71 lines
2.6 KiB
Python
71 lines
2.6 KiB
Python
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"""End-to-end test that flex-spending rules survive £ in the portfolio."""
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from __future__ import annotations
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import numpy as np
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from fire_planner.flex_spending import FlexRule
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from fire_planner.glide_path import static
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from fire_planner.simulator import simulate
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from fire_planner.strategies.trinity import TrinityStrategy
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from fire_planner.tax.uae import UaeTaxRegime
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def _flat_paths(n_paths: int, n_years: int, real_return: float = 0.0) -> np.ndarray:
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"""Returns paths cube where real return == 0% — easy to reason about."""
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paths = np.zeros((n_paths, n_years, 3), dtype=np.float64)
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paths[:, :, 0] = real_return # nominal stocks
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paths[:, :, 1] = real_return # nominal bonds
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paths[:, :, 2] = 0.0 # cpi
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return paths
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def test_flex_rule_saves_money_at_drawdown() -> None:
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"""A scenario that drops below ATH triggers a discretionary cut and
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ends up richer than the same scenario with no flex rules."""
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paths = _flat_paths(n_paths=10, n_years=5, real_return=-0.05)
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initial = 1_000_000.0
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common = dict(
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paths=paths,
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initial_portfolio=initial,
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spending_target=10_000.0,
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glide=static(1.0),
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strategy=TrinityStrategy(),
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regime=UaeTaxRegime(),
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horizon_years=5,
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cashflow_adjustments=np.full(5, -20_000.0, dtype=np.float64),
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discretionary_outflows=np.full(5, 20_000.0, dtype=np.float64),
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)
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no_flex = simulate(**common)
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with_flex = simulate(
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**common,
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flex_rules=[FlexRule(from_ath_pct=0.05, cut_discretionary_pct=0.50)],
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)
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no_flex_end = float(np.median(no_flex.portfolio_real[:, -1]))
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with_flex_end = float(np.median(with_flex.portfolio_real[:, -1]))
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assert with_flex_end > no_flex_end
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assert no_flex_end > 0 # didn't ruin — meaningful comparison
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def test_flex_rule_no_op_without_drawdown() -> None:
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"""Strong-positive returns, never below ATH → flex rules do nothing."""
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paths = _flat_paths(n_paths=10, n_years=5, real_return=0.10)
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common = dict(
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paths=paths,
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initial_portfolio=1_000_000.0,
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spending_target=40_000.0,
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glide=static(1.0),
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strategy=TrinityStrategy(),
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regime=UaeTaxRegime(),
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horizon_years=5,
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cashflow_adjustments=np.full(5, -10_000.0, dtype=np.float64),
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discretionary_outflows=np.full(5, 10_000.0, dtype=np.float64),
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)
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no_flex = simulate(**common)
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with_flex = simulate(
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**common,
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flex_rules=[FlexRule(from_ath_pct=0.10, cut_discretionary_pct=0.50)],
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)
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assert np.allclose(no_flex.portfolio_real, with_flex.portfolio_real)
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