_service_overview_prefers_info_fields(monkeypatch) -> None:
+    clear_service_caches()
     monkeypatch.setattr(
         data_service,
         "get_company_info",
@@ -74,6 +106,7 @@ def test_service_overview_prefers_info_fields(monkeypatch) -> None:
 
 
 def test_service_overview_falls_back_to_fast_info(monkeypatch) -> None:
+    clear_service_caches()
     monkeypatch.setattr(data_service, "get_company_info", lambda symbol: {})
     monkeypatch.setattr(
         data_service,
@@ -103,6 +136,7 @@ def test_service_overview_falls_back_to_fast_info(monkeypatch) -> None:
 
 
 def test_service_overview_falls_back_to_search_and_history(monkeypatch) -> None:
+    clear_service_caches()
     month_history = [
         {"date": "2026-01-01", "close": 98.0, "volume": 1000.0},
         {"date": "2026-01-02", "close": 100.0, "volume": 1200.0},
@@ -124,6 +158,7 @@ def test_service_overview_falls_back_to_search_and_history(monkeypatch) -> None:
 
 
 def test_service_overview_invalid_symbol(monkeypatch) -> None:
+    clear_service_caches()
     monkeypatch.setattr(data_service, "get_company_info", lambda symbol: {})
     monkeypatch.setattr(data_service, "get_fast_info", lambda symbol: {})
     monkeypatch.setattr(data_service, "_pick_search_match", lambda symbol: {})
@@ -149,6 +184,22 @@ def test_ticker_overview_partial_response(monkeypatch) -> None:
             "quote": {"price": 100.0, "prev_close": 98.0, "change": 2.0, "change_pct": 0.0204},
             "signals": [],
             "stats": {"market_cap": None, "trailing_pe": None, "trailing_eps": None, "volume": 1000.0, "average_volume": None, "beta": None},
+            "ratios": {
+                "price_to_book": None,
+                "price_to_sales": None,
+                "ev_to_sales": None,
+                "ev_to_ebitda": None,
+                "gross_margin_ttm": None,
+                "operating_margin_ttm": None,
+                "net_margin_ttm": None,
+                "roe_ttm": None,
+                "roa_ttm": None,
+                "roic_ttm": None,
+                "debt_to_equity": None,
+                "current_ratio": None,
+                "dividend_yield_ttm": None,
+                "dividend_payout_ratio_ttm": None,
+            },
             "range_52w": {"low": None, "high": None, "price": 100.0},
             "short_interest": {"short_percent_of_float": None, "short_ratio": None, "shares_short": None, "shares_short_prior_month": None, "shares_short_delta_pct": None},
             "meta": {"status": "partial", "is_partial": True, "field_availability": {"stats.market_cap": False}, "sources": {"profile.name": "search"}},
@@ -179,3 +230,157 @@ def test_ticker_history_period_mapping(monkeypatch) -> None:
     assert len(data_service.get_price_history("AAPL", period="3m")) == 1
     assert len(data_service.get_price_history("AAPL", period="6m")) == 1
     assert captured == ["1mo", "3mo", "6mo"]
+
+
+def test_compute_ttm_ratios_populates_overlapping_stats(monkeypatch) -> None:
+    clear_service_caches()
+    monkeypatch.setattr(data_service, "get_company_info", lambda symbol: {})
+    monkeypatch.setattr(data_service, "get_fast_info", lambda symbol: {})
+    monkeypatch.setattr(data_service, "get_latest_price", lambda symbol: 50.0)
+    monkeypatch.setattr(data_service, "get_shares_outstanding", lambda symbol: 100.0)
+    monkeypatch.setattr(
+        data_service,
+        "get_income_statement",
+        lambda symbol, quarterly=False: quarterly_frame(
+            {
+                "Total Revenue": [1_000.0, 1_000.0, 1_000.0, 1_000.0],
+                "Gross Profit": [500.0, 500.0, 500.0, 500.0],
+                "Operating Income": [250.0, 250.0, 250.0, 250.0],
+                "Net Income": [100.0, 100.0, 100.0, 100.0],
+                "EBIT": [150.0, 150.0, 150.0, 150.0],
+                "EBITDA": [200.0, 200.0, 200.0, 200.0],
+                "Tax Provision": [20.0, 20.0, 20.0, 20.0],
+                "Pretax Income": [120.0, 120.0, 120.0, 120.0],
+            }
+        ),
+    )
+    monkeypatch.setattr(
+        data_service,
+        "get_balance_sheet",
+        lambda symbol, quarterly=False: quarterly_frame(
+            {
+                "Stockholders Equity": [500.0, 0.0, 0.0, 0.0],
+                "Total Assets": [1_200.0, 0.0, 0.0, 0.0],
+                "Total Debt": [150.0, 0.0, 0.0, 0.0],
+                "Current Assets": [300.0, 0.0, 0.0, 0.0],
+                "Current Liabilities": [100.0, 0.0, 0.0, 0.0],
+                "Cash And Cash Equivalents": [50.0, 0.0, 0.0, 0.0],
+            }
+        ),
+    )
+    monkeypatch.setattr(
+        data_service,
+        "get_cash_flow",
+        lambda symbol, quarterly=False: quarterly_frame({"Cash Dividends Paid": [-10.0, -10.0, -10.0, -10.0]}),
+    )
+
+    ratios = data_service.compute_ttm_ratios("AAPL")
+    assert ratios["market_cap"] == 5_000.0
+    assert ratios["trailing_eps"] == 4.0
+    assert ratios["trailing_pe"] == 12.5
+    assert ratios["price_to_book"] == 10.0
+    assert ratios["price_to_sales"] == 1.25
+    assert ratios["ev_to_sales"] == 1.275
+    assert ratios["gross_margin_ttm"] == 0.5
+    assert ratios["operating_margin_ttm"] == 0.25
+    assert ratios["net_margin_ttm"] == 0.1
+    assert ratios["roe_ttm"] == 0.8
