Institutional · Systematic

Systematic alpha
across every
liquid market.

A fully autonomous AI trading system that identifies, sizes, executes, and exits positions across crypto and traditional markets — with zero emotional drift and adaptive risk management.

Sharpe · ETH
3.07
Max drawdown · NAS100
4.00%
Win rate · avg
82%
01 · Thesis
01 / 06

Markets are structurally
inefficient.

The edge is not prediction. It is consistent, disciplined execution of statistical advantages at scale — with zero emotional drift and adaptive risk management.

BlocQuant is the infrastructure that turns that edge into compounding, risk-adjusted returns across every liquid market.

02 · The problem
02 / 06

Most systematic strategies share
three failure modes.

01 · Decay
Signal decay as participants arbitrage the same factors.
What worked last cycle is table stakes this one. Alpha collapses into beta.
02 · Regime
Static models trained on regimes that no longer exist.
Backtests on 2015–2020 data tell you nothing about 2026 market microstructure.
03 · Drawdown
Drawdowns deep enough to trigger redemptions.
The strategy may recover. Your LPs won't wait to find out.

Institutional allocators are paying for alpha and receiving beta in a quant wrapper — with tail risk they did not price in.

03 · The system
03 / 06

A proprietary multi-factor framework
built on four pillars.

No manual overrides. No discretionary trades. Every decision is machine-generated, rules-based, and auditable.

I. Machine learning
Models trained on high-resolution market structure data — continuously retrained on live flow, never stale.
II. Regime-aware sizing
Exposure scales to volatility and liquidity conditions in real time — not on a calendar.
III. Pattern recognition
Statistical patterns across correlated assets, timeframes, and order-book dynamics.
IV. Systematic risk
Controls at the trade, instrument, and portfolio level — enforced by the execution layer itself.

The system does not forecast. It identifies asymmetries and deploys capital against them.

Part II · Performance

Performance
across asset classes.

One strategy · two worlds · consistent results
Ethereum · Crypto

Ethereum · ETH / USDT

Backtest · Dec 2023 → Apr 2026
1,966 trades
Sharpe
3.07
Max DD
4.20%
PF
4.67
Win rate
82.25%
Total trades
1,966
Strategy return
+438,576%
Buy & hold
−3.64%
The asset lost money. The strategy made 6.17M USDT on a 1,407 USDT base. This is the definition of alpha.
Equity curve · ETH / USDT
ETH equity curve
Bitcoin · Crypto

Bitcoin · BTC / USDT

Backtest · Dec 2023 → Apr 2026
1,960 trades
Max DD
6.67%
Profit factor
5.15
Win rate
82.24%
Total trades
1,960
Net P&L
6.29M
Strategy return
+447,195%
Denomination
USDT
Two crypto assets. Near-identical win rates above 82%. Drawdowns contained below 7%. The edge is structural, not asset-specific.
Equity curve · BTC / USDT
BTC equity curve
Nasdaq 100 · Traditional

Nasdaq 100 · NAS100

Backtest · Jan 2020 → Apr 2026
6 years · 4,659 trades
Sharpe
1.87
Max DD
4.00%
Profit factor
3.41
Long · WR / PF
72.20% / 3.53
Short · WR / PF
76.62% / 3.25
Total trades
4,659
Six years. COVID shock, ZIRP, the fastest hiking cycle on record, and two recession scares. The drawdown never exceeded 4%.
Metrics · NAS100
NAS100 metrics
Gold · Traditional

Gold · XAU / USD

Backtest · Jan 2022 → Apr 2026
4 years · 2,715 trades
Profit factor
5.56
Max DD
6.08%
Win rate
75.29%
Total trades
2,715
Window
Jan '22 → Apr '26
Four years spanning post-pandemic re-pricing and the US rate hiking cycle. Same framework. Different instrument. Same pattern.
Equity curve · Gold
Gold equity curve
04 · Coverage
04 / 06

The multi-asset spine.

One strategy. Four liquid markets. Consistent risk profile across every deployment.

Asset Class Window Sharpe Max DD Profit factor Win rate Trades
Ethereum Crypto · Perp Dec 2023 – Apr 2026 3.07 4.20% 4.67 82.25% 1,966
Bitcoin Crypto · Perp Dec 2023 – Apr 2026 — 6.67% 5.15 82.24% 1,960
Nasdaq 100 Index · Future Jan 2020 – Apr 2026 1.87 4.00% 3.41 72.20 / 76.62%L/S 4,659
Gold Commodity · Spot Jan 2022 – Apr 2026 — 6.08% 5.56 75.29% 2,715

All figures net of fees and slippage. Full methodology and trade-level data available under NDA in due-diligence materials.

05 · Why AI, why now
05 / 06

Static quant was built for a
market that no longer exists.

Fragmentation
Execution venues have fragmented. Price discovery is no longer centralized on a single exchange.
Algorithmic liquidity
Liquidity has shifted to algorithmic participants with sub-millisecond reaction times.
Regime velocity
Regimes change faster than human-calibrated models can adapt.
Our infrastructure
Adaptive. Continuous. Non-discretionary. Designed for this environment — not retrofitted to it.

Every market we deploy into produces the same pattern. Tight drawdowns. High win rates. Compounding returns.

06 · Terms
06 / 06

Structured for long-duration capital.

Raising allocations from institutional partners aligned with systematic capital deployment.

Minimum allocation
$5M
USD · per mandate
Fee structure
1% / 30%
Management / performance · high-water mark
Lock-up
12 mo
3% early-redemption fee
Liquidity
Quarterly
Redemptions · 60 days written notice
Contact

Institutional inquiries,
by introduction.

BLOCQUANT
BLOCQUANT.COM
info@blocquant.com