"""Independent numerical checks for three Tradewink Learn studies.

Run: python3 equity-research-labs.py
Python standard library only. Fully synthetic; no network, credentials, brokers,
files or trading actions. This checks arithmetic, not market risk calibration.
It enumerates all full-horizon rotations; it does not reproduce the separate
NumPy implementation's random stream or block-one simulation percentiles.
"""

import json
import math


def drawdown(values):
    peak = values[0]
    worst = 0.0
    for value in values:
        peak = max(peak, value)
        worst = max(worst, 100 * (1 - value / peak))
    return worst


def check_studies():
    closing = [100, 100, 100]
    intraday = [100, 70, 100, 70, 100]
    assert drawdown(closing) == 0
    assert math.isclose(drawdown(intraday), 30)
    cash, requests = 1000, [800, 800]
    fraction = cash / sum(requests)
    quantities = [requests[0] * fraction / 10, requests[1] * fraction / 20]
    terminal = quantities[0] * 12 + quantities[1] * 18
    assert fraction == 0.625 and quantities == [50, 25] and terminal == 1050
    returns = [-0.1, -0.1, 0.25] + [0.0] * 17
    rotations = []
    for start in range(len(returns)):
        equity = [100.0]
        for offset in range(len(returns)):
            equity.append(equity[-1] * (1 + returns[(start + offset) % len(returns)]))
        terminal_pct = 100 * (equity[-1] / equity[0] - 1)
        assert math.isclose(terminal_pct, 1.25, abs_tol=1e-10)
        rotations.append({"start": start, "terminal_return_pct": terminal_pct, "max_drawdown_pct": drawdown(equity)})
    depths = [row["max_drawdown_pct"] for row in rotations]
    assert math.isclose(min(depths), 10) and math.isclose(max(depths), 19)
    return {
        "synthetic_only": True,
        "closing_drawdown_pct": drawdown(closing),
        "intraday_drawdown_pct": drawdown(intraday),
        "shared_capital": {"fill_fraction": fraction, "quantities": quantities, "terminal_equity": terminal},
        "full_horizon_rotations": rotations,
    }


if __name__ == "__main__":
    print(json.dumps(check_studies(), indent=2, allow_nan=False))