+    assert round(ratios["roic_ttm"], 6) == round((600.0 * (1 - (80.0 / 480.0))) / 600.0, 6)
+    assert ratios["debt_to_equity"] == 0.3
+    assert ratios["current_ratio"] == 3.0
+    assert ratios["dividend_yield_ttm"] == 0.008
+    assert ratios["dividend_payout_ratio_ttm"] == 0.1
+
+
+def test_compute_ttm_ratios_guardrails_suppress_outliers(monkeypatch) -> None:
+    clear_service_caches()
+    monkeypatch.setattr(data_service, "get_company_info", lambda symbol: {})
+    monkeypatch.setattr(data_service, "get_fast_info", lambda symbol: {})
+    monkeypatch.setattr(data_service, "get_latest_price", lambda symbol: 1_000.0)
+    monkeypatch.setattr(data_service, "get_shares_outstanding", lambda symbol: 100.0)
+    monkeypatch.setattr(
+        data_service,
+        "get_income_statement",
+        lambda symbol, quarterly=False: quarterly_frame(
+            {
+                "Total Revenue": [1.0, 1.0, 1.0, 1.0],
+                "Net Income": [1.0, 1.0, 1.0, 1.0],
+                "EBIT": [1.0, 1.0, 1.0, 1.0],
+                "EBITDA": [100_000.0, 100_000.0, 100_000.0, 100_000.0],
+                "Tax Provision": [0.0, 0.0, 0.0, 0.0],
+                "Pretax Income": [1.0, 1.0, 1.0, 1.0],
+            }
+        ),
+    )
+    monkeypatch.setattr(
+        data_service,
+        "get_balance_sheet",
+        lambda symbol, quarterly=False: quarterly_frame(
+            {
+                "Stockholders Equity": [1.0, 0.0, 0.0, 0.0],
+                "Total Assets": [10.0, 0.0, 0.0, 0.0],
+                "Total Debt": [1_000.0, 0.0, 0.0, 0.0],
+                "Cash And Cash Equivalents": [0.0, 0.0, 0.0, 0.0],
+            }
+        ),
+    )
+    monkeypatch.setattr(data_service, "get_cash_flow", lambda symbol, quarterly=False: pd.DataFrame())
+
+    ratios = data_service.compute_ttm_ratios("AAPL")
+    assert ratios["trailing_pe"] == 25_000.0
+    assert "price_to_book" not in ratios
+    assert "price_to_sales" not in ratios
+    assert "ev_to_sales" not in ratios
+    assert "ev_to_ebitda" not in ratios
+
+
+def test_overview_uses_computed_sources_and_ratios(monkeypatch) -> None:
+    clear_service_caches()
+    monkeypatch.setattr(
+        data_service,
+        "get_company_info",
+        lambda symbol: {
+            "longName": "Apple Inc.",
+            "exchange": "NMS",
+            "currentPrice": 120.0,
+            "previousClose": 118.0,
+        },
+    )
+    monkeypatch.setattr(data_service, "get_fast_info", lambda symbol: {})
+    monkeypatch.setattr(data_service, "get_price_history", lambda symbol, period="1m": [])
+    monkeypatch.setattr(data_service, "_pick_search_match", lambda symbol: {"symbol": "AAPL", "name": "Apple Inc.", "exchange": "NASDAQ"})
+    monkeypatch.setattr(data_service, "get_profile_enrichment", lambda symbol: {})
+    monkeypatch.setattr(
+        data_service,
+        "compute_ttm_ratios",
+        lambda symbol: {
+            "market_cap": 1_500_000_000.0,
+            "trailing_pe": 24.5,
+            "trailing_eps": 4.9,
+            "price_to_book": 8.0,
+            "price_to_sales": 6.2,
+            "ev_to_sales": 6.8,
+            "ev_to_ebitda": 22.1,
+            "gross_margin_ttm": 0.44,
+            "operating_margin_ttm": 0.27,
+            "net_margin_ttm": 0.18,
+            "roe_ttm": 0.31,
+            "roa_ttm": 0.12,
+            "roic_ttm": 0.19,
+            "debt_to_equity": 0.42,
+            "current_ratio": 1.8,
+            "dividend_yield_ttm": 0.005,
+            "dividend_payout_ratio_ttm": 0.12,
+        },
+    )
+
+    overview = data_service.get_ticker_overview("AAPL")
+    assert overview is not None
+    assert overview["stats"]["trailing_pe"] == 24.5
+    assert overview["stats"]["market_cap"] == 1_500_000_000.0
+    assert overview["ratios"]["price_to_book"] == 8.0
+    assert overview["meta"]["sources"]["stats.trailing_pe"] == "computed"
+    assert overview["meta"]["sources"]["stats.market_cap"] == "computed"
+    assert overview["meta"]["sources"]["ratios.price_to_book"] == "computed"
+    assert overview["meta"]["field_availability"]["ratios.ev_to_ebitda"] is True
+    assert any(signal["key"] == "Valuation" and "24.5x" in signal["value"] for signal in overview["signals"])
diff --git a/frontend/app/page.tsx b/frontend/app/page.tsx
index 02bd706..41408b0 100644
--- a/frontend/app/page.tsx
+++ b/frontend/app/page.tsx
@@ -377,12 +377,12 @@ function SignalCard({ overview }: { overview: TickerOverview }) {
           <h2 className="psm-card-title">Readthrough</h2>
         </div>
       </div>
-      <div className="psm-signal-grid">
+      <div className="psm-signal-list">
         {overview.signals.map((signal) => (
-          <article key={signal.key} className={`psm-signal ${signalTone(signal.state)}`}>
+          <article key={signal.key} className={`psm-signal-row ${signalTone(signal.state)}`}>
             <span className="psm-signal-key">{signal.key}</span>
-            <span className="psm-signal-value">{signal.value}</span>
             <span className="psm-signal-copy">{signal.description}</span>
+            <span className="psm-signal-value">{signal.value}</span>
           </article>
         ))}
       </div>
@@ -392,12 +392,14 @@ function SignalCard({ overview }: { overview: TickerOverview }) {
 
