Risk disclosure

CubeQuants Abyss v6.9.0 — Negative-Position Control Risk Notice

Risk notice for CubeQuants Abyss v6.9.0, ETHUSDT: how far a negative position can hold under negative-position control, and when it fails.

CubeQuants Abyss v6.9.0 ETHUSDT trading pair Risk notice for the negative extreme systemic quantitative control model
"If we fall into the Abyss, then we fight emotion with rules"
🎯 In plain terms: "Under extreme conditions, how far can a negative position hold under negative-position control, and under what conditions does it die".
Trading pairETHUSDT
Initial price2000 U
Initial orders8 orders
Total orders60 orders
Investment per order100 U
Capital / Leverage2000 U / 3×
Final average price1580.84 U
Final current price1226.17 U
Liquidation price1070.12 U
Safe decline tolerance38.69%
Maximum decline tolerance46.49%
Final unrealized loss (Phase 6, fully loaded orders)1197.65 U
💡 Negative-position control risk notice: The "cumulative unrealized loss" in each row = the unrealized loss calculated at that phase's trigger price when the last order of that phase has been filled (i.e. the actual loss at that moment). At most it can withstand a straight-line decline of 774U (at which point there is still 12.73% left before the liquidation line), which is a very safe position in ETHUSDT futures trading. Note: this is an extreme-data simulation test, with the positive position at 0 profit and no rebound during the decline, but then again, if you insist on arguing with me about a straight-line crash of 930U (774+156), then forget I said anything. This reveals the basic prototype of CubeQuants negative risk control (the actual model has roughly three or four more dimensions of influence plus AI decisions, with a decision influence rate of about 20-30%, which is confidential and cannot be disclosed).
Phase Orders at end Current price Cumulative decline
(from 2000)
Liquidation price
(3× leverage)
Safety distance
trigger price→liquidation price
Cumulative investment Cumulative quantity Phase average price Cumulative unrealized loss
(calculated at trigger price)
Status
Initial phase Order 8 2000.00 0% −3000.00 800 0.40000 2000.00 0.00 ✅ Safe
Phase 1 Order 10 1933.33 3.33% −1984.30 1000 0.50327 1987.33 26.69 ✅ Safe
Phase 2 Order 15 1828.59 8.57% −725.83 1500 0.77397 1940.69 84.70 ✅ Safe
Phase 3 Order 21 1710.63 14.47% −53.88 2100 1.11989 1882.08 184.52 ✅ Safe
Phase 4 Order 30 1567.29 21.64% 437.79 1129.50 3000 1.68150 1799.53 364.63 ⚠️ Caution
Phase 5 Order 42 1409.13 29.54% 778.98 630.15 4200 2.50835 1702.31 665.75 ⚠️ Caution
Phase 6 Order 60 1226.17 38.69% 1070.12 156.05 6000 3.91558 1580.84 1197.65 🔴 High risk
Death phase Full 60 orders 1070.12 46.49% 1070.12 0 6000 3.91558 1580.84 2000.00 🔴 Death
⚔️ Strategy comparison · CubeQuants Abyss vs Martingale Fundamentally different
Comparison dimension ♠️ Martingale strategy 🪤 CubeQuants Abyss strategy
Position-adding amount Multiplicative increase: 1, 2, 4, 8, 16… doubling every time Fixed equal amount: 100U per order, never increases
Position-adding spacing Fixed spacing: add a position every fixed number of points dropped Dynamic expansion: 60→120→180→***→***→***, the deeper it falls the wider the spacing
Core purpose Cover all losses with one large order; a tiny rebound breaks even Distribute evenly to average down cost and withstand larger negative swings
Break-even logic Break even as soon as price rebounds to the last entry price (triggered very easily) Take profit and reduce positions at low rebounds (continuously trade small losses for a lower average entry price)
Liquidation risk Extremely high; after a few rounds the single order is huge, and one move without a rebound liquidates you Relatively controllable; every order is fixed and orders stay dispersed without over-concentration at high levels
Capital consumption Exponential growth; after 10 rounds you need 1024× the initial capital Linear growth; 60 orders = 6000U, fully predictable
Applicable scenarios Ranging markets (price oscillating back and forth) Compatible with ranging and extreme market conditions (decline <=774)
📐 Appendix · CubeQuants system architecture Full model composition
🪤 CubeQuants Abyss Negative control · Disclosed
Core positioningDefense · Accumulation · Extreme resistance
Position-adding methodFixed equal amount (100U per order)
Position-adding spacingDynamic expansion: 60→120→180→***→***→***
Decline tolerance38.69%~46.49% (2000 → 1226.17 → 1070.12)
Liquidation price1070.12
✅ The basic model is disclosed in this document. It provides negative position management with steps to retreat along and a floor to defend amid panic, spreads cost evenly, and withstands larger fluctuations.
🌅 CubeQuants Daybreak Positive harvesting · To be disclosed
Core positioningOffense · Harvesting · Catching reversals
Trigger logicAfter the Abyss, the hour of daybreak
Harvesting methodTake profit and reduce positions at low rebounds
Relation to the AbyssOffense-defense alliance · Causal linkage
🔜 To be disclosed Dynamic harvesting is applied to positive positions, locking in rebound profits by rules at the end of every panic. The Abyss accumulates strength, Daybreak harvests, forming a closed loop.
⚙️ CubeQuants Pivot · Order execution system Execution layer · To be disclosed
🔜
📊 CubeQuants Pivot·Chenheng
Mean-referenced order placement
Takes the time-series mean as its benchmark, executing disciplined deployment when price returns to normal.
🔜
⚡ CubeQuants Pivot·Jiyao
Extreme-value-referenced order placement
Captures the highlights and troughs at the extreme edges, acting only at the market's extreme boundaries.
🔜
📡 CubeQuants Pivot·Lingxing
Signal-referenced order placement
Orders are as firm as military commands; a signal is the trend. Fully obey system signals with absolute discipline.
🧩 Chenheng sets the base · Jiyao catches the edges · Lingxing executes the middle — together they form a complete order-placement decision matrix  (all to be disclosed later)
⏳ Full parameters for CubeQuants Daybreak & CubeQuants Pivot will be disclosed in upcoming versions. Stay tuned.

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