strategies: spending input is honoured + new "Custom" preset with guardrails

The user noticed the "Annual spending" field was a no-op for Trinity,
GK, VPW, VPW+floor — the strategies internally hardcoded the year-0
withdrawal as `initial_portfolio × initial_rate` (4% / 5.5%) and
ignored what the user typed. Two fixes:

(1) Trinity + GK now use state.initial_withdrawal (= the user's
    spending_target) as the year-0 draw. GK's guardrail anchor
    becomes the implied initial rate (initial_withdrawal /
    initial_portfolio), so the rule shape adapts to the user's
    chosen rate. Both strategies still fall back to their preset
    rate × initial_portfolio when initial_withdrawal isn't set
    (test paths). VPW and VPW+floor stay algorithmic — they're
    "withdraw-what's-sustainable" by design and don't take a
    spending input.

(2) New "custom" preset (SpendingPlanStrategy) exposing all the
    knobs:
    - initial_spend = "Annual spending" input
    - annual_real_adjust_pct = scale last year's withdrawal by N%
      each year (0 = constant real £, +0.02 = 2%/yr healthcare
      creep, -0.005 = -0.5%/yr slow-down with age)
    - guardrail_threshold_pct = if portfolio falls below X% of
      starting NW, trigger a cut (None = disabled)
    - guardrail_cut_pct = cut last year's withdrawal by Y% each
      triggered year

Adjust applies first, then guardrail cut — so a triggered year in
+2% adjust mode goes 40k → 40.8k → 36.7k.

UI: "custom" added to the strategy dropdown; when selected, three
extra fields appear (annual real adjustment %, guardrail trigger
threshold, guardrail cut size) with hints. The existing inputs
(spending, NW seed) drive year 0 across all strategies that use
them. About-the-model panel updated.

10 new tests on SpendingPlanStrategy + adjusted GK tests for the
new spending_target-aware behaviour. 209 backend tests + 7
frontend tests. mypy + ruff + tsc all pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

fire_planner/api/schemas.py

@@ -238,6 +238,16 @@ class SimulateRequest(BaseModel):
     #                   recent regime only (~6 years). Glide path is moot.
     returns_mode: str = Field(default="shiller", pattern="^(shiller|manual|wealthfolio)$")
     manual_real_return_pct: Decimal | None = None
+    # Custom spending-plan parameters — only consulted when strategy="custom".
+    # All real-£ / real-fraction. annual_real_adjust_pct = 0 means constant
+    # real spending (Trinity-shape). Non-zero scales last year's withdrawal
+    # multiplicatively each year (e.g. -0.005 for slow-down with age,
+    # +0.02 for healthcare creep). Guardrail cuts spending by
+    # `guardrail_cut_pct` whenever the portfolio falls below
+    # `guardrail_threshold_pct` of its starting value; null disables.
+    annual_real_adjust_pct: Decimal = Decimal("0")
+    guardrail_threshold_pct: Decimal | None = None
+    guardrail_cut_pct: Decimal = Decimal("0.10")
 
 
 class SimulateResult(BaseModel):

fire_planner/api/simulate.py

@@ -105,13 +105,22 @@ def _project(req: SimulateRequest, paths: np.ndarray) -> tuple[SimulationResult,
         ]
         cashflow_adjustments = events_to_cashflow_array(engine_events, req.horizon_years)
 
+    strategy = build_strategy(
+        req.strategy,
+        floor=floor,
+        annual_real_adjust_pct=float(req.annual_real_adjust_pct),
+        guardrail_threshold_pct=(float(req.guardrail_threshold_pct)
+                                 if req.guardrail_threshold_pct is not None else None),
+        guardrail_cut_pct=float(req.guardrail_cut_pct),
+    )
+
     started = time.perf_counter()
     result = simulate(
         paths=paths,
         initial_portfolio=float(req.nw_seed_gbp),
         spending_target=float(req.spending_gbp),
         glide=get_glide(req.glide_path),
-        strategy=build_strategy(req.strategy, floor=floor),
+        strategy=strategy,
         regime=build_regime_schedule(req.jurisdiction, req.leave_uk_year),
         horizon_years=req.horizon_years,
         annual_savings=annual_savings,

