research(surfer): crypto edge-falsification probes — intraday/cascade dead, stablecoin peg-reversion validated
- crypto_mft_xsec / mft_*: intraday/MFT XS price edge FALSIFIED (fee-trap) - crypto_cascade_reversion: liquidation-cascade reversion FALSIFIED (continuation) - crypto_trend_sizing: TS-trend return-engine reconfirmed (Sharpe ~1.25) - crypto_stablecoin_dislocation/harden/intraday: short-rich peg-reversion VALIDATED (bounded, uncorrelated); long-cheap = death-spiral trap Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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jgrusewski
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scripts/surfer/crypto_cascade_reversion.py
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scripts/surfer/crypto_cascade_reversion.py
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#!/usr/bin/env python3
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"""Cascade reversion — do crypto coins BOUNCE after an extreme forced-flow down-move?
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Liquidation cascades are forced deleveraging that overshoots; the harvestable consequence is the
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mean-reversion bounce. Binance killed the historical liquidation feed (live websocket only), so we
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test the PROXY already on disk: extreme negative trailing-H return = a cascade. Pre-registered:
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formation: trailing-H log return per coin (cross-sectional)
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signal: LONG the bottom-q fraction (biggest losers) — long-only on crashed names
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hold: next H hours, NON-OVERLAPPING rebalance
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cost: 5 bp / leg on actual weight turnover
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two builds: raw_long (equal-weight losers, has crypto beta)
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hedged (long losers − short equal-weight UNIVERSE basket; beta-neutral, short leg
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is the diversified basket NOT a single coin → dodges the short-melt-up ruin
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that killed generic XS reversal)
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KILL: net annualized SR < 0.5 OR not positive in most years (chrono) → cascade reversion closed.
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LIMITATION: npz panel has close only (no volume) → cannot condition on the volume spike that
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confirms a true liquidation cascade; the extreme-return tail is the proxy. Flagged, not hidden.
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"""
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import math
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import os
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import numpy as np
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OUT = "data/surfer/crypto1h"
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COST_BP = 5.0
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SYMS = ["BTCUSDT", "ETHUSDT", "SOLUSDT", "XRPUSDT", "BNBUSDT", "DOGEUSDT", "ADAUSDT", "AVAXUSDT",
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"LINKUSDT", "LTCUSDT", "DOTUSDT", "TRXUSDT", "BCHUSDT", "ETCUSDT", "FILUSDT", "ATOMUSDT"]
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HOUR_MS = 3_600_000
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HOLDS = [1, 2, 4, 8, 12, 24] # formation == hold, hours
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Q = 0.20 # bottom quintile = biggest losers
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def build_panel():
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series = {}
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for s in SYMS:
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cache = f"{OUT}/{s}.npz"
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if not os.path.exists(cache):
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continue
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d = np.load(cache)
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if len(d["ts"]) > 24 * 60:
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series[s] = (d["ts"], d["close"])
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allts = sorted(set().union(*[set((ts // HOUR_MS).tolist()) for ts, _ in series.values()]))
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tindex = {t: i for i, t in enumerate(allts)}
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syms = sorted(series)
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P = np.full((len(allts), len(syms)), np.nan)
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for j, s in enumerate(syms):
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ts, c = series[s]
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for t, px in zip(ts // HOUR_MS, c):
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P[tindex[int(t)], j] = px
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yrs = np.array([1970 + int(t) // int(365.25 * 24) for t in allts])
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return P, syms, yrs
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def ann(rets, per_year_factor):
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rets = np.asarray(rets)
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if len(rets) < 20 or rets.std() == 0:
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return float("nan"), float("nan")
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sr = rets.mean() / rets.std()
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t = rets.mean() / (rets.std() / math.sqrt(len(rets)))
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return sr * per_year_factor, t
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def run():
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P, syms, yrs = build_panel()
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T, N = P.shape
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logP = np.log(P)
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print(f"\n===== CRYPTO CASCADE REVERSION (long the crashed names, net {COST_BP}bp/leg) =====")
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print(f"panel: {T} hours x {N} coins years {int(yrs.min())}-{int(yrs.max())} q={Q} (bottom quintile)")
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print("LONG bottom-q losers; hedged = long losers - short equal-wt universe basket\n")
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hdr = f"{'hold':>5} {'periods':>8} {'build':>8} {'net_SR':>8} {'t(net)':>7} {'hit%':>6} {'per-year net-SR (chrono)':>30}"
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print(hdr); print("-" * len(hdr))
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for H in HOLDS:
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pf = math.sqrt(24 * 365 / H)
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idx = np.arange(H, T - H, H) # need t-H for formation, t+H for fwd
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raw, hed, yr_raw, yr_hed = [], [], [], []
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w_raw_prev = np.zeros(N); w_hed_prev = np.zeros(N)
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for t in idx:
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past = logP[t] - logP[t - H]
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fwd = logP[t + H] - logP[t]
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ok = np.isfinite(past) & np.isfinite(fwd)
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n_ok = int(ok.sum())
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if n_ok < 6:
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continue
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okidx = np.where(ok)[0]
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k = max(1, int(round(Q * n_ok)))
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losers = okidx[np.argsort(past[okidx])[:k]] # most-negative trailing return
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# raw long
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w_raw = np.zeros(N); w_raw[losers] = 1.0 / k
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# hedged: long losers - short equal-weight universe basket
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w_hed = np.zeros(N); w_hed[losers] += 1.0 / k; w_hed[okidx] -= 1.0 / n_ok
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r_raw = float(np.nansum(w_raw * fwd)) - np.abs(w_raw - w_raw_prev).sum() * COST_BP / 1e4
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r_hed = float(np.nansum(w_hed * fwd)) - np.abs(w_hed - w_hed_prev).sum() * COST_BP / 1e4
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raw.append(r_raw); hed.append(r_hed)
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yr_raw.append(int(yrs[t])); yr_hed.append(int(yrs[t]))
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w_raw_prev = w_raw; w_hed_prev = w_hed
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if len(raw) < 20:
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print(f"{H:>5} (too few periods)"); continue
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for name, series, yrl in (("raw_long", raw, yr_raw), ("hedged", hed, yr_hed)):
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sr, t = ann(series, pf)
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hit = 100.0 * np.mean(np.asarray(series) > 0)
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py = {}
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for r, y in zip(series, yrl):
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py.setdefault(y, []).append(r)
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pystr = " ".join(f"{y}:{(np.mean(v)/(np.std(v)+1e-12)):+.2f}"
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for y, v in sorted(py.items()) if len(v) >= 10)
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tag = f"{H}h" if name == "raw_long" else ""
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print(f"{tag:>5} {len(series):>8} {name:>8} {sr:>+8.2f} {t:>+7.2f} {hit:>6.1f} {pystr}")
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print("-" * len(hdr))
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print("PASS: hedged net SR > 0.5, t>=2, positive in most years. Else cascade reversion closed.")
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if __name__ == "__main__":
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run()
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