Warrior_EA/research/test_adverse.py

"""The last claim left standing: is a broken edge a WORSE place to buy than a random level?

Everything else closed negative tonight. One sub-result survived: on EURUSD H1, a limit order
resting at the actual broken range edge did worse than the same order the same distance away
at a permuted level - `real - placebo` of -0.077 and -0.074 at phi >= 1. That is adverse
selection, and it is the mechanism book 2's A/B test proposed (a pullback deep enough to
reach the level is disproportionately a breakout that has already failed).

It is not tradeable - it is a reason NOT to do something - but it is a claim about market
structure and it was measured on one instrument. The five breadth instruments never had a
hand in finding it, so they can settle it the same way they settled the context score.

  arm REAL      buy limit at price_now - phi*(price_now - broken_edge)
  arm PLACEBO   the same distance from the same starting price, distances permuted across
                events: geometry identical, level identity destroyed

Both arms pay the same spread and meet the same tie convention, so cost cancels in the
difference. The prediction, fixed in advance from the mechanism: real - placebo is NEGATIVE,
and MORE negative as phi rises, because a deeper level selects harder against you.

Note the sign convention: a negative number CONFIRMS the hypothesis here.
"""
import numpy as np, sys
sys.stdout.reconfigure(encoding='utf-8', errors='replace')
import fills, book, wyckoff, breadth

NATIVE = ('EURUSD', 'USDJPY', 'XAUUSD', 'SP500')
PHIS = (0.5, 1.0, 1.5)


def cells(tfs):
    for tf in tfs:
        for s in NATIVE:
            bk = fills.Book(s)
            yield s, tf, bk, book.frame(s, tf, bk), 'original'
        for s in breadth.SPREAD_BP:
            bk, f = breadth.get(s, tf)
            yield breadth.NICE[s], tf, bk, f, 'new'


def gap(bk, f, sym, tf, phi, ev, seeds=(11, 23, 37)):
    """real minus placebo, averaging the placebo over several permutations."""
    a = wyckoff.retest(sym, tf, phi, mrisk=2.0, kR=2.0, wait=40, H=200,
                       bk=bk, f=f, ev=ev)
    if a is None:
        return None
    A = a['R'][a['indep']]
    bs = []
    for sd in seeds:
        b = wyckoff.retest(sym, tf, phi, mrisk=2.0, kR=2.0, wait=40, H=200,
                           bk=bk, f=f, ev=ev, placebo=sd)
        if b is not None:
            bs.append(b['R'][b['indep']])
    if not bs:
        return None
    B = np.concatenate(bs)
    se = np.sqrt(A.var(ddof=1) / len(A) + B.var(ddof=1) / len(B))
    return len(A), A.mean(), B.mean(), A.mean() - B.mean(), (A.mean() - B.mean()) / max(se, 1e-12)


if __name__ == '__main__':
    tfs = tuple(a for a in sys.argv[1:] if a in ('M15', 'H1', 'H4')) or ('H1',)
    print("=== ADVERSE SELECTION AT THE BROKEN EDGE ===")
    print("    prediction: real - placebo is NEGATIVE and grows more negative with phi.")
    print("    a NEGATIVE number confirms the hypothesis.\n")
    print(f"  {'sym':>9}{'tf':>5}{'set':>10}" + "".join(f"{'phi='+str(p):>22}" for p in PHIS))
    print(f"  {'':>24}" + "".join(f"{'gap':>13}{'t':>9}" for p in PHIS))
    acc = {p: {'original': [], 'new': []} for p in PHIS}
    for s, tf, bk, f, kind in cells(tfs):
        ev = wyckoff.breakouts(f, score=False)
        if ev is None:
            continue
        line = f"  {s:>9}{tf:>5}{kind:>10}"
        any_ = False
        for p in PHIS:
            g = gap(bk, f, s, tf, p, ev)
            if g is None:
                line += f"{'-':>13}{'-':>9}"; continue
            n, a, b, d, t = g
            acc[p][kind].append(d)
            any_ = True
            line += f"{d:>+13.4f}{t:>+9.2f}"
        if any_:
            print(line)
    print()
    for p in PHIS:
        o, nw = np.array(acc[p]['original']), np.array(acc[p]['new'])
        al = np.concatenate([o, nw])
        print(f"  phi={p}:  original {o.mean():+.4f} ({int((o<0).sum())}/{len(o)} negative)"
              f"   NEW {nw.mean():+.4f} ({int((nw<0).sum())}/{len(nw)} negative)"
              f"   all {al.mean():+.4f} ({int((al<0).sum())}/{len(al)})")
    print("\n  The NEW column is out of sample: those instruments had no hand in finding this.")