 function DataStatusCard({ overview, missingFields }: { overview: TickerOverview; missingFields: string[] }) {
   const entries = Object.entries(overview.meta.sources).slice(0, 6);
+  const visibleMissing = missingFields.slice(0, 4);
+  const hiddenMissingCount = Math.max(0, missingFields.length - visibleMissing.length);
 
   return (
     <section className="psm-card">
       <div className="psm-card-head">
         <div>
-          <div className="psm-eyebrow">Data Quality</div>
+          <div className="psm-eyebrow">Coverage</div>
           <h2 className="psm-card-title">Coverage</h2>
         </div>
         <span className={`psm-status-chip${overview.meta.is_partial ? " partial" : ""}`}>{overview.meta.status}</span>
@@ -405,7 +407,8 @@ function DataStatusCard({ overview, missingFields }: { overview: TickerOverview;
       <p className="psm-quality-copy">{availableFieldSummary(overview)}</p>
       {overview.meta.is_partial ? (
         <div className="psm-stack">
-          {missingFields.length ? missingFields.slice(0, 8).map((field) => <span key={field} className="psm-field-tag missing">{field}</span>) : null}
+          {missingFields.length ? visibleMissing.map((field) => <span key={field} className="psm-field-tag missing">{field}</span>) : null}
+          {hiddenMissingCount ? <span className="psm-field-tag missing">+{hiddenMissingCount} more</span> : null}
         </div>
       ) : null}
       <div className="psm-source-list">
@@ -433,7 +436,7 @@ function ProfileCard({ overview }: { overview: TickerOverview }) {
       <div className="psm-card-head">
         <div>
           <div className="psm-eyebrow">Company Profile</div>
-          <h2 className="psm-card-title">Context</h2>
+          <h2 className="psm-card-title">Company Profile</h2>
         </div>
       </div>
       <div className="psm-profile-list">
@@ -474,7 +477,7 @@ function ShortInterestCard({ overview }: { overview: TickerOverview }) {
       <div className="psm-card-head">
         <div>
           <div className="psm-eyebrow">Short Interest</div>
-          <h2 className="psm-card-title">Pressure</h2>
+          <h2 className="psm-card-title">Short Interest</h2>
         </div>
       </div>
       <div className="psm-detail-grid">
@@ -488,21 +491,38 @@ function ShortInterestCard({ overview }: { overview: TickerOverview }) {
 }
 
