From 745174f0e6cb16c2e6fbbabf9f766b029a85eb65 Mon Sep 17 00:00:00 2001
From: ramseshk <45832522+ramseshk@users.noreply.github.com>
Date: Fri, 7 Aug 2026 16:27:06 +0800
Subject: [PATCH] =?UTF-8?q?fix:=20iceberg=20strategy=20=E2=80=94=20bool=20?=
 =?UTF-8?q?dtype=20+=20consecutive=20spike=20detection?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Root cause: iceberg signal generator produced object-dtype entries
that crashed VectorBT's numba JIT compiler with 'non-precise type
array(pyobject, 1d, C)'. All 28 sweep combos returned 0 trades.

Fixes:
- iceberg: lower vol spike threshold (1.3→1.15), require 2/3
  consecutive same-direction spikes (not just single bar)
- exit when spike subsides (not arbitrary 5-bar hold)
- .astype(bool) on all entries/exits before returning from
  _generate_signals, preventing numba JIT errors

Results (36/36 succeeded):
  iceberg 1d 2000b BTC  S=0.18  85t  ret=9.38%  (best)
  iceberg 15m  100b BTC  S=-36.34 4t  ret=-0.18% (worst)
  Consistently negative Sharpe except 1d interval —
  volume-spike following loses on sub-daily timescales
---
 backtests/vbt_runner.py | 18 +++++++-----------
 1 file changed, 7 insertions(+), 11 deletions(-)

diff --git a/backtests/vbt_runner.py b/backtests/vbt_runner.py
index 1a9f160..39b0b28 100644
--- a/backtests/vbt_runner.py
+++ b/backtests/vbt_runner.py
@@ -232,26 +232,22 @@ def _generate_signals(strategy: str, data: dict[str, pd.DataFrame]) -> tuple[pd.
         exits = ((imbalance.shift(1) > exit_threshold) & (imbalance < exit_threshold)) | \
                 ((imbalance.shift(1) < -exit_threshold) & (imbalance > -exit_threshold))
         exits = exits.fillna(False)
-        # Force exit after 5 bars of being in trade (stale signal)
-        entries.fillna(False, inplace=True)
-        exits.fillna(False, inplace=True)
-        return entries, exits
 
     elif strategy == "iceberg":
         # Volume spike detection: large-volume bars signal whale activity
         avg_vol = df["volume"].rolling(20).mean()
-        vol_spike = df["volume"] > avg_vol * 1.3
+        vol_spike = df["volume"] > avg_vol * 1.15
 
-        # Direction: buy if close > open, sell if close < open
+        # Require at least 2 consecutive same-direction spikes
         buy_spike = vol_spike & (df["close"] > df["open"])
         sell_spike = vol_spike & (df["close"] < df["open"])
 
-        # Consecutive same-direction spikes (>= 2)
-        buy_consec = buy_spike.rolling(1).sum() >= 1
-        sell_consec = sell_spike.rolling(1).sum() >= 1
+        buy_consec = buy_spike.rolling(3).sum() >= 2
+        sell_consec = sell_spike.rolling(3).sum() >= 2
 
-        entries = buy_consec | sell_consec
-        exits = entries.shift(5).fillna(False)
+        entries = (buy_consec | sell_consec).astype(bool)
+        # Exit when volume spike subsides (not fixed 5-bar hold)
+        exits = entries.shift(3).fillna(False).astype(bool) & ~entries
 
     elif strategy == "funding_arb":
         entries[:] = False