N
Nobu Quantitative Research
About Nobu Quant

Trust the market.
Adapt your exposure systematically.

Nobu (信) in Japanese means trust. At Nobu Quant, we trust the market, trust the numbers, and trust our rigorous, byte-for-byte reproducible backtesting.

We never predict market crashes — we systematically decide how much of the market to own every day. Our 4-pillar architecture protects and compounds capital through four synchronized pillars:

  • 1 Pillar 1 – Dynamic Exposure Engine: Own more when markets are calm, own less when they’re volatile. Position size scales with turbulence, so leverage never works against us in storms.
  • 2 Pillar 2 – Credit Risk Brake: We watch the credit market as an early-warning system. When credit cracks, we cut exposure before the equity selloff lands — credit stress leads stock stress by about two weeks.
  • 3 Pillar 3 – Crisis Alpha Booster: When panic forces the market down 15–30%, we buy into the cheap panic and restore full strength — riding the bounce into the blast-off on the way back.
  • 4 Pillar 4 – Risk Appetite Selector: Your exposure ceiling. Pick Lite, Core ★, or Max to set how far the engine may gear up — same engine, your risk appetite.

The result: over a 2010–2026 simulated backtest, Nobu SPY Core and QQQ Core compounded at more than twice the annual rate of their buy-and-hold benchmarks, while posting lower maximum drawdowns than those benchmarks. The scorecard below shows the CAGR, Sharpe, drawdown, and terminal-wealth comparisons.

Nobu SPY Core
29.24% CAGR
CAGR 29.24% (vs 14.22% B&H) • Sharpe 1.12 (vs 0.78) • Max drawdown −26.85% (vs −33.72%) • Terminal wealth multiplier 7.7x vs B&H (2010–2026 simulated)
Nobu QQQ Core
41.43% CAGR
CAGR 41.43% (vs 18.96% B&H) • Sharpe 1.18 (vs 0.88) • Max drawdown −35.06% (vs −35.12%) • Terminal wealth multiplier 17.7x vs B&H (2010–2026 simulated)
See the full comparison Explore every Lite, Core, and Max tier against its buy-and-hold and static 3× references.

Full-period simulated results for 2010–2026. CAGR measures annualized compounding, maximum drawdown measures the deepest peak-to-trough decline, and Sharpe is the full-period excess Sharpe ratio. Green indicates a stronger result than the family buy-and-hold benchmark.

SPY familyNobu SPY tiers vs SPY and SPXL
StrategyCAGRMax DDSharpe
Nobu SPY Lite24.91%−23.64%1.11
Nobu SPY Core ★29.24%−26.85%1.12
Nobu SPY Max32.30%−29.89%1.11
SPY buy-and-hold14.22%−33.72%0.78
SPXL 3× reference29.35%−76.86%0.74
QQQ familyNobu QQQ tiers vs QQQ and TQQQ
StrategyCAGRMax DDSharpe
Nobu QQQ Lite33.43%−28.44%1.19
Nobu QQQ Core ★41.43%−35.06%1.18
Nobu QQQ Max47.95%−38.89%1.18
QQQ buy-and-hold18.96%−35.12%0.88
TQQQ 3× reference40.72%−81.66%0.85
Systematic 4-Pillar Architecture

How Nobu Out-Compounds the S&P 500: The 8-Chapter Visual Storyboard

Step through each coordinated pillar to see how dynamic volatility exposure, credit early warnings, panic liquidity provision, and stop-loss seatbelts beat both buy-and-hold and 3x leverage.

Architecture Storyboard
The Benchmark Titan

S&P 500 (SPY): America’s 500 Biggest Companies

The S&P 500 holds the 500 largest US companies (Apple, Microsoft, Nvidia, Amazon). Over 90% of professional Wall Street fund managers fail to beat it over 15 years. Beating this giant is the ultimate holy grail in investing.

