Quantum Oak

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Quantum Oak

Fund Offering
We buy the dip. We sell the recovery. Every time.

What We Do

Prices move. They overshoot, they undershoot, and then they correct. This pattern — mean reversion — is one of the most studied and persistent behaviors in financial markets.

Quantum Oak Capital builds algorithms that identify when prices have moved too far from their recent norms, then trades the correction. We trade across the U.S. equity universe, focusing on liquid large- and mid-cap stocks.

We use machine learning to adapt to changing market conditions and statistical methods to size positions and manage risk. The goal is consistent, risk-adjusted returns — not speculation.

Fund Overview

Fund NameQuantum Oak Capital
ManagerQuantum Oak Capital
DomicileUnited States
StrategyMean Reversion + Machine Learning on U.S. Equities
Target Return30%+ annualized
Asset UniverseU.S. Stock Equities (liquid large- and mid-cap names)
Why U.S. EquitiesDeep liquidity, tight spreads, and reliable price data going back decades — essential for the kind of statistical analysis we do
Research PartnerACR Institute — Artificial Consciousness Research Institute, Zürich

How It Works

Our strategy has three layers. Each one is straightforward on its own. The value is in how they work together.

1. Detect

Statistical models identify when a stock's price has deviated meaningfully from its recent average. Not every dip is an opportunity — the models filter for deviations that historically tend to reverse.

2. Adapt

Markets behave differently in calm periods versus volatile ones. Machine learning classifies the current regime and adjusts how aggressively we trade. In choppy markets, we pull back. In stable markets, we lean in.

3. Execute

Every trade has a predefined entry point, exit target, and stop-loss. Position sizes are calculated based on conviction level and current risk budget. No discretionary overrides.

A note on complexity: Our underlying math draws on advanced statistical methods. But the core idea is simple — buy when prices have fallen below where they should be, sell when they've recovered, and always know in advance how much you're willing to lose on any single trade.

Research Partner

ACR

ACR Institute

Artificial Consciousness Research Institute · Zürich, Switzerland

The mathematical foundations behind Quantum Oak's strategy are developed in collaboration with ACR Institute, a Zürich-based non-profit research institute. ACR studies the deep structure of how complex systems behave — what can be computed, what can't, and where the boundaries are. That research helps us build better models.

Specifically, ACR's work helps us improve how we detect market regimes, estimate probabilities, and design algorithms that adapt to conditions conventional models miss. The partnership means our quantitative methods are grounded in original scientific research, not off-the-shelf tools.

Focus

Mathematics of complex systems & computational limits

Structure

Swiss non-profit research institute

Web

acr.institute

Track Record

These are our live results. Real capital, real trades, since April 2025. ● LIVE

+94.7%
Cumulative Return
2.40
Sharpe Ratio
-23.9%
Max Drawdown
Win Rate
60.0%
Total Trades
65
P/L Ratio
1.30×
Calmar Ratio
3.53
Avg Win
$50.0K
Avg Loss
-$38.6K
Best Month
+31.8%
Worst Month
-27.7%
Avg Hold
18d
Max Win Streak
8
Max Loss Streak
4
Positive Months
9 / 12
Growth of $100 — Apr 2025 to Mar 2026
Quantum Oak +94.7%
ARKK +49.6%
QQQ +33.5%
S&P 500 +30.0%
PSH +7.6%
Monthly Returns
MonthQuantum OakPSH (Ackman)S&P 500Alpha vs PSHAlpha vs SPY
Apr 2025+9.6%+4.4%+7.1%+5.2+2.5
May 2025+28.9%+10.8%+7.8%+18.1+21.2
Jun 2025+10.6%+3.5%+4.4%+7.1+6.2
Jul 2025+20.8%-2.4%+2.9%+23.2+17.9
Aug 2025+6.3%+5.0%+1.4%+1.3+4.9
Sep 2025+31.8%+3.9%+3.1%+27.9+28.7
Oct 2025+6.6%-1.7%+0.8%+8.4+5.9
Nov 2025-1.5%+1.8%+2.1%-3.3-3.6
Dec 2025+11.0%-2.2%+0.3%+13.2+10.7
Jan 2026-27.7%-2.5%+1.5%-25.1-29.1
Feb 2026+3.3%-7.7%-1.5%+11.1+4.9
Mar 2026-5.3%-4.3%-2.8%-1.0-2.5
Cumulative+94.7%+7.6%+30.0%+87.0+64.6
Current NAV (Live) $1,947,000
Net Profit (Live) $947,000
Starting Capital $1,000,000
Inception 22 April 2025
Report Date 15 March 2026