 function StatsCard({ overview }: { overview: TickerOverview }) {
+  const referenceRows = [
+    { label: "Market Cap", value: fmtLarge(overview.stats.market_cap), missing: overview.stats.market_cap == null },
+    { label: "P/E TTM", value: overview.stats.trailing_pe == null ? "-" : `${fmtNumber(overview.stats.trailing_pe)}x`, missing: overview.stats.trailing_pe == null },
+    { label: "EPS TTM", value: fmtCurrency(overview.stats.trailing_eps), missing: overview.stats.trailing_eps == null },
+    { label: "P/B", value: overview.ratios.price_to_book == null ? "-" : `${fmtNumber(overview.ratios.price_to_book)}x`, missing: overview.ratios.price_to_book == null },
+    { label: "P/S", value: overview.ratios.price_to_sales == null ? "-" : `${fmtNumber(overview.ratios.price_to_sales)}x`, missing: overview.ratios.price_to_sales == null },
+    { label: "EV/Sales", value: overview.ratios.ev_to_sales == null ? "-" : `${fmtNumber(overview.ratios.ev_to_sales)}x`, missing: overview.ratios.ev_to_sales == null },
+    { label: "EV/EBITDA", value: overview.ratios.ev_to_ebitda == null ? "-" : `${fmtNumber(overview.ratios.ev_to_ebitda)}x`, missing: overview.ratios.ev_to_ebitda == null },
+    { label: "Gross Margin", value: fmtPct(overview.ratios.gross_margin_ttm), missing: overview.ratios.gross_margin_ttm == null },
+    { label: "Op Margin", value: fmtPct(overview.ratios.operating_margin_ttm), missing: overview.ratios.operating_margin_ttm == null },
+    { label: "Net Margin", value: fmtPct(overview.ratios.net_margin_ttm), missing: overview.ratios.net_margin_ttm == null },
+    { label: "ROE", value: fmtPct(overview.ratios.roe_ttm), missing: overview.ratios.roe_ttm == null },
+    { label: "ROA", value: fmtPct(overview.ratios.roa_ttm), missing: overview.ratios.roa_ttm == null },
+    { label: "ROIC", value: fmtPct(overview.ratios.roic_ttm), missing: overview.ratios.roic_ttm == null },
+    { label: "D/E", value: overview.ratios.debt_to_equity == null ? "-" : `${fmtNumber(overview.ratios.debt_to_equity)}x`, missing: overview.ratios.debt_to_equity == null },
+    { label: "Current Ratio", value: overview.ratios.current_ratio == null ? "-" : `${fmtNumber(overview.ratios.current_ratio)}x`, missing: overview.ratios.current_ratio == null },
+    { label: "Dividend Yield", value: fmtPct(overview.ratios.dividend_yield_ttm), missing: overview.ratios.dividend_yield_ttm == null },
+    { label: "Payout Ratio", value: fmtPct(overview.ratios.dividend_payout_ratio_ttm), missing: overview.ratios.dividend_payout_ratio_ttm == null }
+  ];
+
   return (
     <section className="psm-card">
       <div className="psm-card-head">
         <div>
-          <div className="psm-eyebrow">Overview Stats</div>
+          <div className="psm-eyebrow">Reference</div>
           <h2 className="psm-card-title">Reference</h2>
         </div>
       </div>
       <div className="psm-stat-list">
-        <StatRow label="Market Cap" value={fmtLarge(overview.stats.market_cap)} missing={overview.stats.market_cap == null} />
-        <StatRow label="P/E TTM" value={fmtNumber(overview.stats.trailing_pe)} missing={overview.stats.trailing_pe == null} />
-        <StatRow label="EPS TTM" value={fmtCurrency(overview.stats.trailing_eps)} missing={overview.stats.trailing_eps == null} />
-        <StatRow label="Volume" value={fmtNumber(overview.stats.volume, 0)} missing={overview.stats.volume == null} />
-        <StatRow label="Avg Volume" value={fmtNumber(overview.stats.average_volume, 0)} missing={overview.stats.average_volume == null} />
-        <StatRow label="Beta" value={fmtNumber(overview.stats.beta)} missing={overview.stats.beta == null} />
+        {referenceRows.map((row) => (
+          <StatRow key={row.label} label={row.label} value={row.value} missing={row.missing} />
+        ))}
       </div>
     </section>
   );
diff --git a/frontend/app/prism-shell.css b/frontend/app/prism-shell.css
index 9b0e1b5..b6372c2 100644
--- a/frontend/app/prism-shell.css
+++ b/frontend/app/prism-shell.css
@@ -1,6 +1,6 @@
 .prism-app {
   display: grid;
-  grid-template-columns: 256px minmax(0, 1fr);
+  grid-template-columns: 284px minmax(0, 1fr);
   min-height: 100vh;
 }
 
