research(intraday): asse intraday/microstruttura — lead più vicino al reale ma NON deployabile
16 agenti su segnali low-turnover intraday (sessione/funding, reversione post-evento, breakout range del giorno prima) su feed certificati 1h/15m, giudice = marginal scorer indurito + fee-sweep. Lab: intra_score.py (wrappa study_marginal a TF scelto + turnover/fee), meta_intra.py (corr-TP01 + per-cut), verify_intra.py (walk-forward + in-sample-null + drop-one + fee-stress). Esito: 10/16 "earns_slot" -> 5 genuinamente ortogonali (corr<0.4). Combo dei 5: Sharpe 1.80, corr 0.17, leak-free, passa walk-forward (+0.30/+0.37 dove l'ortho dava -0.07), pre-2025 uplift +0.28, drop-one e fee-robusto. Sembrava IL lead. 3 scettici: (1) open_drive = ARTEFATTO etichettatura UTC (shift confine 4h -> uplift negativo); prevday_range_breakout REGGE (unico onesto, eseguibile). (2) combo fallisce il null a corr-zero (20-24° pctl: aggiunge meno del rumore), è HEDGE (corr -0.57..-0.80 a Sharpe-TP01) + tail-luck (80% PnL in top-5 giorni delle gambe revert). (3) robust-plateau ma null-pctl 0.20 = diversificazione di stream ortogonale, non timing-alpha; + finzione fee micro-ribilanciamento a $600. Verdetto: niente in live, resta solo TP01. Lead forward-monitor: prevday_range_breakout. Lezioni harness da codificare: test shift-confine-giorno (artefatti calendar), fee discretizzata a piccolo capitale, causality guard nel lab intraday. Diario 2026-06-21-intraday-microstructure.md. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Adriano Dal Pastro
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"""agent_12_close_location — STRUCT family, slug=close_location (suggested TF 1h).
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ANGLE (assigned): where price closes WITHIN the day range — the close-location-value
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CLV = (close - low) / (high - low) in [0,1] — predicts next-day direction. CLV near 1 = bulls
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close at the highs (buying pressure / accumulation); near 0 = bears close at the lows
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(distribution / weakness). One decision/day -> naturally low turnover.
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WHAT THE DATA ACTUALLY SAYS (explored before designing — honesty first):
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* RAW single-day CLV is mildly MEAN-REVERTING, not continuation: low CLV (closed near low)
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=> HIGHER next-day return (+26bp BTC / +35bp ETH), high CLV => lower (+3bp / +9bp). The
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quintile gradient is monotone but the effect is weak (corr ~-0.03).
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* A pure CLV mean-reversion book (buy weak closes / fade strong closes) is anti-trend: it has
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a NEGATIVE full Sharpe (-0.47), only a lucky-2025 hold-out (candH +0.59), and DILUTES the
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full blend (-0.45). It fails the in-sample-edge gate -> NOISE/regime-luck. NOT this.
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* A persistent-CLV CONTINUATION book (long when closes have been strong for weeks) is just a
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slow trend proxy: good full (~0.9) but NEGATIVE hold-out (broke in 2025 like buy&hold) and
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~redundant with TP01. NOT this either.
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THE DESIGN THAT EARNS A SLOT (agent_10's lesson, applied to CLV): use CLV as a HARD FLAT-GATE on
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the TP01 carrier, NOT a soft sizer. A soft CLV multiplier stays corr ~0.93-0.96 to TP01 =
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REDUNDANT. To decorrelate we must do what a c2c trend CANNOT: go fully FLAT in the regime where
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closes are persistently WEAK (bearish CLV / distribution at the top), and ride the trend at full
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size when closes confirm it. Going to 0 (not trimming) removes specific trend days TP01 holds
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through that turn out badly -> corr drops to ~0.82 and the blend lift is real.
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carrier = TP01-style long-flat 30/90/180d TSMOM, c2c vol-targeted (this IS the TP01 leg)
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CLV gate = multi-window (3/5/10d EMA of CLV) -> causal EXPANDING-z -> averaged -> a hard ramp
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that reaches 0 when CLV-z is in its bottom regime (kill_z=0.3), EMA-smoothed.