fire_planner/scenarios.py

@@ -22,6 +22,7 @@ from fire_planner.glide_path import GLIDE_PATHS
 from fire_planner.simulator import RegimeFn, constant_regime, jurisdiction_schedule
 from fire_planner.strategies.base import WithdrawalStrategy
 from fire_planner.strategies.guyton_klinger import GuytonKlingerStrategy
+from fire_planner.strategies.spending_plan import SpendingPlanStrategy
 from fire_planner.strategies.trinity import TrinityStrategy
 from fire_planner.strategies.vpw import VpwStrategy, VpwWithFloorStrategy
 from fire_planner.tax.base import TaxRegime
@@ -58,7 +59,13 @@ class ScenarioSpec:
                 f"glide-{self.glide_path}")
 
 
-def build_strategy(name: str, floor: float | None = None) -> WithdrawalStrategy:
+def build_strategy(
+    name: str,
+    floor: float | None = None,
+    annual_real_adjust_pct: float = 0.0,
+    guardrail_threshold_pct: float | None = None,
+    guardrail_cut_pct: float = 0.10,
+) -> WithdrawalStrategy:
     if name == "trinity":
         return TrinityStrategy()
     if name == "guyton_klinger":
@@ -69,6 +76,12 @@ def build_strategy(name: str, floor: float | None = None) -> WithdrawalStrategy:
         if floor is None:
             raise ValueError("vpw_floor strategy requires a `floor` value (real GBP)")
         return VpwWithFloorStrategy(floor=floor)
+    if name == "custom":
+        return SpendingPlanStrategy(
+            annual_real_adjust_pct=annual_real_adjust_pct,
+            guardrail_threshold_pct=guardrail_threshold_pct,
+            guardrail_cut_pct=guardrail_cut_pct,
+        )
     raise KeyError(f"Unknown strategy: {name!r}")
 
 

fire_planner/strategies/guyton_klinger.py

@@ -41,17 +41,26 @@ class GuytonKlingerStrategy(WithdrawalStrategy):
         self.initial_rate = initial_rate
 
     def propose_withdrawal(self, state: StrategyState) -> float:
+        # Year 0 = the user's target spending; the implied initial rate
+        # (initial_withdrawal / initial_portfolio) becomes the anchor
+        # the guardrails compare against. Falls back to the preset rate
+        # × initial_portfolio when no target was given.
+        target_initial = (state.initial_withdrawal
+                          if state.initial_withdrawal > 0 else
+                          state.initial_portfolio * self.initial_rate)
         if state.year_idx == 0:
-            return state.initial_portfolio * self.initial_rate
+            return target_initial
         if state.portfolio <= 0:
             return 0.0
+        implied_initial_rate = (target_initial / state.initial_portfolio
+                                if state.initial_portfolio > 0 else self.initial_rate)
         last_w = state.last_withdrawal
         current_rate = last_w / state.portfolio
         years_left = state.horizon_years - state.year_idx
         # Capital-preservation cut: only if more than 15 years remain.
-        if (current_rate > self.initial_rate * CAPITAL_PRESERVATION_RATIO
+        if (current_rate > implied_initial_rate * CAPITAL_PRESERVATION_RATIO
                 and years_left > MIN_HORIZON_FOR_CUT):
             return last_w * (1 - ADJUSTMENT)
-        if current_rate < self.initial_rate * PROSPERITY_RATIO:
+        if current_rate < implied_initial_rate * PROSPERITY_RATIO:
             return last_w * (1 + ADJUSTMENT)
         return last_w