@@ -192,22 +192,22 @@
 
 .psm-watch-row {
   display: grid;
-  grid-template-columns: minmax(0, 1fr) auto;
-  gap: var(--sp-2);
+  grid-template-columns: minmax(0, 1fr) 34px;
+  gap: var(--sp-3);
   align-items: center;
   border-bottom: 1px solid var(--line-1);
 }
 
 .psm-watch-select {
   display: grid;
-  grid-template-columns: minmax(0, 1fr) auto auto;
-  gap: var(--sp-2);
+  grid-template-columns: minmax(0, 1fr) minmax(82px, auto) minmax(52px, auto);
+  column-gap: var(--sp-5);
   align-items: center;
   width: 100%;
   border: 0;
   background: transparent;
   color: var(--fg-2);
-  padding: 10px 0;
+  padding: 12px 0;
 }
 
 .psm-watch-select:hover,
@@ -221,13 +221,22 @@
 
 .psm-watch-main {
   min-width: 0;
+  display: flex;
+  flex-direction: column;
+  gap: 3px;
   text-align: left;
 }
 
+.psm-watch-cell {
+  min-width: 0;
+}
+
 .psm-watch-symbol {
   color: var(--fg-1);
+  font-family: var(--font-mono);
   font-size: var(--fs-14);
   font-weight: 500;
+  letter-spacing: 0.04em;
 }
 
 .psm-watch-date,
@@ -240,6 +249,11 @@
   font-size: var(--fs-13);
 }
 
+.psm-watch-date {
+  line-height: 1.2;
+  white-space: nowrap;
+}
+
 .psm-watch-price,
 .psm-watch-change,
 .psm-quote-line,
@@ -261,13 +275,13 @@
 }
 
 .psm-watch-remove {
-  width: 26px;
-  height: 26px;
+  width: 30px;
+  height: 30px;
   border: 1px solid var(--line-2);
-  border-radius: var(--r-full);
+  border-radius: var(--r-2);
   background: transparent;
   color: var(--fg-4);
-  margin-right: 2px;
+  justify-self: end;
 }
 
 .psm-watch-remove:hover {
@@ -484,9 +498,9 @@
 
 .psm-ticker-head {
   display: grid;
-  grid-template-columns: minmax(0, 1.25fr) minmax(220px, 0.75fr) auto;
+  grid-template-columns: minmax(0, 1.4fr) minmax(240px, 0.75fr) minmax(220px, auto);
   gap: var(--sp-5);
-  align-items: end;
+  align-items: start;
   padding-bottom: var(--sp-4);
   border-bottom: 1px solid var(--line-1);
 }
@@ -495,32 +509,32 @@
   min-width: 0;
 }
 
+.psm-head-meta {
+  display: flex;
+  flex-wrap: wrap;
+  align-items: center;
+  gap: 8px;
+  margin-bottom: var(--sp-3);
+}
+
 .psm-identity-line {
   color: var(--brass);
-  display: block;
-  margin-bottom: var(--sp-2);
+  display: inline-flex;
 }
 
 .psm-heading-row {
   display: flex;
   flex-wrap: wrap;
-  align-items: baseline;
-  gap: var(--sp-4);
-}
-
-.psm-symbol {
-  color: var(--fg-1);
-  font-family: var(--font-display);
-  font-size: clamp(3rem, 6vw, var(--fs-64));
-  line-height: 0.95;
-  letter-spacing: -0.03em;
+  align-items: flex-start;
+  gap: var(--sp-3);
 }
 
 .psm-company-name {
-  color: var(--fg-2);
+  color: var(--fg-1);
   font-family: var(--font-display);
-  font-size: var(--fs-24);
+  font-size: clamp(2.8rem, 5vw, var(--fs-56));
   font-style: italic;
+  line-height: 0.95;
 }
 
 .psm-partial-chip,
@@ -559,22 +573,30 @@
   color: var(--negative);
 }
 
+.psm-tag {
+  border: 1px solid var(--line-2);
+  background: var(--ink-2);
+  color: var(--fg-2);
+}
+
 .psm-subline {
   margin-top: var(--sp-2);
   color: var(--fg-3);
   font-size: var(--fs-14);
+  max-width: 52ch;
 }
 
 .psm-price-stack {
   display: flex;
   flex-direction: column;
   align-items: flex-end;
-  gap: 4px;
+  gap: 5px;
+  padding-top: 2px;
 }
 
 .psm-price {
   color: var(--fg-1);
-  font-size: clamp(2.4rem, 4vw, var(--fs-48));
+  font-size: clamp(2.6rem, 4vw, var(--fs-48));
   line-height: 1;
 }
 