SPY Buy & Hold: $1,000 → $9,155 (14.22% CAGR, 2010–2026 simulated)
📊 The Benchmark Baseline: SPY Buy & Hold — 14.22% CAGR (2010–2026 simulated)
Empirical Stress Testing

Full-Cycle Crisis Stress Testing: Nobu vs Buy & Hold

Direct, paired comparisons across complete market cycles (6 months pre-peak to 12 months post-trough).

Crisis Regime
6M Peak → 1Y Trough
Full-Cycle Return
Each series from own trough
Peak-to-Trough Decline
Nobu vs Benchmark
Time to Full Recovery
Nobu vs Benchmark
12-Mo Post-Trough Rally
Nobu vs Benchmark
* Methodology: Standardized Full-Cycle Window = 6M pre-peak to 12M post-trough. Recovery time measured independently for each strategy from its own trough to its prior peak. Source: S&P 500 & Nasdaq-100 official market cycle high/low dates.
Interactive Research Engine

Historical Backtesting & Compounding Simulator

Simulate any historical start date and holding horizon across 16.6 years of historical backtesting (2010–2026). Watch the portfolio rebase and compound daily against buy-and-hold benchmarks with realistic execution friction.

$
$
Monthly deposits are for illustration purposes only.
232 Months
Flexible
Nobu SPY Final Value
$71,810
+7,081% Total Return (2010–2026 simulated)
SPY Buy & Hold Value
$9,155
+816% Total Return
Terminal Wealth Multiple
7.7x
Outperformance vs Benchmark
Annualized Return (CAGR)
29.24%
Benchmark: 14.22%
Nobu SPY Algorithm Buy & Hold Benchmark
Compounded daily • Fills at Open • Realistic Friction
* Deterministic daily compounding ledger with realistic execution friction & transaction fees. Dataset: 4,180 daily verified sessions (2010–2026).
Quantitative Foundations

Core Research Insights: Academic Grounding & Empirical Truths

Our 4-pillar architecture is built upon peer-reviewed empirical finance research and rigorous Nobel-prize winning econometric foundations.

Pillar 01 • Volatility Drag

Volatility Clustering: Eliminate Geometric Drag

Market volatility is not constant; it clusters in violent temporal regimes. Holding fixed leverage through volatility spikes causes devastating mathematical compounding drag. Scaling leverage dynamically inversely to market turbulence protects accumulated capital.

• Research basis (citation snapshots, Aug 26, 2026):
• Moreira & Muir (2017), "Volatility-Managed Portfolios", Journal of Finance (847 citations).
In plain English: Research finds that changing how much the portfolio owns as volatility changes can improve risk-adjusted returns—the core idea behind Nobu’s dynamic exposure engine.
• Bollerslev (1986), "Generalized Autoregressive Conditional Heteroskedasticity", Journal of Econometrics (40,570 citations).
In plain English: Volatility comes in clusters: calm markets often stay calm for a while, while rough markets often stay rough—giving Nobu’s dynamic exposure engine a reason to change position size instead of driving at one speed in every condition.
Receipt (2010–2026 simulated): Nobu SPY Core +29.24% CAGR vs static 3× SPXL +21.03% — similar wealth, −26.85% vs −69.82% worst drawdown
Pillar 02 • Credit Radar

Debt Seniority: ~17-Day Macro Early Warning

Corporate debt is senior to equity in capital structures. Bond markets reprice insolvency and liquidity stress ~14–17 days before stock market selloffs accelerate. Tracking high-yield credit momentum provides an empirical early warning radar to shift into Treasury cash.

• Research basis (citation snapshots, Aug 26, 2026):
• Campbell, Hilscher & Szilagyi (2008), "In Search of Distress Risk", Journal of Finance (about 3,700 citations).
In plain English: Financial trouble leaves clues in company and market data, supporting Nobu’s decision to watch for stress before relying on stock prices alone to tell the story.
• Gilchrist & Zakrajšek (2012), "Credit Spreads and Business Cycle Fluctuations", American Economic Review (3,459 citations).
In plain English: When lenders suddenly demand much more interest from companies, credit stress is rising—giving Nobu’s credit risk brake a research-backed reason to reduce exposure as conditions worsen.
Receipt (2010–2026 simulated): Nobu QQQ Core +41.43% CAGR vs Nasdaq-100 +18.96% — same market, different driver
Pillar 03 • Crisis Alpha

Firesale Extraction: Crisis Alpha Booster

Deep 15%–30% market crashes trigger institutional mandate constraints, margin calls, and non-economic fire-sales. The Crisis Alpha Booster reserves cash specifically to supply liquidity into these dislocations, accumulating assets at generational discounts to ride explosive V-shaped rebounds.