We also ran a backtest from 2013–2025 which showed significantly higher returns (362% CAGR, 4.08 Sharpe). Backtests always look better than reality — the model has already seen the data. We include it for transparency, but we ask you to judge us on the live numbers above.

Past performance — whether backtested or live — does not guarantee future results. All investments carry risk, including loss of principal.

Comparisons

How Quantum Oak stacks up against well-known benchmarks and actively managed funds over the same period.

Risk-Adjusted Comparison
MetricQuantum OakARKK (Wood)QQQ (Nasdaq)S&P 500PSH (Ackman)
Total Return+94.7%+49.6%+33.5%+30.0%+7.6%
Ann. Return~94%~46%~30%~27%~9%
Ann. Volatility54.8%33.0%11.0%10.8%17.6%
Sharpe Ratio2.401.232.252.050.20
Max Drawdown-23.9%-21.1%-4.2%-4.3%-15.8%
Calmar Ratio4.032.358.047.060.47
Return / Drawdown4.0×2.3×8.0×7.0×0.5×
Positive Months9 / 127 / 129 / 1210 / 126 / 12
Best Month+31.8%+25.0%+8.4%+7.8%+10.8%
Worst Month-27.7%-12.9%-2.1%-2.8%-7.7%
Reading these numbers: We deliver the highest absolute return and a competitive Sharpe ratio. Our volatility is higher — that's the nature of concentrated mean-reversion trades. The Calmar ratio shows we earn roughly $4 for every $1 of maximum drawdown. QQQ and S&P have better Calmar ratios because passive indices have shallow drawdowns in a bull market — that won't hold in a correction.
Attribution by Symbol
SymbolTradesWin RateP&L% of Total
NVDA875.0%+$401,02242.4%
TSLA1154.5%+$229,25724.2%
AAPL955.6%+$130,04513.7%
PLTR450.0%+$81,5028.6%
AVGO250.0%+$56,3586.0%
MSTR2100%+$44,3614.7%
AMD1100%+$38,4914.1%
SPOT1100%+$37,0763.9%
HIMS2100%+$36,1483.8%
AMZN475.0%+$32,4483.4%
MSFT728.6%-$151,429-16.0%
Others (10)1457.1%+$11,2281.2%

Risk

Every investment strategy can lose money. Here is how we manage that risk, and what you should know about what could go wrong.

What We Control
What We Cannot Control

Technology

High-performance computing infrastructure. Proprietary machine learning models. Institutional-grade security and redundancy. All execution is automated with manual oversight capability.

Compliance & Service Providers

Structured in alignment with SEC guidelines. Available exclusively to accredited/qualified investors.

Administrator: Opus Fund Management

Prime Brokerage & Custodian: BNP Paribas

Research Partner: ACR Institute

Full documentation available upon request during due diligence.

Terms

Minimum Investment $1,000,000 USD / EUR / CHF
Management Fee 2% annually
Performance Fee 20% of profits above high-water mark — you don't pay performance fees on recovered losses
Lock-Up Period 18 months — we need this time horizon for the strategy to work through full market cycles
Redemption Quarterly with advance notice
Fund Liquidity $500,000,000 USD capacity
Administrator Opus Fund Management
Prime Brokerage & Custodian BNP Paribas
Research Partner ACR Institute (Zürich, Switzerland)
Plain language on fees: On a $1,000,000 investment, you pay $20,000/year in management fees regardless of performance. If the fund returns 20% ($200,000 profit), the performance fee is $40,000. Your net return in that scenario: $140,000, or 14%. We think that's a fair exchange for the risk-adjusted returns we aim to deliver.
The performance data in this document is a static snapshot. Live results update dynamically and can be viewed at the live performance dashboard.