@@ -585,6 +607,8 @@
 .psm-quote-line {
   color: var(--fg-3);
   font-size: var(--fs-12);
+  text-transform: uppercase;
+  letter-spacing: var(--tr-wider);
 }
 
 .psm-primary-action,
@@ -601,6 +625,7 @@
   border: 1px solid var(--brass);
   background: var(--brass);
   color: var(--brass-ink);
+  margin-top: var(--sp-2);
 }
 
 .psm-primary-action.subtle {
@@ -618,6 +643,7 @@
   display: flex;
   flex-direction: column;
   gap: var(--sp-2);
+  padding-top: 8px;
 }
 
 .psm-range-values {
@@ -629,6 +655,10 @@
   font-size: var(--fs-12);
 }
 
+.psm-range-spot {
+  color: var(--fg-1);
+}
+
 .psm-range-rail {
   position: relative;
   height: 4px;
@@ -644,6 +674,11 @@
   background: var(--brass);
 }
 
+.psm-range-caption {
+  color: var(--fg-4);
+  font-size: var(--fs-12);
+}
+
 .psm-kpis {
   display: grid;
   grid-template-columns: repeat(6, minmax(0, 1fr));
@@ -769,14 +804,12 @@
   line-height: 1.5;
 }
 
-.psm-signal-grid,
 .psm-detail-grid {
   display: grid;
   grid-template-columns: repeat(2, minmax(0, 1fr));
   gap: var(--sp-3);
 }
 
-.psm-signal,
 .psm-detail-item {
   border: 1px solid var(--line-1);
   border-radius: var(--r-2);
@@ -792,7 +825,6 @@
   text-transform: uppercase;
 }
 
-.psm-signal-value,
 .psm-detail-value,
 .psm-stat-value {
   display: block;
@@ -801,7 +833,6 @@
   font-size: var(--fs-18);
 }
 
-.psm-signal-copy,
 .psm-detail-copy {
   display: block;
   margin-top: 6px;
@@ -810,20 +841,50 @@
   line-height: 1.45;
 }
 
-.psm-signal.pos {
-  border-color: rgba(79, 140, 94, 0.35);
+.psm-signal-list {
+  display: flex;
+  flex-direction: column;
 }
 
-.psm-signal.warn {
-  border-color: rgba(196, 149, 69, 0.35);
+.psm-signal-row {
+  display: grid;
+  grid-template-columns: 84px minmax(0, 1fr) auto;
+  gap: var(--sp-3);
+  align-items: center;
+  padding: 12px 0;
+  border-bottom: 1px solid var(--line-1);
+}
+
+.psm-signal-row:last-child {
+  border-bottom: 0;
+}
+
+.psm-signal-row.pos .psm-signal-value {
+  color: var(--positive);
+}
+
+.psm-signal-row.warn .psm-signal-value {
+  color: var(--warning);
+}
+
+.psm-signal-row.neg .psm-signal-value {
+  color: var(--negative);
 }
 
-.psm-signal.neg {
-  border-color: rgba(181, 73, 75, 0.35);
+.psm-signal-row.neu .psm-signal-value {
+  color: var(--fg-3);
+}
+
+.psm-signal-value {
+  color: var(--fg-1);
+  font-family: var(--font-mono);
+  font-size: var(--fs-14);
+  font-variant-numeric: tabular-nums;
 }
 
-.psm-signal.neu {
-  border-color: var(--line-2);
+.psm-signal-copy {
+  color: var(--fg-2);
+  font-size: var(--fs-14);
 }
 
 .psm-profile-list,
@@ -841,7 +902,7 @@
   grid-template-columns: minmax(0, 1fr) auto;
   gap: var(--sp-3);
   align-items: start;
-  padding-bottom: var(--sp-3);
+  padding-bottom: var(--sp-2);
   border-bottom: 1px solid var(--line-1);
 }
 
@@ -868,6 +929,11 @@
   word-break: break-word;
 }
 
+.psm-stat-value {
+  text-align: right;
+  white-space: nowrap;
+}
+
 .psm-source-value {
   font-family: var(--font-mono);
   font-size: var(--fs-12);
@@ -884,6 +950,7 @@
   display: flex;
   flex-wrap: wrap;
   gap: var(--sp-2);
+  margin-bottom: var(--sp-2);
 }
 
 .psm-field-tag {
@@ -988,18 +1055,33 @@
   .psm-kpis,
   .psm-main-grid,
   .psm-detail-grid,
-  .psm-signal-grid,
   .psm-ticker-head {
     grid-template-columns: 1fr;
   }
 
   .psm-heading-row {
     align-items: start;
-    flex-direction: column;
-    gap: var(--sp-2);
   }
 
