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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>
87 lines
3.3 KiB
Python
87 lines
3.3 KiB
Python
"""SpendingPlanStrategy: user-customisable initial spend + annual adjust + guardrail."""
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from fire_planner.strategies.base import StrategyState
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from fire_planner.strategies.spending_plan import SpendingPlanStrategy
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def state(**overrides: float | int) -> StrategyState:
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base = dict(
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portfolio=1_000_000.0,
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initial_portfolio=1_000_000.0,
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initial_withdrawal=40_000.0,
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year_idx=0,
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horizon_years=60,
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last_withdrawal=40_000.0,
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expected_real_return=0.04,
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)
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base.update(overrides)
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return StrategyState(**base) # type: ignore[arg-type]
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def test_year_zero_takes_initial_withdrawal() -> None:
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s = SpendingPlanStrategy()
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assert s.propose_withdrawal(state()) == 40_000.0
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def test_year_zero_explicit_override() -> None:
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s = SpendingPlanStrategy(initial_spend=72_000.0)
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assert s.propose_withdrawal(state()) == 72_000.0
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def test_constant_real_with_zero_adjust() -> None:
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s = SpendingPlanStrategy(annual_real_adjust_pct=0.0)
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assert s.propose_withdrawal(state(year_idx=10, last_withdrawal=40_000.0)) == 40_000.0
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def test_positive_annual_adjust_grows_spending() -> None:
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"""+2% real adjust → year 5 spend is last_w × 1.02 (one step from year 4)."""
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s = SpendingPlanStrategy(annual_real_adjust_pct=0.02)
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out = s.propose_withdrawal(state(year_idx=5, last_withdrawal=40_000.0))
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assert abs(out - 40_800.0) < 1e-6
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def test_negative_annual_adjust_shrinks_spending() -> None:
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s = SpendingPlanStrategy(annual_real_adjust_pct=-0.005)
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out = s.propose_withdrawal(state(year_idx=10, last_withdrawal=40_000.0))
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assert abs(out - 39_800.0) < 1e-6
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def test_guardrail_not_triggered_when_portfolio_above_threshold() -> None:
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s = SpendingPlanStrategy(guardrail_threshold_pct=0.80, guardrail_cut_pct=0.10)
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# portfolio at 90% of starting → above threshold → no cut
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out = s.propose_withdrawal(state(year_idx=3, portfolio=900_000.0,
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last_withdrawal=40_000.0))
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assert out == 40_000.0
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def test_guardrail_triggered_cuts_by_pct() -> None:
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s = SpendingPlanStrategy(guardrail_threshold_pct=0.80, guardrail_cut_pct=0.10)
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# portfolio at 70% of starting → below threshold → 10% cut
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out = s.propose_withdrawal(state(year_idx=3, portfolio=700_000.0,
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last_withdrawal=40_000.0))
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assert abs(out - 36_000.0) < 1e-6
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def test_guardrail_combines_with_annual_adjust() -> None:
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"""Adjust applies first, then cut — both fire."""
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s = SpendingPlanStrategy(
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annual_real_adjust_pct=0.02,
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guardrail_threshold_pct=0.80,
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guardrail_cut_pct=0.10,
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)
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out = s.propose_withdrawal(state(year_idx=3, portfolio=700_000.0,
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last_withdrawal=40_000.0))
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# 40_000 * 1.02 = 40_800; trigger; 40_800 * 0.90 = 36_720
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assert abs(out - 36_720.0) < 1e-6
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def test_guardrail_disabled_when_threshold_none() -> None:
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s = SpendingPlanStrategy(guardrail_threshold_pct=None)
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out = s.propose_withdrawal(state(year_idx=3, portfolio=10_000.0,
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last_withdrawal=40_000.0))
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assert out == 40_000.0 # no cut despite tiny portfolio
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def test_returns_zero_when_portfolio_drained() -> None:
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s = SpendingPlanStrategy()
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out = s.propose_withdrawal(state(year_idx=5, portfolio=0.0, last_withdrawal=40_000.0))
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assert out == 0.0
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