69 lines
3.3 KiB
Python
69 lines
3.3 KiB
Python
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"""Retail's own side looked positive once the fill was fixed. Is that the pattern or the drift?
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Retrial 1 killed the fade and inverted it: on USDJPY, XAUUSD and SP500 the fade loses 0.05
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to 0.14 R because retail's trend-following setups are on the right side of instruments that
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rose for the whole sample. Several cells show retail's own expR positive - SP500 H1 engulf
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+0.113, XAUUSD H1 engulf +0.095 - and a POSITIVE base would be better than the near-zero one
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step 2 is hunting for.
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Before any of that is believed it has to beat the control that makes the boring explanation
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explicit:
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CONTROL = random bars drawn from the SAME trend-filter state, same direction, same entry
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mechanics (a stop through the bar's extreme), same stop rule, same n.
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Everything is held fixed except the candlestick itself. If retail's edge is really "buy the
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break of any bar's high while the 20-MA is rising, on something that went up", the control
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matches it and the pattern is worth nothing. That is the same shape of control that killed
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"stops are a farmable magnet".
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Reported on the NON-OVERLAPPING subset, and the difference carries its own standard error
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rather than being eyeballed from two columns.
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"""
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import numpy as np, sys
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sys.stdout.reconfigure(encoding='utf-8', errors='replace')
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import fills, book, retrial
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SYMS = ('EURUSD', 'USDJPY', 'XAUUSD', 'SP500')
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def diff_t(a, b):
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"""Welch t for the difference of two independent means."""
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se = np.sqrt(a.var(ddof=1) / len(a) + b.var(ddof=1) / len(b))
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return (a.mean() - b.mean()) / max(se, 1e-12)
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if __name__ == '__main__':
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syms = [s for s in sys.argv[1:] if s in SYMS] or list(SYMS)
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print("=== RETRIAL 2: is retail's trend side a PATTERN, or just drift? ===")
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print(" control = same trend state, same direction, same entry, random bar.")
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print(" 'excess' is pattern minus control on independent trades - the real claim.\n")
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print(f" {'sym':>7}{'tf':>5}{'setup':>8}{'dir':>4}{'k':>3}"
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f"{'n':>6}{'pattern':>9}{'t':>6}{'ctrl n':>7}{'control':>9}{'t':>6}"
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f"{'EXCESS':>9}{'t':>6}")
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tally = []
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for sym in syms:
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bk = fills.Book(sym)
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for tf in ('M15', 'H1'):
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f = book.frame(sym, tf, bk)
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for k in (1.0, 2.0):
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pat = retrial.retail_arm(sym, tf, k=k, bk=bk, f=f)
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ctl = retrial.retail_arm(sym, tf, k=k, control=True, bk=bk, f=f)
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cmap = {(nm, d): o for nm, d, o in ctl}
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for nm, d, o in pat:
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c = cmap.get((nm, d))
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if c is None:
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continue
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A = o['R'][o['indep']]; B = c['R'][c['indep']]
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ex = A.mean() - B.mean()
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t = diff_t(A, B)
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tally.append(ex)
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print(f" {sym:>7}{tf:>5}{nm:>8}{d:>+4}{k:>3.0f}"
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f"{len(A):>6}{A.mean():>+9.4f}{book.tstat(A):>+6.2f}"
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f"{len(B):>7}{B.mean():>+9.4f}{book.tstat(B):>+6.2f}"
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f"{ex:>+9.4f}{t:>+6.2f}")
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ex = np.array(tally)
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print(f"\n {len(ex)} cells mean excess {ex.mean():+.4f} "
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f"positive {int((ex>0).sum())}/{len(ex)}")
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print(" A pattern with real content clears its control in most cells and by a margin")
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print(" that does not shrink when the sample is made independent.")
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