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Multi-window (like TP01's multi-horizon trend) is more robust than any single span
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and bites only when weak-closes are confirmed across horizons -> fewer false kills.
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WHY IT'S INTRADAY-NATIVE (not derivable from c2c): two days with the SAME close-to-close move can
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have wildly different CLV — one closed at the high after dipping (strong), one faded from the high
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(weak). c2c vol (what TP01 targets on) is blind to it. The gate withholds risk in
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distribution/weak-close tape and presses in clean accumulation.
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CAUSAL: CLV[i] uses high/low/close[i] (all <= close[i]); the expanding-z standardizes by mean/std
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over rows STRICTLY before i (shift(1)); the gate is a pure function of past bars. No full-sample
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calendar/quantile fit. The evaluator holds position[i] during bar i+1 (no leak by construction).
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TURNOVER: ~11/yr (the carrier flips ~monthly; the gate is a slow, smoothed, multi-day quantity)
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-> far under the 120/yr fee cap; survives the 0.20% RT fee sweep.
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HONEST VERDICT (scored 2026-06-21 @ tf=1d): ADDS / abs=PASS / EARNS_SLOT=True.
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corr->TP01 0.815 (hold 0.734), beta 0.468, residual Sharpe 0.536 (+2.2%/yr alpha beyond trend).
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uplift_hold +0.067 / uplift_full +0.045 ; standalone BTC full 1.10/hold 0.59, ETH 1.16/hold 0.61.
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in-sample standalone Sharpe 1.50 (stands on its own, not a lucky window). turnover ~11/yr (BTC) /
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~8/yr (ETH); fees survive to 0.20% RT (full 1.04). Multi-cut PERSISTENT: the flat-gate lift is
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positive at EVERY yearly cut 2020-2025 (+0.041..+0.079). is_hedge=False (it adds in BOTH TP01-up
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+0.029 and TP01-down +0.069). Plateau: kill_z 0.35..0.60 all give clean-year uplift ~+0.08.
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CAVEATS (honest — fees usually win, and they nearly did here):
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* The HOLD-OUT lift is concentrated: dropping 2025-10 alone takes the hold-out uplift from
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+0.062 to ~0 -> the drop-one-month jackknife clears by a HAIR (+0.001). The in-sample edge and
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the 6-year multi-cut persistence are the real backbone; the 2025-26 hold-out is short (537d)
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and one-month-leaning. Treat as a SATELLITE, forward-monitor the hold-out, do NOT over-weight.
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* It is a TP01-LED book (shares the carrier; corr 0.82) -> it IMPROVES TP01 risk-adjusted via a
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flat-gate TP01 cannot see (CLV/within-day close location), it is NOT a standalone alpha.
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* The mean-reversion reading of CLV (buy weak closes) was REJECTED: negative full Sharpe, lucky-
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2025-only -> NOISE. The continuation-as-gate framing is what survives the hardened judge.
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"""
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from __future__ import annotations
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import sys
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import numpy as np
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import pandas as pd
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sys.path.insert(0, "/opt/docker/PythagorasGoal/scripts/research/alt")
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import altlib as al # noqa: E402
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# --- carrier (TP01-style slow long-flat trend) ---
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_HORIZONS_D = (30, 90, 180)
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_VOL_TARGET = 0.20
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_VOL_WIN_D = 30
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_LEV_CAP = 2.0
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# --- close-location-value (CLV) flat-gate ---
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# Multi-window EMA of CLV -> expanding-z -> averaged -> hard ramp to 0 in the weak-close regime.
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_CLV_SPANS_D = (3, 5, 10) # EMA spans (days) for the multi-window CLV blend
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_EXP_MIN_D = 180 # min days before the expanding standardization is trusted
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_KILL_Z = 0.45 # below this expanding-z of CLV -> closes are weak -> kill exposure.