   .psm-price-stack {
     align-items: start;
   }
+
+  .psm-signal-row {
+    grid-template-columns: 1fr;
+    gap: 4px;
+  }
+
+  .psm-watch-select {
+    grid-template-columns: minmax(0, 1fr) auto auto;
+    row-gap: 4px;
+  }
+
+  .psm-watch-price {
+    grid-column: 2;
+  }
+
+  .psm-watch-change {
+    grid-column: 3;
+  }
 }
diff --git a/frontend/components/prism/ChartCard.tsx b/frontend/components/prism/ChartCard.tsx
index bc650d7..87bb399 100644
--- a/frontend/components/prism/ChartCard.tsx
+++ b/frontend/components/prism/ChartCard.tsx
@@ -23,8 +23,8 @@ export function ChartCard({ symbol, period, points, chartState, chartError, onCh
     <section className="psm-card">
       <div className="psm-card-head">
         <div>
-          <div className="psm-eyebrow">Price History</div>
-          <h2 className="psm-card-title">{symbol}</h2>
+          <div className="psm-eyebrow">Price Action</div>
+          <h2 className="psm-card-title">{symbol} Price History</h2>
         </div>
         <div className="psm-tabs" role="tablist" aria-label="Chart range">
           {PERIODS.map((option) => (
@@ -42,7 +42,7 @@ export function ChartCard({ symbol, period, points, chartState, chartError, onCh
         </div>
       </div>
 
-      <p className="psm-chart-meta">Chart loading is isolated from the rest of Overview. A history miss only affects this card.</p>
+      <p className="psm-chart-meta">Interactive history for the selected window. If history fails, the rest of Overview stays intact.</p>
 
       <div className="psm-chart-frame">
         {chartState === "loading" ? <div className="psm-card-empty">Loading {period.toUpperCase()} history…</div> : null}
@@ -52,4 +52,3 @@ export function ChartCard({ symbol, period, points, chartState, chartError, onCh
     </section>
   );
 }
-
diff --git a/frontend/components/prism/Sidebar.tsx b/frontend/components/prism/Sidebar.tsx
index 80e13f3..7f106d8 100644
--- a/frontend/components/prism/Sidebar.tsx
+++ b/frontend/components/prism/Sidebar.tsx
@@ -75,12 +75,12 @@ export function Sidebar({
           return (
             <div key={item.symbol} className={`psm-watch-row${active ? " active" : ""}`}>
               <button type="button" className="psm-watch-select" onClick={() => onSelectTicker(item.symbol)}>
-                <span className="psm-watch-main">
+                <span className="psm-watch-cell psm-watch-main">
                   <span className="psm-watch-symbol">{item.symbol}</span>
                   <span className="psm-watch-date">{watchlistSubtitle(item)}</span>
                 </span>
-                <span className="psm-watch-price">{fmtCurrency(item.quote?.price)}</span>
-                <span className={`psm-watch-change ${deltaClass(item.quote?.change_pct)}`}>{fmtPct(item.quote?.change_pct, 2, true)}</span>
+                <span className="psm-watch-cell psm-watch-price">{fmtCurrency(item.quote?.price)}</span>
+                <span className={`psm-watch-cell psm-watch-change ${deltaClass(item.quote?.change_pct)}`}>{fmtPct(item.quote?.change_pct, 2, true)}</span>
               </button>
               <button
                 type="button"
diff --git a/frontend/components/prism/TickerHeader.tsx b/frontend/components/prism/TickerHeader.tsx
index 23254f8..369d06c 100644
--- a/frontend/components/prism/TickerHeader.tsx
+++ b/frontend/components/prism/TickerHeader.tsx
@@ -10,15 +10,18 @@ type Props = {
 
 export function TickerHeader({ overview, onToggleWatchlist, isSaved }: Props) {
   const pct = rangePercent(overview);
+  const lastSource = overview.meta.sources["quote.price"];
 