fire_planner/strategies/spending_plan.py

@@ -0,0 +1,62 @@
+"""Custom user-defined spending plan.
+
+A flexible strategy where the user chooses every knob:
+
+- `initial_spend` — year 0 withdrawal in real GBP (taken from
+  `state.initial_withdrawal` if not overridden).
+- `annual_real_adjust_pct` — fraction by which last year's withdrawal
+  scales each subsequent year, on top of inflation. 0.0 = constant
+  real GBP (Trinity-shape). +0.02 = 2%/yr above-inflation creep
+  (e.g. healthcare). -0.005 = -0.5%/yr decreasing spend (slowing
+  down with age).
+- `guardrail_threshold_pct` — if portfolio drops below this fraction
+  of the starting NW, apply a cut. None = no guardrail.
+- `guardrail_cut_pct` — fraction by which to cut last year's
+  withdrawal when triggered. Applied multiplicatively each triggered
+  year — not "snap to threshold-implied rate", just a soft cut.
+
+The cut is checked AFTER the annual adjustment, so a cut + an
+increase don't double-apply: cut wins.
+
+Compared to Guyton-Klinger this is simpler — one threshold, one
+cut size, no prosperity rule. If the user wants the prosperity rule
+behaviour they can pick the GK preset.
+"""
+from __future__ import annotations
+
+from fire_planner.strategies.base import StrategyState, WithdrawalStrategy
+
+
+class SpendingPlanStrategy(WithdrawalStrategy):
+    name = "custom"
+
+    def __init__(
+        self,
+        initial_spend: float | None = None,
+        annual_real_adjust_pct: float = 0.0,
+        guardrail_threshold_pct: float | None = None,
+        guardrail_cut_pct: float = 0.10,
+    ) -> None:
+        self.initial_spend = initial_spend
+        self.annual_real_adjust_pct = annual_real_adjust_pct
+        self.guardrail_threshold_pct = guardrail_threshold_pct
+        self.guardrail_cut_pct = guardrail_cut_pct
+
+    def propose_withdrawal(self, state: StrategyState) -> float:
+        if state.year_idx == 0:
+            # Explicit override wins; otherwise take the user's target.
+            return (self.initial_spend
+                    if self.initial_spend is not None and self.initial_spend > 0 else
+                    state.initial_withdrawal)
+        if state.portfolio <= 0:
+            return 0.0
+
+        proposed = state.last_withdrawal * (1.0 + self.annual_real_adjust_pct)
+
+        if (self.guardrail_threshold_pct is not None
+                and state.initial_portfolio > 0):
+            trigger_at = state.initial_portfolio * self.guardrail_threshold_pct
+            if state.portfolio < trigger_at:
+                proposed = proposed * (1.0 - self.guardrail_cut_pct)
+
+        return max(0.0, proposed)

fire_planner/strategies/trinity.py

@@ -1,9 +1,10 @@
-"""Trinity 4% Safe Withdrawal Rate.
+"""Constant-real-£ withdrawal (the classic 4% rule shape).
 
-Bengen's seminal 1994 paper + the Trinity Study (Cooley/Hubbard/Walz,
-1998) — withdraw 4% of the starting balance in year 1, then keep the
-real withdrawal constant for the rest of retirement. In our real-GBP
-internal frame this is just "the same number every year".
+Withdraw `state.initial_withdrawal` in year 0, then keep that real-£
+amount fixed for the rest of retirement. In a 4% / £1M setup the year-0
+draw is £40k, then £40k real every year after. The strategy's
+`initial_rate` is kept only as a fallback for callers that don't feed
+`state.initial_withdrawal`.
 """
 from __future__ import annotations
 
@@ -20,5 +21,10 @@ class TrinityStrategy(WithdrawalStrategy):
 
     def propose_withdrawal(self, state: StrategyState) -> float:
         if state.year_idx == 0:
+            # Year 0 = the user's target spending. Falls back to
+            # initial_rate × initial_portfolio if no target was provided
+            # (zero or missing) for backwards compatibility.
+            if state.initial_withdrawal > 0:
+                return state.initial_withdrawal
             return state.initial_portfolio * self.initial_rate
         return state.last_withdrawal