quantitative portfolio rebalancer
No emotions. No human error. Structural limits on every DCA dollar you deploy.
AQMath runs institutional-grade portfolio math on a secure backend engine — Risk Parity, KKT optimization, and volatility-weighted DCA. No accounts, no guesswork.
The engine loop, live
A simulation of the exact cycle the engine runs on our backend: recompute the covariance matrix, read the drawdown / downside-volatility regime, scale exposure continuously. Every number shown is real — taken from the production-path validation backtest.
- risk parity + KKT projection on live market data
- continuous de-risk — no indicators, no timers
- 0 bytes persisted by default — portfolio processed in-memory (opt-in signal service excepted)
What is AQMath, How It Works & Why
A privacy-first quantitative rebalancer for passive crypto investors.
AQMath is a quantitative portfolio rebalancer built for passive crypto investors.
It combines institutional-grade mathematics — Risk Parity, Karush-Kuhn-Tucker (KKT) optimization, and volatility-weighted Dollar-Cost Averaging — to keep your portfolio balanced without emotion, guesswork, or centralized data collection.
Non-Custodial Math Processing. Your portfolio data is sent only during DCA/Optimize and never persisted — unless you opt in to the optional signal service. No accounts. No tracking. Just math.
1. Add your tokens and target allocations (or let the engine calculate them using 180-day historical volatility).
2. Click SYNC to get live prices — spot prices come from Binance’s public market data, with CoinGecko as automatic fallback. Read-only market data: no API keys, no account linking.
3. Use DCA Distribution to invest new capital only into underweight tokens, filtered by volatility and trend.
4. (Black) Run the AQMath Engine to re-compute optimal weights using full covariance matrix and KKT projection.
Most portfolio tools either collect your data or offer only basic rebalancing. AQMath is different:
→ Institutional-grade math (same concepts used by multi-billion funds)
→ Non-Custodial — your portfolio stays in your browser’s localStorage, backend processing is ephemeral (opt-in signal service excepted)
→ Transparent, auditable logic (no black boxes)
→ €999 / year — transparent pricing, processed via USDC & EURC
Your balances are ephemeral — processed in-memory, never stored (the opt-in signal service excepted). No exchange API keys required. No data to sell.
Every cycle ends the same way: investors ride the rally, freeze in the crash, and sell the bottom — not for lack of intelligence, but because emotion always outruns discipline. AQMath removes emotion from the loop. While others refresh charts at 3 AM, your portfolio is already de-risking itself: as drawdown deepens and downside volatility rises, exposure scales toward stablecoins — automatically, continuously, by math you can audit line by line.
Deleverage Shield — validated on the production path
Proteus (v18) scales exposure continuously off a volatility-adaptive drawdown threshold — no indicators, no timers, no correlation gate. It ramps exposure toward its target steadily in either direction, and only rebalances when target exposure drifts meaningfully.
Replayed through the exact production path — a rolling 180-day window, the live re-optimisation cadence, persisted shield state and turnover at the live fee rate — Proteus (v18) held peak drawdown to 23.1% against 55.9% for Buy & Hold on a large-cap basket, at Sharpe 1.63 vs 1.37 and Calmar 2.00 vs 1.23. On a high-volatility alt basket it cut drawdown from 59.8% to 29.4% and won Calmar (1.29 vs 1.23) — but lost Sharpe there, 1.10 vs 1.18, and Buy & Hold ends both samples with more dollars. The shield’s edge is drawdown and consistency, not terminal wealth. On a sealed out-of-sample second half of an earlier survivor basket, Aegis (v14) still cut drawdown from 63.2% to 25.3%, but its Sharpe was lower than Buy & Hold’s (0.24 vs 0.30) — an earlier version of this page had those two numbers the wrong way round. Backtest baskets include survivor tokens; past results don’t guarantee future performance.
LIVE ENGINE Proteus (v18) is the production shield. Aegis (v14), its fixed-threshold predecessor, still runs as a warm-up fallback for portfolios too young to calibrate the adaptive threshold; where v14 figures appear on this site they are labelled as historical. The figures above are measured on the exact production path, not on a continuous full-history replay.
--run-the-backtest--community-signals
The covariance matrix runs on our secure backend. All computation is stateless — data is processed in-memory and discarded immediately. Nothing is written to disk.
- High-variance assets receive smaller dynamic caps
- Correlated assets are penalized through covariance
- Underweight assets are prioritized only when they improve the risk-balanced structure
- Core DCA distribution with volatility safety factors
- Live price sync (Binance / CoinGecko)
- Portfolio tracking in your browser — non-custodial
- Trend filter — buys the dip, skips tokens mid-rally
- Upgrade anytime to unlock Risk Parity + Deleverage Shield
- Risk Parity optimization with full Covariance & Variance Matrix
- Deleverage Modulator with continuous drawdown protection
- Dynamic volatility-based allocation caps
- Automatic 180-day historical data pipeline
- Unlimited token support and portfolio optimization
- DCA distribution with full safety pipeline
- Non-custodial privacy — portfolio stays in your browser (server-side storage only if you opt in)
- Shared Black chat — pseudonymous, 20-message rolling buffer, deletable anytime
- 365-day term from activation — annual access only
- 14-day EU right of withdrawal — firm annual term afterwards [details]
- Send a message — we review and activate within 48h