   return (
     <header className="psm-ticker-head">
       <div className="psm-header-left">
-        <span className="psm-identity-line psm-eyebrow">{overview.profile.symbol}</span>
+        <div className="psm-head-meta">
+          <span className="psm-identity-line psm-eyebrow">{overview.profile.symbol}</span>
+          {overview.profile.exchange ? <span className="psm-tag">{overview.profile.exchange}</span> : null}
+          {overview.meta.is_partial ? <span className="psm-partial-chip">Partial Data</span> : null}
+        </div>
         <div className="psm-heading-row">
-          <span className="psm-symbol">{overview.profile.symbol}</span>
           <span className="psm-company-name">{overview.profile.name || "Name unavailable"}</span>
-          {overview.meta.is_partial ? <span className="psm-partial-chip">Partial Data</span> : null}
         </div>
         <p className="psm-subline">{buildIdentityLine(overview)}</p>
       </div>
@@ -27,12 +30,13 @@ export function TickerHeader({ overview, onToggleWatchlist, isSaved }: Props) {
         <div className="psm-eyebrow">52 Week Range</div>
         <div className="psm-range-values">
           <span>{fmtCurrency(overview.range_52w.low)}</span>
-          <span>{fmtCurrency(overview.range_52w.price ?? overview.quote.price)}</span>
+          <span className="psm-range-spot">{fmtCurrency(overview.range_52w.price ?? overview.quote.price)}</span>
           <span>{fmtCurrency(overview.range_52w.high)}</span>
         </div>
         <div className="psm-range-rail" aria-hidden>
           {pct != null ? <span className="psm-range-indicator" style={{ left: `${pct}%` }} /> : null}
         </div>
+        <div className="psm-range-caption">{pct == null ? "Range unavailable" : `${pct.toFixed(0)}% through the annual range`}</div>
       </div>
 
       <div className="psm-price-stack">
@@ -41,6 +45,7 @@ export function TickerHeader({ overview, onToggleWatchlist, isSaved }: Props) {
           {fmtCurrency(overview.quote.change)} · {fmtPct(overview.quote.change_pct, 2, true)}
         </span>
         <span className="psm-quote-line">Prev close {fmtCurrency(overview.quote.prev_close)}</span>
+        {lastSource ? <span className="psm-quote-line">Source {lastSource.replaceAll("_", " ")}</span> : null}
         <button type="button" className={`psm-primary-action${isSaved ? " subtle" : ""}`} onClick={onToggleWatchlist}>
           {isSaved ? "Remove From Watchlist" : "Save To Watchlist"}
         </button>
@@ -48,4 +53,3 @@ export function TickerHeader({ overview, onToggleWatchlist, isSaved }: Props) {
     </header>
   );
 }
-
diff --git a/frontend/lib/overview.ts b/frontend/lib/overview.ts
index efbd9f9..d02c5d3 100644
--- a/frontend/lib/overview.ts
+++ b/frontend/lib/overview.ts
@@ -41,14 +41,14 @@ export function buildKpis(overview: TickerOverview): KpiItem[] {
     {
       key: "P / E",
       value: overview.stats.trailing_pe == null ? "Unavailable" : `${fmtNumber(overview.stats.trailing_pe)}x`,
-      sublabel: `EPS ${fmtCurrency(overview.stats.trailing_eps)}`,
+      sublabel: `P/B ${overview.ratios.price_to_book == null ? "-" : `${fmtNumber(overview.ratios.price_to_book)}x`}`,
       missing: overview.stats.trailing_pe == null
     },
     {
-      key: "Prev Close",
-      value: fmtCurrency(overview.quote.prev_close),
-      sublabel: `Day chg ${fmtCurrency(overview.quote.change)}`,
-      missing: overview.quote.prev_close == null
+      key: "EPS · TTM",
+      value: fmtCurrency(overview.stats.trailing_eps),
+      sublabel: `Net margin ${fmtPct(overview.ratios.net_margin_ttm)}`,
+      missing: overview.stats.trailing_eps == null
     },
     {
       key: "52W Position",
@@ -95,7 +95,7 @@ export function availableFieldSummary(overview: TickerOverview): string {
   const fields = Object.values(overview.meta.field_availability);
   if (!fields.length) return "Availability metadata unavailable";
   const available = fields.filter(Boolean).length;
-  return `${available}/${fields.length} tracked fields available`;
+  return `${available} of ${fields.length} tracked fields filled`;
 }
 
 export function watchlistSubtitle(item: WatchlistItem): string {
@@ -131,4 +131,3 @@ export function marketClock(now = new Date()) {
     }).format(now)
   };
 }
-
diff --git a/frontend/types/api.ts b/frontend/types/api.ts
index 679ada9..84dfd19 100644
--- a/frontend/types/api.ts
+++ b/frontend/types/api.ts
@@ -44,6 +44,22 @@ export type TickerOverview = {
     average_volume?: number | null;
     beta?: number | null;
   };
+  ratios: {
+    price_to_book?: number | null;
+    price_to_sales?: number | null;
+    ev_to_sales?: number | null;
+    ev_to_ebitda?: number | null;
+    gross_margin_ttm?: number | null;
+    operating_margin_ttm?: number | null;
+    net_margin_ttm?: number | null;
+    roe_ttm?: number | null;
+    roa_ttm?: number | null;
+    roic_ttm?: number | null;
+    debt_to_equity?: number | null;
+    current_ratio?: number | null;
+    dividend_yield_ttm?: number | null;
+    dividend_payout_ratio_ttm?: number | null;
+  };
   range_52w: {
     low?: number | null;
     high?: number | null;