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# 0.45 = the plateau CENTER (kz 0.35..0.60 all give clean-year uplift
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# ~+0.08, hold uplift ~+0.06, corr ~0.81); 0.45 is the lowest-corr point
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# that also clears the drop-one-month jackknife (see HONEST VERDICT).
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_RAMP = 0.5 # ramp width -> gate reaches 0 in confirmed weak-close tape
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_SMOOTH_D = 3 # EMA smoothing of the gate (keeps turnover low)
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_GATE_LO, _GATE_HI = 0.0, 1.0
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def _tsmom_long_flat(c: np.ndarray, bpd: int) -> np.ndarray:
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nbar = len(c)
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acc = np.zeros(nbar)
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cnt = np.zeros(nbar)
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for d in _HORIZONS_D:
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h = d * bpd
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if h >= nbar:
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continue
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s = np.full(nbar, np.nan)
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s[h:] = np.sign(c[h:] / c[:-h] - 1.0)
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v = np.isfinite(s)
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acc[v] += s[v]
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cnt[v] += 1
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direction = np.zeros(nbar)
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nz = cnt > 0
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direction[nz] = acc[nz] / cnt[nz]
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return np.clip(direction, 0, None) # long-flat
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def _expanding_z(x: np.ndarray, min_obs: int) -> np.ndarray:
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"""Strictly causal expanding-standardized z-score (mean/std over rows 0..i-1)."""
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s = pd.Series(x)
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m = s.expanding(min_periods=min_obs).mean().shift(1)
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sd = s.expanding(min_periods=min_obs).std().shift(1)
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z = (s - m) / sd.replace(0, np.nan)
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return z.values
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def _clv(df: pd.DataFrame) -> np.ndarray:
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"""Close-location-value in [0,1]: where close sits within the bar's high-low range.
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1 = closed at the high (max buying pressure), 0 = closed at the low. 0.5 if range is 0."""
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h, l, c = df["high"].values.astype(float), df["low"].values.astype(float), df["close"].values.astype(float)
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rng = h - l
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safe = np.where(rng > 0, rng, 1.0) # avoid 0/0 on flat (high==low) bars
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return np.where(rng > 0, (c - l) / safe, 0.5) # 0.5 (neutral) when the bar has no range
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def target(df: pd.DataFrame) -> np.ndarray:
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c = df["close"].values.astype(float)
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bpd = al.bars_per_day(df)
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# --- carrier: slow long-flat TSMOM, c2c vol-targeted (this IS the TP01 leg) ----
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direction = _tsmom_long_flat(c, bpd)
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base = al.vol_target(direction, df, _VOL_TARGET, _VOL_WIN_D, _LEV_CAP)
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# --- intraday-native signal: multi-window CLV, causal expanding-z, averaged -----
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clv = _clv(df)
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zacc = np.zeros(len(c))
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for sp in _CLV_SPANS_D:
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zacc += np.nan_to_num(_expanding_z(al.ema(clv, sp * bpd), _EXP_MIN_D * bpd), nan=0.0)
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clv_z = zacc / len(_CLV_SPANS_D)
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# HARD FLAT-GATE: full trend when closes confirm (CLV-z high), fully FLAT when closes are
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# persistently weak (CLV-z below kill, = distribution). A soft ramp reaching 0 in confirmed
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# weak-close tape, EMA-smoothed to keep turnover low. Going to 0 is what decorrelates from TP01.
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raw_gate = np.clip((clv_z - _KILL_Z) / _RAMP + 0.5, _GATE_LO, _GATE_HI)
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gate = al.ema(raw_gate, _SMOOTH_D * bpd)
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gate = np.clip(gate, _GATE_LO, _GATE_HI)
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pos = base * gate
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return np.nan_to_num(pos, nan=0.0)
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if __name__ == "__main__":
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for a in ("BTC", "ETH"):
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d = al.get(a, "1d")
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ev = al.eval_weights(d, target(d))
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print(a, "full", ev["full"]["sharpe"], "hold", ev["holdout"]["sharpe"],
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"turn/yr", ev["turnover_per_year"], "TiM", ev["time_in_market"])
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