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-layer architecture protects and compounds capital through four common-sense safeguards:
The result: more than double to nearly triple the market’s annual compounding rate — 26.9% Compound Annual Growth Rate (CAGR) on Nobu SPY (vs 11.1% for S&P 500) and 46.6% CAGR on Nobu QQQ (vs 16.6% for Nasdaq-100) across 19+ years of historical backtesting.
Step through each coordinated layer to see how dynamic volatility exposure, credit early warnings, panic liquidity provision, and stop-loss seatbelts beat both buy-and-hold and 3x leverage.
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.
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 Nobu vs Benchmark |
Peak-to-Trough Decline Nobu vs Benchmark |
Time to Full Recovery Nobu vs Benchmark |
12-Mo Post-Trough Rally Nobu vs Benchmark |
|---|---|---|---|---|
|
2008 GFC
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2008 Global Financial Crisis (SPY)
• Window: 2007-04-11 → 2010-03-09
• Peak: 2007-10-09 (6M entry)
• Trough: 2009-03-09 (12M exit)
|
+31.84% vs −15.53% | −57.05% vs −55.19% | ~11 mos vs ~3.4 yrs | +138.37% vs +44.63% |
|
2011–12 Eurozone
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2011–2012 Eurozone Debt Crisis (SPY)
• Window: 2010-11-01 → 2012-10-03
• Peak: 2011-05-02 (6M entry)
• Trough: 2011-10-04 (12M exit)
|
+29.81% vs +27.52% | −24.97% vs −19.39% | ~2.5 mos vs ~4.5 mos | +32.40% vs +26.10% |
|
2018 Fed Crunch
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2018 Fed Tightening Crunch (SPY)
• Window: 2018-04-04 → 2019-12-24
• Peak: 2018-10-03 (6M entry)
• Trough: 2018-12-24 (12M exit)
|
+56.77% vs +26.04% | −17.16% vs −19.78% | ~3 mos vs ~4.0 mos | +35.60% vs +31.49% |
|
2020 COVID Shock
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2020 COVID Liquidity Shock (SPY)
• Window: 2019-08-21 → 2021-03-23
• Peak: 2020-02-19 (6M entry)
• Trough: 2020-03-23 (12M exit)
|
+46.28% vs +37.44% | −33.36% vs −33.72% | 70 days vs 140 days | +70.99% vs +77.50% |
|
2022 Rate Bear
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2022 Fed Rate-Shock Bear (SPY)
• Window: 2021-07-06 → 2023-10-12
• Peak: 2022-01-03 (6M entry)
• Trough: 2022-10-12 (12M exit)
|
+27.05% vs +3.61% | −22.77% vs −24.50% | 8 days vs ~1.2 yrs | +47.82% vs +26.29% |
|
2025 Trade War
?
2025 Trade & Tariff Shock (SPY)
• Window: 2024-07-02 → 2026-03-13
• Peak: 2025-01-02 (6M entry)
• Trough: 2025-03-13 (12M exit)
|
+52.47% vs +22.84% | −16.67% vs −5.68% | ~2.5 mos vs ~5 mos | +47.82% vs +21.52% |
Simulate any historical start date and holding horizon across 19+ years of historical backtesting (2007–2026). Watch the portfolio rebase and compound daily against buy-and-hold benchmarks with realistic execution friction.
Our 4-layer architecture is built upon peer-reviewed empirical finance research and rigorous Nobel-prize winning econometric foundations.
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.
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.
Deep 15%–30% market crashes trigger institutional mandate constraints, margin calls, and non-economic fire-sales. The Panic Bounce reserves cash specifically to supply liquidity into these dislocations, accumulating assets at generational discounts to ride explosive V-shaped rebounds.
While dynamic exposure models mitigate ordinary volatility, rare black-swan dislocations can produce severe gap-downs. An always-on portfolio stop-loss acts as a non-negotiable circuit breaker, bounding tail losses and ensuring 100% capital survival to compound into the future.
Engineered for full transparency, byte-for-byte reproducibility, realistic friction modeling, and frictionless execution.
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.
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.
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.
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.
From free open-source backtest datasets to live signals, full Python codebases, and autonomous quant agent nodes.
Complete 19+ year transaction-level backtest ledger and daily equity curves in CSV/JSON format for independent verification.
Daily pre-market target exposure weights and credit gate alerts broadcasted via Telegram and webhook.
Complete, inspectable Python 3.11 backtesting engine with full strategy parameters. Protected against resale via cryptographic buyer watermarking.
Turnkey, self-hosted Docker execution node. Zero-touch pre-market signal calculation, automated Alpaca execution, and private Telegram bot controls.