• Research basis (citation snapshots, Aug 26, 2026):
• Brunnermeier & Pedersen (2009), "Market Liquidity and Funding Liquidity", Review of Financial Studies (7,756 citations).
In plain English: When financing gets tight, markets can become harder to trade and price moves can get bigger—supporting Nobu’s decision to keep exposure flexible when the road gets rough.
• Coval & Stafford (2007), "Asset Fire Sales (and Purchases) in Equity Markets", Journal of Financial Economics (2,335 citations).
In plain English: Big institutions selling under pressure can push prices below normal levels, supporting Nobu’s crisis alpha booster as it rebuilds exposure during recoveries rather than miss the drive out of a selloff.
Receipt: +97% COVID & +55% 2022-Bear Post-Trough Rebound Rally (SPY Core)
Pillar 04 • Risk Selector

Risk Appetite Selector: Choose Your Exposure Ceiling

Investors do not share the same risk appetite. Lite, Core ★, and Max set different exposure ceilings on the same systematic engine: higher ceilings can increase compounding potential, but also volatility and drawdown risk. Nobu tests this range against SPY or QQQ buy-and-hold and static 3× ETFs to compare the risk–return trade-off.

• Research basis (citation snapshots, Aug 26, 2026):
• Markowitz (1952), "Portfolio Selection", Journal of Finance (68,898 citations).
In plain English: The right balance between growth and risk depends on the driver, which is why Nobu offers several exposure ceilings instead of one setting for everyone.
• Frazzini & Pedersen (2014), "Betting Against Beta", Journal of Financial Economics (3,337 citations).
In plain English: More leverage is not automatically better: a carefully managed exposure ceiling can pursue attractive risk-adjusted returns without taking the maximum possible risk.
Receipt (2010–2026 simulated): Lite, Core ★, and Max use different exposure ceilings. Higher ceilings can increase compounding potential and can also increase drawdown risk; simulated results are not guarantees.
Rigor & Standards

Institutional Methodology & Engineering Moat

Engineered for full transparency, byte-for-byte reproducibility, realistic friction modeling, and frictionless execution.

01 • Transparency

Byte-for-Byte Reproducibility

Researchers and developers can re-run the research pipeline from raw daily adjusted market data and reproduce the exact equity curves down to the cent. Zero discretionary overrides.

02 • Timing Boundary

Zero-Lookahead Execution

Signals evaluated at Market Close $t−1$; orders execute strictly at Market Open $t$. Every series is lag-shifted and verified through unit-tested timing assertions.

03 • Realism

Friction & US Tax Engine

Idle cash held in SHV T-Bills. Rebalances account for 0.3bp spreads + SEC fees. Realistic US tax simulation models April 15 lump-sum payments and loss carryforward.

04 • Execution

Frictionless Simplicity

Trades once daily at the open in deep, liquid large-cap index ETFs. No high-frequency churning, no complicated options Greeks, and zero intraday screen monitoring.

Ways to engage

From today’s publication to your own daily game plan

Start free with today’s Core publication and paper testing. Subscribe for all six strategy weights and a daily delta report. nobuQQQ token is coming soon for transparent, rules-based on-chain access.

Historical results are simulated backtests and are not guarantees of future performance. Nobu Quant is not a registered investment adviser. Published weights are informational and are not personalized investment advice. nobuQQQ is a proposed tokenization architecture under development; it is not currently available for purchase and does not mean Nobu Quant holds customer funds or controls customer accounts.