Haozhe Wu
d3c76819c3
Fix live option guards, grounding operand evidence, source-bound benchmarks, trade artifacts, attribution, drawdowns, valuation tolerances, and SEC point-in-time factor inputs. Add Brazil research data and market support, 13 fundamental and valuation factors, channel progress forwarding, and opt-in ZimaOS templates. Update seven README News sections with three visible dates. Validation: 17,635 backend tests passed; 1,084 final targeted tests and 103 frontend tests passed. Frontend build, package build, documentation checks, and CI gates passed.
61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
"""A recovered high-water mark starts a new underwater episode."""
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from __future__ import annotations
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import json
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import pandas as pd
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import pytest
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from src.quantlib.risk import max_drawdown_analysis
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from src.tools.quantlib_tool import QuantlibCallTool
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@pytest.mark.parametrize(
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"values,peak,trough,recovery",
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[
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([100, 90, 100, 80, 100], 2, 3, 4),
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([100, 100, 80, 100], 1, 2, 3),
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([100, 80, 100, 70], 2, 3, None),
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([90, 100, 80, 110], 1, 2, 3),
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([100, 70, 100, 80], 0, 1, 2),
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([100, 100, 100], 0, 0, 0),
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],
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)
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def test_episode_starts_at_last_high_water_mark_before_worst_trough(
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values, peak, trough, recovery
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):
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result = max_drawdown_analysis(values)
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assert result["peak_date"] == peak
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assert result["trough_date"] == trough
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assert result["recovery_date"] == recovery
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assert result["peak_to_trough_periods"] == trough - peak
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assert result["max_drawdown"] == pytest.approx(1 - values[trough] / values[peak])
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def test_calendar_underwater_duration_excludes_an_already_recovered_episode():
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equity = pd.Series(
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[100, 90, 100, 80, 100],
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index=pd.to_datetime(
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["2025-01-01", "2025-01-02", "2025-01-10", "2025-01-12", "2025-01-15"]
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),
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)
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result = max_drawdown_analysis(equity)
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assert result["peak_date"] == pd.Timestamp("2025-01-10")
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assert result["underwater_days"] == 2
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assert result["recovery_days"] == 3
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def test_registered_quantlib_tool_reports_the_current_drawdown_episode():
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result = json.loads(
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QuantlibCallTool().execute(
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action="call",
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module="risk",
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function="max_drawdown_analysis",
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kwargs={"equity": [100, 90, 100, 80, 100]},
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)
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)
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assert result["ok"] is True
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assert result["result"]["peak_date"] == 2
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assert result["result"]["peak_to_trough_periods"] == 1
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